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Presented at CODE BLUE 2023, this project titled Enhanced Vulnerability Hunting in WDM Drivers with Symbolic Execution and Taint Analysis introduces IOCTLance, a tool that enhances its capacity to detect various vulnerability types in Windows Driver Model (WDM) drivers. In a comprehensive evaluation involving 104 known vulnerable WDM drivers and 328 unknow n ones, IOCTLance successfully unveiled 117 previously unidentified vulnerabilities within 26 distinct drivers. As a result, 41 CVEs were reported, encompassing 25 cases of denial of service, 5 instances of insufficient access control, and 11 examples of elevation of privilege.
FreshRSS docker build .
dpkg --add-architecture i386
apt-get update
apt-get install git build-essential python3 python3-pip python3-dev htop vim sudo \
openjdk-8-jdk zlib1g:i386 libtinfo5:i386 libstdc++6:i386 libgcc1:i386 \
libc6:i386 libssl-dev nasm binutils-multiarch qtdeclarative5-dev libpixman-1-dev \
libglib2.0-dev debian-archive-keyring debootstrap libtool libreadline-dev cmake \
libffi-dev libxslt1-dev libxml2-dev
pip install angr==9.2.18 ipython==8.5.0 ipdb==0.13.9
# python3 analysis/ioctlance.py -h
usage: ioctlance.py [-h] [-i IOCTLCODE] [-T TOTAL_TIMEOUT] [-t TIMEOUT] [-l LENGTH] [-b BOUND]
[-g GLOBAL_VAR] [-a ADDRESS] [-e EXCLUDE] [-o] [-r] [-c] [-d]
path
positional arguments:
path dir (including subdirectory) or file path to the driver(s) to analyze
optional arguments:
-h, --help show this help message and exit
-i IOCTLCODE, --ioctlcode IOCTLCODE
analyze specified IoControlCode (e.g. 22201c)
-T TOTAL_TIMEOUT, --total_timeout TOTAL_TIMEOUT
total timeout for the whole symbolic execution (default 1200, 0 to unlimited)
-t TIMEOUT, --timeout TIMEOUT
timeout for analyze each IoControlCode (default 40, 0 to unlimited)
-l LENGTH, --length LENGTH
the limit of number of instructions for technique L engthLimiter (default 0, 0
to unlimited)
-b BOUND, --bound BOUND
the bound for technique LoopSeer (default 0, 0 to unlimited)
-g GLOBAL_VAR, --global_var GLOBAL_VAR
symbolize how many bytes in .data section (default 0 hex)
-a ADDRESS, --address ADDRESS
address of ioctl handler to directly start hunting with blank state (e.g.
140005c20)
-e EXCLUDE, --exclude EXCLUDE
exclude function address split with , (e.g. 140005c20,140006c20)
-o, --overwrite overwrite x.sys.json if x.sys has been analyzed (default False)
-r, --recursion do not kill state if detecting recursion (default False)
-c, --complete get complete base state (default False)
-d, --debug print debug info while analyzing (default False)
# python3 evaluation/statistics.py -h
usage: statistics.py [-h] [-w] path
positional arguments:
path target dir or file path
optional arguments:
-h, --help show this help message and exit
-w, --wdm copy the wdm drivers into <path>/wdm
APKDeepLens is a Python based tool designed to scan Android applications (APK files) for security vulnerabilities. It specifically targets the OWASP Top 10 mobile vulnerabilities, providing an easy and efficient way for developers, penetration testers, and security researchers to assess the security posture of Android apps.
APKDeepLens is a Python-based tool that performs various operations on APK files. Its main features include:
To use APKDeepLens, you'll need to have Python 3.8 or higher installed on your system. You can then install APKDeepLens using the following command:
git clone https://github.com/d78ui98/APKDeepLens/tree/main
cd /APKDeepLens
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
python APKDeepLens.py --help
git clone https://github.com/d78ui98/APKDeepLens/tree/main
cd \APKDeepLens
python3 -m venv venv
.\venv\Scripts\activate
pip install -r .\requirements.txt
python APKDeepLens.py --help
To simply scan an APK, use the below command. Mention the apk file with -apk argument. Once the scan is complete, a detailed report will be displayed in the console.
python3 APKDeepLens.py -apk file.apk
If you've already extracted the source code and want to provide its path for a faster scan you can use the below command. Mention the source code of the android application with -source parameter.
python3 APKDeepLens.py -apk file.apk -source <source-code-path>
To generate detailed PDF and HTML reports after the scan you can pass -report argument as mentioned below.
python3 APKDeepLens.py -apk file.apk -report
We welcome contributions to the APKDeepLens project. If you have a feature request, bug report, or proposal, please open a new issue here.
For those interested in contributing code, please follow the standard GitHub process. We'll review your contributions as quickly as possible :)
drozer (formerly Mercury) is the leading security testing framework for Android.
drozer allows you to search for security vulnerabilities in apps and devices by assuming the role of an app and interacting with the Dalvik VM, other apps' IPC endpoints and the underlying OS.
drozer provides tools to help you use, share and understand public Android exploits. It helps you to deploy a drozer Agent to a device through exploitation or social engineering. Using weasel (WithSecure's advanced exploitation payload) drozer is able to maximise the permissions available to it by installing a full agent, injecting a limited agent into a running process, or connecting a reverse shell to act as a Remote Access Tool (RAT).
drozer is a good tool for simulating a rogue application. A penetration tester does not have to develop an app with custom code to interface with a specific content provider. Instead, drozer can be used with little to no programming experience required to show the impact of letting certain components be exported on a device.
drozer is open source software, maintained by WithSecure, and can be downloaded from: https://labs.withsecure.com/tools/drozer/
To help with making sure drozer can be run on modern systems, a Docker container was created that has a working build of Drozer. This is currently the recommended method of using Drozer on modern systems.
Note: On Windows please ensure that the path to the Python installation and the Scripts folder under the Python installation are added to the PATH environment variable.
Note: On Windows please ensure that the path to javac.exe is added to the PATH environment variable.
git clone https://github.com/WithSecureLabs/drozer.git
cd drozer
python setup.py bdist_wheel
sudo pip install dist/drozer-2.x.x-py2-none-any.whl
git clone https://github.com/WithSecureLabs/drozer.git
cd drozer
make deb
sudo dpkg -i drozer-2.x.x.deb
git clone https://github.com/WithSecureLabs/drozer.git
cd drozer
make rpm
sudo rpm -I drozer-2.x.x-1.noarch.rpm
NOTE: Windows Defender and other Antivirus software will flag drozer as malware (an exploitation tool without exploit code wouldn't be much fun!). In order to run drozer you would have to add an exception to Windows Defender and any antivirus software. Alternatively, we recommend running drozer in a Windows/Linux VM.
git clone https://github.com/WithSecureLabs/drozer.git
cd drozer
python.exe setup.py bdist_msi
Run dist/drozer-2.x.x.win-x.msi
Drozer can be installed using Android Debug Bridge (adb).
Download the latest Drozer Agent here.
$ adb install drozer-agent-2.x.x.apk
You should now have the drozer Console installed on your PC, and the Agent running on your test device. Now, you need to connect the two and you're ready to start exploring.
We will use the server embedded in the drozer Agent to do this.
If using the Android emulator, you need to set up a suitable port forward so that your PC can connect to a TCP socket opened by the Agent inside the emulator, or on the device. By default, drozer uses port 31415:
$ adb forward tcp:31415 tcp:31415
Now, launch the Agent, select the "Embedded Server" option and tap "Enable" to start the server. You should see a notification that the server has started.
Then, on your PC, connect using the drozer Console:
On Linux:
$ drozer console connect
On Windows:
> drozer.bat console connect
If using a real device, the IP address of the device on the network must be specified:
On Linux:
$ drozer console connect --server 192.168.0.10
On Windows:
> drozer.bat console connect --server 192.168.0.10
You should be presented with a drozer command prompt:
selecting f75640f67144d9a3 (unknown sdk 4.1.1)
dz>
The prompt confirms the Android ID of the device you have connected to, along with the manufacturer, model and Android software version.
You are now ready to start exploring the device.
| Command | Description |
|---|---|
| run | Executes a drozer module |
| list | Show a list of all drozer modules that can be executed in the current session. This hides modules that you do not have suitable permissions to run. |
| shell | Start an interactive Linux shell on the device, in the context of the Agent process. |
| cd | Mounts a particular namespace as the root of session, to avoid having to repeatedly type the full name of a module. |
| clean | Remove temporary files stored by drozer on the Android device. |
| contributors | Displays a list of people who have contributed to the drozer framework and modules in use on your system. |
| echo | Print text to the console. |
| exit | Terminate the drozer session. |
| help | Display help about a particular command or module. |
| load | Load a file containing drozer commands, and execute them in sequence. |
| module | Find and install additional drozer modules from the Internet. |
| permissions | Display a list of the permissions granted to the drozer Agent. |
| set | Store a value in a variable that will be passed as an environment variable to any Linux shells spawned by drozer. |
| unset | Remove a named variable that drozer passes to any Linux shells that it spawns. |
drozer is released under a 3-clause BSD License. See LICENSE for full details.
drozer is Open Source software, made great by contributions from the community.
Bug reports, feature requests, comments and questions can be submitted here.
There’s little rest for your hard-working smartphone. If you’re like many professionals today, you use it for work, play, and a mix of personal business in between. Now, what if something went wrong with that phone, like loss or theft? Worse yet, what if your smartphone got hacked? Let’s try and keep that from happening to you.
Globally, plenty of people pull double duty with their smartphones. In Spain, one survey found that 55% of people use the same phone for a mix of personal and and work activity. The same survey showed that up to half of people interviewed in Japan, Australia, and the U.S. do so as well, while nations like the UK and Germany trailed at 31% and 23% respectively.
Whether these figures trend on the low or high end, the security implications remain constant. A smartphone loaded with business and personal data makes for a desirable target. Hackers target smartphones because they’re often unprotected, which gives hackers an easy “in” to your personal information and to any corporate networks you may use. It’s like two hacks with one stone.
Put simply, as a working professional with a smartphone, you’re a high-value target.
As both a parent and a professional, I put together a few things you can do to protect your smartphone from hacks so that you can keep your personal and work life safe:
First up, the basics. Locking your phone with facial ID, a fingerprint, pattern or a pin is your most basic form of protection, particularly in the event of loss or theft. (Your options will vary depending on the device, operating system, and manufacturer.) Take it a step further for even more protection. Secure the accounts on your phone with strong passwords and use two-factor authentication on the apps that offer it, which doubles your line of defense.
Or, put another way, don’t hop onto public Wi-Fi networks without protection. A VPN masks your connection from hackers allowing you to connect privately when you are on unsecure public networks at airports, cafes, hotels, and the like. With a VPN connection, you’ll know that your sensitive data, documents, and activities you do are protected from snooping, which is definitely a great feeling given the amount of personal and professional business we manage with our smartphones.
Both Google Play and Apple’s App Store have measures in place to help prevent potentially dangerous apps from making it into their stores. Malicious apps are often found outside of the app stores, which can run in the background and compromise your personal data like passwords, credit card numbers, and more—practically everything that you keep on your phone. Further, when you are in the app stores, look closely at the descriptions and reviews for apps before you download them. Malicious apps and counterfeits can still find their way into stores, and here are a few ways you can keep those bad apps from getting onto your phone.
Backing up your phone is always a good idea for two reasons:
Both iPhones and Android phones have straightforward ways of backing up your phone regularly.
Worst case scenario—your phone is gone. Really gone. Either it’s hopelessly lost or got stolen. What now? Lock it remotely or even wipe its data entirely. While that last bit about wiping the phone seems like a drastic move, if you maintain regular backups as mentioned above, your data is secure in the cloud—ready for you to restore. In all, this means that hackers won’t be able to access you, or your company’s, sensitive information—which can keep you out of trouble and your professional business safe. Apple provides iOS users with a step-by-step guide for remotely wiping devices, and Google offers up a guide for Android users as well.
We all download apps, use them once, and then forget they are on our phone. Take a few moments to swipe through your screen and see which ones you’re truly done with and delete them along with their data. Some apps have an account associated with them that may store data off your phone as well. Take the extra step and delete those accounts so any off-phone data is deleted.
The reason for this is that every extra app is another app that needs updating or that may have a security issue associated with it. In a time of data breaches and vulnerabilities, deleting old apps is a smart move. As for the ones you keep, update them regularly and turn on auto-updates if that’s an option. Updates not only introduce new features to apps, but they also often address security issues too.
With so much of your life on your phone, getting security software installed on it can protect you and the things you keep on your phone. Whether you’re an Android owner or iOS owner, mobile security software can keep your data, your shopping, and payments secure.
The post 7 Tips to Protect Your Smartphone from Getting Hacked appeared first on McAfee Blog.
Exploitation and scanning tool specifically designed for Jenkins versions <= 2.441 & <= LTS 2.426.2. It leverages CVE-2024-23897 to assess and exploit vulnerabilities in Jenkins instances.
Ensure you have the necessary permissions to scan and exploit the target systems. Use this tool responsibly and ethically.
python CVE-2024-23897.py -t <target> -p <port> -f <file>
or
python CVE-2024-23897.py -i <input_file> -f <file>
Parameters: - -t or --target: Specify the target IP(s). Supports single IP, IP range, comma-separated list, or CIDR block. - -i or --input-file: Path to input file containing hosts in the format of http://1.2.3.4:8080/ (one per line). - -o or --output-file: Export results to file (optional). - -p or --port: Specify the port number. Default is 8080 (optional). - -f or --file: Specify the file to read on the target system.
-i INPUT_FILE). -o OUTPUT_FILE).Contributions are welcome. Please feel free to fork, modify, and make pull requests or report issues.
Alexander Hagenah - URL - Twitter
This tool is meant for educational and professional purposes only. Unauthorized scanning and exploiting of systems is illegal and unethical. Always ensure you have explicit permission to test and exploit any systems you target.
SploitScan is a powerful and user-friendly tool designed to streamline the process of identifying exploits for known vulnerabilities and their respective exploitation probability. Empowering cybersecurity professionals with the capability to swiftly identify and apply known and test exploits. It's particularly valuable for professionals seeking to enhance their security measures or develop robust detection strategies against emerging threats.
Regular:
python sploitscan.py CVE-YYYY-NNNNN
Enter one or more CVE IDs to fetch data. Separate multiple CVE IDs with spaces.
python sploitscan.py CVE-YYYY-NNNNN CVE-YYYY-NNNNN
Optional: Export the results to a JSON or CSV file. Specify the format: 'json' or 'csv'.
python sploitscan.py CVE-YYYY-NNNNN -e JSON
The Patching Prioritization System in SploitScan provides a strategic approach to prioritizing security patches based on the severity and exploitability of vulnerabilities. It's influenced by the model from CVE Prioritizer, with enhancements for handling publicly available exploits. Here's how it works:
This system assists users in making informed decisions on which vulnerabilities to patch first, considering both their potential impact and the likelihood of exploitation. Thresholds can be changed to your business needs.
Contributions are welcome. Please feel free to fork, modify, and make pull requests or report issues.
Alexander Hagenah - URL - Twitter
SqliSniper is a robust Python tool designed to detect time-based blind SQL injections in HTTP request headers. It enhances the security assessment process by rapidly scanning and identifying potential vulnerabilities using multi-threaded, ensuring speed and efficiency. Unlike other scanners, SqliSniper is designed to eliminates false positives through and send alerts upon detection, with the built-in Discord notification functionality.
git clone https://github.com/danialhalo/SqliSniper.git
cd SqliSniper
chmod +x sqlisniper.py
pip3 install -r requirements.txt
This will display help for the tool. Here are all the options it supports.
ubuntu:~/sqlisniper$ ./sqlisniper.py -h
███████╗ ██████╗ ██╗ ██╗ ███████╗███╗ ██╗██╗██████╗ ███████╗██████╗
██╔════╝██╔═══██╗██║ ██║ ██╔════╝████╗ ██║██║██╔══██╗██╔════╝██╔══██╗
██████╗██║ ██║██║ ██║ ███████╗██╔██╗ ██║██║██████╔╝█████╗ ██████╔╝
╚════██║██║▄▄ ██║██║ ██║ ╚════██║██║╚██╗██║██║██╔═══╝ ██╔══╝ ██╔══██╗
███████║╚██ ███╔╝███████╗██║ ███████║██║ ╚████║██║██║ ███████╗██║ ██║
╚══════╝ ╚══▀▀═╝ ╚══════╝╚═╝ ╚══════╝╚═╝ ╚═══╝╚═╝╚═╝ ╚══════╝╚═╝ ╚═╝
-: By Muhammad Danial :-
usage: sqlisniper.py [-h] [-u URL] [-r URLS_FILE] [-p] [--proxy PROXY] [--payload PA YLOAD] [--single-payload SINGLE_PAYLOAD] [--discord DISCORD] [--headers HEADERS]
[--threads THREADS]
Detect SQL injection by sending malicious queries
options:
-h, --help show this help message and exit
-u URL, --url URL Single URL for the target
-r URLS_FILE, --urls_file URLS_FILE
File containing a list of URLs
-p, --pipeline Read from pipeline
--proxy PROXY Proxy for intercepting requests (e.g., http://127.0.0.1:8080)
--payload PAYLOAD File containing malicious payloads (default is payloads.txt)
--single-payload SINGLE_PAYLOAD
Single payload for testing
--discord DISCORD Discord Webhook URL
--headers HEADERS File containing headers (default is headers.txt)
--threads THREADS Number of threads
The url can be provided with -u flag for single site scan
./sqlisniper.py -u http://example.com
The -r flag allows SqliSniper to read a file containing multiple URLs for simultaneous scanning.
./sqlisniper.py -r url.txt
The SqliSniper can also worked with the pipeline input with -p flag
cat url.txt | ./sqlisniper.py -p
The pipeline feature facilitates seamless integration with other tools. For instance, you can utilize tools like subfinder and httpx, and then pipe their output to SqliSniper for mass scanning.
subfinder -silent -d google.com | sort -u | httpx -silent | ./sqlisniper.py -p
By default the SqliSniper use the payloads.txt file. However --payload flag can be used for providing custom payloads file.
./sqlisniper.py -u http://example.com --payload mssql_payloads.txt
While using the custom payloads file, ensure that you substitute the sleep time with %__TIME_OUT__%. SqliSniper dynamically adjusts the sleep time iteratively to mitigate potential false positives. The payloads file should look like this.
ubuntu:~/sqlisniper$ cat payloads.txt
0\"XOR(if(now()=sysdate(),sleep(%__TIME_OUT__%),0))XOR\"Z
"0"XOR(if(now()=sysdate()%2Csleep(%__TIME_OUT__%)%2C0))XOR"Z"
0'XOR(if(now()=sysdate(),sleep(%__TIME_OUT__%),0))XOR'Z
If you want to only test with the single payload --single-payload flag can be used. Make sure to replace the sleep time with %__TIME_OUT__%
./sqlisniper.py -r url.txt --single-payload "0'XOR(if(now()=sysdate(),sleep(%__TIME_OUT__%),0))XOR'Z"
Headers are saved in the file headers.txt for scanning custom header save the custom HTTP Request Header in headers.txt file.
ubuntu:~/sqlisniper$ cat headers.txt
User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64)
X-Forwarded-For: 127.0.0.1
SqliSniper also offers Discord alert notifications, enhancing its functionality by providing real-time alerts through Discord webhooks. This feature proves invaluable during large-scale scans, allowing prompt notifications upon detection.
./sqlisniper.py -r url.txt --discord <web_hookurl>
Threads can be defined with --threads flag
./sqlisniper.py -r url.txt --threads 10
Note: It is crucial to consider that employing a higher number of threads might lead to potential false positives or overlooking valid issues. Due to the nature of time-based SQL injection it is recommended to use lower thread for more accurate detection.
SqliSniper is made in python with lots of <3 by @Muhammad Danial.
This repo contains the code for our USENIX Security '23 paper "ARGUS: A Framework for Staged Static Taint Analysis of GitHub Workflows and Actions". Argus is a comprehensive security analysis tool specifically designed for GitHub Actions. Built with an aim to enhance the security of CI/CD workflows, Argus utilizes taint-tracking techniques and an impact classifier to detect potential vulnerabilities in GitHub Action workflows.
Visit our website - secureci.org for more information.
Taint-Tracking: Argus uses sophisticated algorithms to track the flow of potentially untrusted data from specific sources to security-critical sinks within GitHub Actions workflows. This enables the identification of vulnerabilities that could lead to code injection attacks.
Impact Classifier: Argus classifies identified vulnerabilities into High, Medium, and Low severity classes, providing a clearer understanding of the potential impact of each identified vulnerability. This is crucial in prioritizing mitigation efforts.
This Python script provides a command line interface for interacting with GitHub repositories and GitHub actions.
python argus.py --mode [mode] --url [url] [--output-folder path_to_output] [--config path_to_config] [--verbose] [--branch branch_name] [--commit commit_hash] [--tag tag_name] [--action-path path_to_action] [--workflow-path path_to_workflow]--mode: The mode of operation. Choose either 'repo' or 'action'. This parameter is required.--url: The GitHub URL. Use USERNAME:TOKEN@URL for private repos. This parameter is required.--output-folder: The output folder. The default value is '/tmp'. This parameter is optional.--config: The config file. This parameter is optional.--verbose: Verbose mode. If this option is provided, the logging level is set to DEBUG. Otherwise, it is set to INFO. This parameter is optional.--branch: The branch name. You must provide exactly one of: --branch, --commit, --tag. This parameter is optional.--commit: The commit hash. You must provide exactly one of: --branch, --commit, --tag. This parameter is optional.--tag: The tag. You must provide exactly one of: --branch, --commit, --tag. This parameter is optional.--action-path: The (relative) path to the action. You cannot provide --action-path in repo mode. This parameter is optional.--workflow-path: The (relative) path to the workflow. You cannot provide --workflow-path in action mode. This parameter is optional.To use this script to interact with a GitHub repo, you might run a command like the following:
python argus.py --mode repo --url https://github.com/username/repo.git --branch masterThis would run the script in repo mode on the master branch of the specified repository.
Argus can be run inside a docker container. To do so, follow the steps:
results folderYou can view SARIF results either through an online viewer or with a Visual Studio Code (VSCode) extension.
Online Viewer: The SARIF Web Viewer is an online tool that allows you to visualize SARIF files. You can upload your SARIF file (argus_report.sarif) directly to the website to view the results.
VSCode Extension: If you prefer to use VSCode, you can install the SARIF Viewer extension. After installing the extension, you can open your SARIF file (argus_report.sarif) in VSCode. The results will appear in the SARIF Explorer pane, which provides a detailed and navigable view of the results.
Remember to handle the SARIF file with care, especially if it contains sensitive information from your codebase.
If there is an issue with needing the Github authorization for running, you can provide username:TOKEN in the GITHUB_CREDS environment variable. This will be used for all the requests made to Github. Note, we do not store this information anywhere, neither create any thing in the Github account - we only use this for cloning the repositories.
Argus is an open-source project, and we welcome contributions from the community. Whether it's reporting a bug, suggesting a feature, or writing code, your contributions are always appreciated!
If you use Argus in your research, please cite our paper:
@inproceedings{muralee2023Argus,
title={ARGUS: A Framework for Staged Static Taint Analysis of GitHub Workflows and Actions},
author={S. Muralee, I. Koishybayev, A. Nahapetyan, G. Tystahl, B. Reaves, A. Bianchi, W. Enck,
A. Kapravelos, A. Machiry},
booktitle={32st USENIX Security Symposium (USENIX Security 23)},
year={2023},
}
RAVEN (Risk Analysis and Vulnerability Enumeration for CI/CD) is a powerful security tool designed to perform massive scans for GitHub Actions CI workflows and digest the discovered data into a Neo4j database. Developed and maintained by the Cycode research team.
With Raven, we were able to identify and report security vulnerabilities in some of the most popular repositories hosted on GitHub, including:
We listed all vulnerabilities discovered using Raven in the tool Hall of Fame.
The tool provides the following capabilities to scan and analyze potential CI/CD vulnerabilities:
Possible usages for Raven:
This tool provides a reliable and scalable solution for CI/CD security analysis, enabling users to query bad configurations and gain valuable insights into their codebase's security posture.
In the past year, Cycode Labs conducted extensive research on fundamental security issues of CI/CD systems. We examined the depths of many systems, thousands of projects, and several configurations. The conclusion is clear – the model in which security is delegated to developers has failed. This has been proven several times in our previous content:
Each of the vulnerabilities above has unique characteristics, making it nearly impossible for developers to stay up to date with the latest security trends. Unfortunately, each vulnerability shares a commonality – each exploitation can impact millions of victims.
It was for these reasons that Raven was created, a framework for CI/CD security analysis workflows (and GitHub Actions as the first use case). In our focus, we examined complex scenarios where each issue isn't a threat on its own, but when combined, they pose a severe threat.
To get started with Raven, follow these installation instructions:
Step 1: Install the Raven package
pip3 install raven-cycodeStep 2: Setup a local Redis server and Neo4j database
docker run -d --name raven-neo4j -p7474:7474 -p7687:7687 --env NEO4J_AUTH=neo4j/123456789 --volume raven-neo4j:/data neo4j:5.12
docker run -d --name raven-redis -p6379:6379 --volume raven-redis:/data redis:7.2.1Another way to setup the environment is by running our provided docker compose file:
git clone https://github.com/CycodeLabs/raven.git
cd raven
make setupStep 3: Run Raven Downloader
Org mode:
raven download org --token $GITHUB_TOKEN --org-name RavenDemoCrawl mode:
raven download crawl --token $GITHUB_TOKEN --min-stars 1000Step 4: Run Raven Indexer
raven indexStep 5: Inspect the results through the reporter
raven report --format rawAt this point, it is possible to inspect the data in the Neo4j database, by connecting http://localhost:7474/browser/.
Raven is using two primary docker containers: Redis and Neo4j. make setup will run a docker compose command to prepare that environment.
The tool contains three main functionalities, download and index and report.
usage: raven download org [-h] --token TOKEN [--debug] [--redis-host REDIS_HOST] [--redis-port REDIS_PORT] [--clean-redis] --org-name ORG_NAME
options:
-h, --help show this help message and exit
--token TOKEN GITHUB_TOKEN to download data from Github API (Needed for effective rate-limiting)
--debug Whether to print debug statements, default: False
--redis-host REDIS_HOST
Redis host, default: localhost
--redis-port REDIS_PORT
Redis port, default: 6379
--clean-redis, -cr Whether to clean cache in the redis, default: False
--org-name ORG_NAME Organization name to download the workflowsusage: raven download crawl [-h] --token TOKEN [--debug] [--redis-host REDIS_HOST] [--redis-port REDIS_PORT] [--clean-redis] [--max-stars MAX_STARS] [--min-stars MIN_STARS]
options:
-h, --help show this help message and exit
--token TOKEN GITHUB_TOKEN to download data from Github API (Needed for effective rate-limiting)
--debug Whether to print debug statements, default: False
--redis-host REDIS_HOST
Redis host, default: localhost
--redis-port REDIS_PORT
Redis port, default: 6379
--clean-redis, -cr Whether to clean cache in the redis, default: False
--max-stars MAX_STARS
Maximum number of stars for a repository
--min-stars MIN_STARS
Minimum number of stars for a repository, default : 1000usage: raven index [-h] [--redis-host REDIS_HOST] [--redis-port REDIS_PORT] [--clean-redis] [--neo4j-uri NEO4J_URI] [--neo4j-user NEO4J_USER] [--neo4j-pass NEO4J_PASS]
[--clean-neo4j] [--debug]
options:
-h, --help show this help message and exit
--redis-host REDIS_HOST
Redis host, default: localhost
--redis-port REDIS_PORT
Redis port, default: 6379
--clean-redis, -cr Whether to clean cache in the redis, default: False
--neo4j-uri NEO4J_URI
Neo4j URI endpoint, default: neo4j://localhost:7687
--neo4j-user NEO4J_USER
Neo4j username, default: neo4j
--neo4j-pass NEO4J_PASS
Neo4j password, default: 123456789
--clean-neo4j, -cn Whether to clean cache, and index f rom scratch, default: False
--debug Whether to print debug statements, default: Falseusage: raven report [-h] [--redis-host REDIS_HOST] [--redis-port REDIS_PORT] [--clean-redis] [--neo4j-uri NEO4J_URI]
[--neo4j-user NEO4J_USER] [--neo4j-pass NEO4J_PASS] [--clean-neo4j]
[--tag {injection,unauthenticated,fixed,priv-esc,supply-chain}]
[--severity {info,low,medium,high,critical}] [--queries-path QUERIES_PATH] [--format {raw,json}]
{slack} ...
positional arguments:
{slack}
slack Send report to slack channel
options:
-h, --help show this help message and exit
--redis-host REDIS_HOST
Redis host, default: localhost
--redis-port REDIS_PORT
Redis port, default: 6379
--clean-redis, -cr Whether to clean cache in the redis, default: False
--neo4j-uri NEO4J_URI
Neo4j URI endpoint, default: neo4j://localhost:7687
--neo4j-user NEO4J_USER
Neo4j username, default: neo4j
--neo4j-pass NEO4J_PASS
Neo4j password, default: 123456789
--clean-neo4j, -cn Whether to clean cache, and index from scratch, default: False
--tag {injection,unauthenticated,fixed,priv-esc,supply-chain}, -t {injection,unauthenticated,fixed,priv-esc,supply-chain}
Filter queries with specific tag
--severity {info,low,medium,high,critical}, -s {info,low,medium,high,critical}
Filter queries by severity level (default: info)
--queries-path QUERIES_PATH, -dp QUERIES_PATH
Queries folder (default: library)
--format {raw,json}, -f {raw,json}
Report format (default: raw)Retrieve all workflows and actions associated with the organization.
raven download org --token $GITHUB_TOKEN --org-name microsoft --org-name google --debugScrape all publicly accessible GitHub repositories.
raven download crawl --token $GITHUB_TOKEN --min-stars 100 --max-stars 1000 --debugAfter finishing the download process or if interrupted using Ctrl+C, proceed to index all workflows and actions into the Neo4j database.
raven index --debugNow, we can generate a report using our query library.
raven report --severity high --tag injection --tag unauthenticatedFor effective rate limiting, you should supply a Github token. For authenticated users, the next rate limiting applies:
Dockerfile (without action.yml). Currently, this behavior isn't supported.docker://... URL. Currently, this behavior isn't supported.data. That action parameter may be used in a run command: - run: echo ${{ inputs.data }}, which creates a path for a code execution.GITHUB_ENV. This may utilize the previous taint analysis as well.actions/github-script has an interesting threat landscape. If it is, it can be modeled in the graph.If you liked Raven, you would probably love our Cycode platform that offers even more enhanced capabilities for visibility, prioritization, and remediation of vulnerabilities across the software delivery.
If you are interested in a robust, research-driven Pipeline Security, Application Security, or ASPM solution, don't hesitate to get in touch with us or request a demo using the form https://cycode.com/book-a-demo/.
Bugsy is a command-line interface (CLI) tool that provides automatic security vulnerability remediation for your code. It is the community edition version of Mobb, the first vendor-agnostic automated security vulnerability remediation tool. Bugsy is designed to help developers quickly identify and fix security vulnerabilities in their code.
Mobb is the first vendor-agnostic automatic security vulnerability remediation tool. It ingests SAST results from Checkmarx, CodeQL (GitHub Advanced Security), OpenText Fortify, and Snyk and produces code fixes for developers to review and commit to their code.
Bugsy has two modes - Scan (no SAST report needed) & Analyze (the user needs to provide a pre-generated SAST report from one of the supported SAST tools).
Scan
Analyze
This is a community edition version that only analyzes public GitHub repositories. Analyzing private repositories is allowed for a limited amount of time. Bugsy does not detect any vulnerabilities in your code, it uses findings detected by the SAST tools mentioned above.
You can simply run Bugsy from the command line, using npx:
WebCopilot is an automation tool designed to enumerate subdomains of the target and detect bugs using different open-source tools.
The script first enumerate all the subdomains of the given target domain using assetfinder, sublister, subfinder, amass, findomain, hackertarget, riddler and crt then do active subdomain enumeration using gobuster from SecLists wordlist then filters out all the live subdomains using dnsx then it extract titles of the subdomains using httpx & scans for subdomain takeover using subjack. Then it uses gauplus & waybackurls to crawl all the endpoints of the given subdomains then it use gf patterns to filters out xss, lfi, ssrf, sqli, open redirect & rce parameters from that given subdomains, and then it scans for vulnerabilities on the sub domains using different open-source tools (like kxss, dalfox, openredirex, nuclei, etc). Then it'll print out the result of the scan and save all the output in a specified directory.
g!2m0:~ webcopilot -h
──────▄▀▄─────▄▀▄
─────▄█░░▀▀▀▀▀░░█▄
─▄▄──█░░░░░░░░░░░█──▄▄
█▄▄█─█░░▀░░┬░░▀░░█─█▄▄█
██╗░░░░░░░██╗███████╗██████╗░░█████╗░░█████╗░██████╗░██╗██╗░░░░░░█████╗░████████╗
░██║░░██╗░░██║██╔════╝██╔══██╗██╔══██╗██╔══██╗██╔══██╗██║██║░░░░░██╔══██╗╚══██╔══╝
░╚██╗████╗██╔╝█████╗░░██████╦╝██║░░╚═╝██║░░██║██████╔╝██║██║░░░░░██║░░██║░░░██║░░░
░░████╔═████║░██╔══╝░░██╔══██╗██║░░██╗██║░░██║██╔═══╝░██║██║ ░░░░██║░░██║░░░██║░░░
░░╚██╔╝░╚██╔╝░███████╗██████╦╝╚█████╔╝╚█████╔╝██║░░░░░██║███████╗╚█████╔╝░░░██║░░░
░░░╚═╝░░░╚═╝░░╚══════╝╚═════╝░░╚════╝ ░╚════╝░╚═╝░░░░░╚═╝╚══════╝░╚════╝░░░░╚═╝░░░
[●] @h4r5h1t.hrs | G!2m0
Usage:
webcopilot -d <target>
webcopilot -d <target> -s
webcopilot [-d target] [-o output destination] [-t threads] [-b blind server URL] [-x exclude domains]
Flags:
-d Add your target [Requried]
-o To save outputs in folder [Default: domain.com]
-t Number of threads [Default: 100]
-b Add your server for BXSS [Default: False]
-x Exclude out of scope domains [Default: False]
-s Run only Subdomain Enumeration [Default: False]
-h Show this help message
Example: webcopilot -d domain.com -o domain -t 333 -x exclude.txt -b testServer.xss
Use https://xsshunter.com/ or https://interact.projectdiscovery.io/ to get your serverWebCopilot requires git to install successfully. Run the following command as a root to install webcopilot
git clone https://github.com/h4r5h1t/webcopilot && cd webcopilot/ && chmod +x webcopilot install.sh && mv webcopilot /usr/bin/ && ./install.shSubFinder • Sublist3r • Findomain • gf • OpenRedireX • dnsx • sqlmap • gobuster • assetfinder • httpx • kxss • qsreplace • Nuclei • dalfox • anew • jq • aquatone • urldedupe • Amass • gauplus • waybackurls • crlfuzz
To run the tool on a target, just use the following command.
g!2m0:~ webcopilot -d bugcrowd.comThe -o command can be used to specify an output dir.
g!2m0:~ webcopilot -d bugcrowd.com -o bugcrowdThe -s command can be used for only subdomain enumerations (Active + Passive and also get title & screenshots).
g!2m0:~ webcopilot -d bugcrowd.com -o bugcrowd -s The -t command can be used to add thrads to your scan for faster result.
g!2m0:~ webcopilot -d bugcrowd.com -o bugcrowd -t 333 The -b command can be used for blind xss (OOB), you can get your server from xsshunter or interact
g!2m0:~ webcopilot -d bugcrowd.com -o bugcrowd -t 333 -b testServer.xssThe -x command can be used to exclude out of scope domains.
g!2m0:~ echo out.bugcrowd.com > excludeDomain.txt
g!2m0:~ webcopilot -d bugcrowd.com -o bugcrowd -t 333 -x excludeDomain.txt -b testServer.xssDefault options looks like this:
g!2m0:~ webcopilot -d bugcrowd.com - bugcrowd ──────▄▀▄─────▄▀▄
─────▄█░░▀▀▀▀▀░░█▄
─▄▄──█░░░░░░░░░░░█──▄▄
█▄▄█─█░░▀░░┬░░▀░░█─█▄▄█
██╗░░░░░░░██╗███████╗██████╗░░█████╗░ █████╗░██████╗░██╗██╗░░░░░░█████╗░████████╗
░██║░░██╗░░██║██╔════╝██╔══██╗██╔══██╗██╔══██╗██╔══██╗██║██║░░░░░██╔══██╗╚══██╔══╝
░╚██╗████╗██╔╝█ ███╗░░██████╦╝██║░░╚═╝██║░░██║██████╔╝██║██║░░░░░██║░░██║░░░██║░░░
░░████╔═████║░██╔══╝░░██╔══██╗██║░░██╗██║░░██║██╔═══╝░██║██║░░░░░██║░░██║░░ ██║░░░
░░╚██╔╝░╚██╔╝░███████╗██████╦╝╚█████╔╝╚█████╔╝██║░░░░░██║███████╗╚█████╔╝░░░██║░░░
░░░╚═╝░░░╚═╝░░╚══════╝╚═════╝░░╚════╝░░╚════╝░╚═╝░░░ ░╚═╝╚══════╝░╚════╝░░░░╚═╝░░░
[●] @h4r5h1t.hrs | G!2m0
[❌] Warning: Use with caution. You are responsible for your own actions.
[❌] Developers assume no liability and are not responsible for any misuse or damage cause by this tool.
Target: bugcrowd.com
Output: /home/gizmo/targets/bugcrowd
Threads: 100
Server: False
Exclude: False
Mode: Running all Enumeration
Time: 30-08-2021 15:10:00
[!] Please wait while scanning...
[●] Subdoamin Scanning is in progress: Scanning subdomains of bugcrowd.com
[●] Subdoamin Scanned - [assetfinder✔] Subdomain Found: 34
[●] Subdoamin Scanned - [sublist3r✔] Subdomain Found: 29
[●] Subdoamin Scanned - [subfinder✔] Subdomain Found: 54
[●] Subdoamin Scanned - [amass✔] Subdomain Found: 43
[●] Subdoamin Scanned - [findomain✔] Subdomain Found: 27
[●] Active Subdoamin Scanning is in progress:
[!] Please be patient. This may take a while...
[●] Active Subdoamin Scanned - [gobuster✔] Subdomain Found: 11
[●] Active Subdoamin Scanned - [amass✔] Subdomain Found: 0
[●] Subdomain Scanning: Filtering out of scope subdomains
[●] Subdomain Scanning: Filtering Alive subdomains
[●] Subdomain Scanning: Getting titles of valid subdomains
[●] Visual inspection of Subdoamins is completed. Check: /subdomains/aquatone/
[●] Scanning Completed for Subdomains of bugcrowd.com Total: 43 | Alive: 30
[●] Endpoints Scanning Completed for Subdomains of bugcrowd.com Total: 11032
[●] Vulnerabilities Scanning is in progress: Getting all vulnerabilities of bugcrowd.com
[●] Vulnerabilities Scanned - [XSS✔] Found: 0
[●] Vulnerabilities Scanned - [SQLi✔] Found: 0
[●] Vulnerabilities Scanned - [LFI✔] Found: 0
[●] Vulnerabilities Scanned - [CRLF✔] Found: 0
[●] Vulnerabilities Scanned - [SSRF✔] Found: 0
[●] Vulnerabilities Scanned - [Sensitive Data✔] Found: 0
[●] Vulnerabilities Scanned - [Open redirect✔] Found: 0
[●] Vulnerabilities Scanned - [Subdomain Takeover✔] Found: 0
[●] Vulnerabilities Scanned - [Nuclie✔] Found: 0
[●] Vulnerabilities Scanning Completed for Subdomains of bugcrowd.com Check: /vulnerabilities/
▒█▀▀█ █▀▀ █▀▀ █░░█ █░░ ▀▀█▀▀
▒█▄▄▀ █▀▀ ▀▀█ █░░█ █░░ ░░█░░
▒█░▒█ ▀▀▀ ▀▀▀ ░▀▀▀ ▀▀▀ ░░▀░░
[+] Subdomains of bugcrowd.com
[+] Subdomains Found: 0
[+] Subdomains Alive: 0
[+] Endpoints: 11032
[+] XSS: 0
[+] SQLi: 0
[+] Open Redirect: 0
[+] SSRF: 0
[+] CRLF: 0
[+] LFI: 0
[+] Sensitive Data: 0
[+] Subdomain Takeover: 0
[+] Nuclei: 0WebCopilot is inspired from Garud & Pinaak by ROX4R.
@aboul3la @tomnomnom @lc @hahwul @projectdiscovery @maurosoria @shelld3v @devanshbatham @michenriksen @defparam @projectdiscovery @bp0lr @ameenmaali @sqlmapproject @dwisiswant0 @OWASP @OJ @Findomain @danielmiessler @1ndianl33t @ROX4R
| Warning: Developers assume no liability and are not responsible for any misuse or damage cause by this tool. So, please se with caution because you are responsible for your own actions. |
AcuAutomate is an unofficial Acunetix CLI tool that simplifies automated pentesting and bug hunting across extensive targets. It's a valuable aid during large-scale pentests, enabling the easy launch or stoppage of multiple Acunetix scans simultaneously. Additionally, its versatile functionality seamlessly integrates into enumeration wrappers or one-liners, offering efficient control through its pipeline capabilities.
git clone https://github.com/danialhalo/AcuAutomate.git
cd AcuAutomate
chmod +x AcuAutomate.py
pip3 install -r requirements.txt
Before using AcuAutomate, you need to set up the configuration file config.json inside the AcuAutomate folder:
{
"url": "https://localhost",
"port": 3443,
"api_key": "API_KEY"
}The help parameter (-h) can be used for accessing more detailed help for specific actions
__ _ ___
____ ________ ______ ___ / /_(_) __ _____/ (_)
/ __ `/ ___/ / / / __ \/ _ \/ __/ / |/_/_____/ ___/ / /
/ /_/ / /__/ /_/ / / / / __/ /_/ /> </_____/ /__/ / /
\__,_/\___/\__,_/_/ /_/\___/\__/_/_/|_| \___/_/_/
-: By Danial Halo :-
usage: AcuAutomate.py [-h] {scan,stop} ...
Launch or stop a scan using Acunetix API
positional arguments:
{scan,stop} Action to perform
scan Launch a scan use scan -h
stop Stop a scan
options:
-h, --help show this help message and exit
For launching the scan you need to use the scan actions:
xubuntu:~/AcuAutomate$ ./AcuAutomate.py scan -h
usage: AcuAutomate.py scan [-h] [-p] [-d DOMAIN] [-f FILE]
[-t {full,high,weak,crawl,xss,sql}]
options:
-h, --help show this help message and exit
-p, --pipe Read from pipe
-d DOMAIN, --domain DOMAIN
Domain to scan
-f FILE, --file FILE File containing list of URLs to scan
-t {full,high,weak,crawl,xss,sql}, --type {full,high,weak,crawl,xss,sql}
High Risk Vulnerabilities Scan, Weak Password Scan, Crawl Only,
XSS Scan, SQL Injection Scan, Full Scan (by default)The domain can be provided with -d flag for single site scan:
./AcuAutomate.py scan -d https://www.google.com
For scanning multiple domains the domains need to be added into the file and then specify the file name with -f flag:
./AcuAutomate.py scan -f domains.txt
The AcuAutomate can also worked with the pipeline input with -p flag:
cat domain.txt | ./AcuAutomate.py scan -p
This is Great as it can enable the AcuAutomate to work with other tools. For example we can use the subfinder , httpx and then pipe the output to AcuAutomate for mass scanning with acunetix:
subfinder -silent -d google.com | httpx -silent | ./AcuAutomate.py scan -p
The -t flag can be used to define the scan type. For example the following scan will only detect the SQL vulnerabilities:
./AcuAutomate.py scan -d https://www.google.com -t sql
AcuAutomate only accept the domains with http:// or https://
The stop action can be used for stoping the scan either with -d flag for stoping scan by specifing the domain or with -a flage for stopping all running scans.
xubuntu:~/AcuAutomate$ ./AcuAutomate.py stop -h
__ _ ___
____ ________ ______ ___ / /_(_) __ _____/ (_)
/ __ `/ ___/ / / / __ \/ _ \/ __/ / |/_/_____/ ___/ / /
/ /_/ / /__/ /_/ / / / / __/ /_/ /> </_____/ /__/ / /
\__,_/\___/\__,_/_/ /_/\___/\__/_/_/|_| \___/_/_/
-: By Danial Halo :-
usage: AcuAutomate.py stop [-h] [-d DOMAIN] [-a]
options:
-h, --help show this help message and exit
-d DOMAIN, --domain DOMAIN
Domain of the scan to stop
-a, --all Stop all Running Scans
Please submit any bugs, issues, questions, or feature requests under "Issues" or send them to me on Twitter. @DanialHalo
Microsoft ICS Forensics Tools is an open source forensic framework for analyzing Industrial PLC metadata and project files.
it enables investigators to identify suspicious artifacts on ICS environment for detection of compromised devices during incident response or manual check.
open source framework, which allows investigators to verify the actions of the tool or customize it to specific needs.
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
git clone https://github.com/microsoft/ics-forensics-tools.git
Install python requirements
pip install -r requirements.txt
| Args | Description | Required / Optional |
|---|---|---|
-h, --help
| show this help message and exit | Optional |
-s, --save-config
| Save config file for easy future usage | Optional |
-c, --config
| Config file path, default is config.json | Optional |
-o, --output-dir
| Directory in which to output any generated files, default is output | Optional |
-v, --verbose
| Log output to a file as well as the console | Optional |
-p, --multiprocess
| Run in multiprocess mode by number of plugins/analyzers | Optional |
| Args | Description | Required / Optional |
|---|---|---|
-h, --help
| show this help message and exit | Optional |
--ip | Addresses file path, CIDR or IP addresses csv (ip column required). add more columns for additional info about each ip (username, pass, etc...) | Required |
--port | Port number | Optional |
--transport | tcp/udp | Optional |
--analyzer | Analyzer name to run | Optional |
python driver.py -s -v PluginName --ip ips.csv
python driver.py -s -v PluginName --analyzer AnalyzerName
python driver.py -s -v -c config.json --multiprocess
from forensic.client.forensic_client import ForensicClient
from forensic.interfaces.plugin import PluginConfig
forensic = ForensicClient()
plugin = PluginConfig.from_json({
"name": "PluginName",
"port": 123,
"transport": "tcp",
"addresses": [{"ip": "192.168.1.0/24"}, {"ip": "10.10.10.10"}],
"parameters": {
},
"analyzers": []
})
forensic.scan([plugin])When developing locally make sure to mark src folder as "Sources root"
from pathlib import Path
from forensic.interfaces.plugin import PluginInterface, PluginConfig, PluginCLI
from forensic.common.constants.constants import Transport
class GeneralCLI(PluginCLI):
def __init__(self, folder_name):
super().__init__(folder_name)
self.name = "General"
self.description = "General Plugin Description"
self.port = 123
self.transport = Transport.TCP
def flags(self, parser):
self.base_flags(parser, self.port, self.transport)
parser.add_argument('--general', help='General additional argument', metavar="")
class General(PluginInterface):
def __init__(self, config: PluginConfig, output_dir: Path, verbose: bool):
super().__init__(config, output_dir, verbose)
def connect(self, address):
self.logger.info(f"{self.config.name} connect")
def export(self, extracted):
self.logger.info(f"{self.config.name} export")
__init__.py file under the plugins folderfrom pathlib import Path
from forensic.interfaces.analyzer import AnalyzerInterface, AnalyzerConfig
class General(AnalyzerInterface):
def __init__(self, config: AnalyzerConfig, output_dir: Path, verbose: bool):
super().__init__(config, output_dir, verbose)
self.plugin_name = 'General'
self.create_output_dir(self.plugin_name)
def analyze(self):
pass__init__.py file under the analyzers folderMicrosoft Defender for IoT is an agentless network-layer security solution that allows organizations to continuously monitor and discover assets, detect threats, and manage vulnerabilities in their IoT/OT and Industrial Control Systems (ICS) devices, on-premises and in Azure-connected environments.
Section 52 under MSRC blog
ICS Lecture given about the tool
Section 52 - Investigating Malicious Ladder Logic | Microsoft Defender for IoT Webinar - YouTube
This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.
When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.
This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.
This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow Microsoft's Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party's policies.
A comprehensive tool that provides an insightful analysis of Microsoft's monthly security updates.
IF you are interested in seing all this data in a live website, visit:
PatchaPalooza uses the power of Microsoft's MSRC CVRF API to fetch, store, and analyze security update data. Designed for cybersecurity professionals, it offers a streamlined experience for those who require a quick yet detailed overview of vulnerabilities, their exploitation status, and more. This tool operates entirely offline once the data has been fetched, ensuring that your analyses can continue even without an internet connection.
Run PatchaPalooza without arguments to see an analysis of the current month's data:
python PatchaPalooza.pyFor a specific month's analysis:
python PatchaPalooza.py --month YYYY-MMMTo display a detailed view of a specific CVE:
python PatchaPalooza.py --detail CVE-IDTo update and store the latest data:
python PatchaPalooza.py --updateFor an overall statistical overview:
python PatchaPalooza.py --statsThis tool is built upon the Microsoft's MSRC CVRF API and is inspired by the work of @KevTheHermit.
Alexander Hagenah
This tool is meant for educational and professional purposes only. No license, so do with it whatever you like.
OSDP attack tool (and the Elvish word for friend)
OSDP supports, but doesn't strictly require, encryption. So your connection might not even be encrypted at all. Attack #1 is just to passively listen and see if you can read the card numbers on the wire.
Just because the controller and reader support encryption doesn't mean they're configured to require it be used. An attacker can modify the reader's capability reply message (osdp_PDCAP) to advertise that it doesn't support encryption. When this happens, some controllers will barrel ahead without encryption.
OSDP has a quasi-official “install mode” that applies to both readers and controllers. As the name suggests, it’s supposed to be used when first setting up a reader. What it does is essentially allow readers to ask the controller for what the base encryption key (the SCBK) is. If the controller is configured to be persistently in install-mode, then an attacker can show up on the wire and request the SCBK.
OSDP sample code often comes with hardcoded encryption keys. Clearly these are meant to be samples, where the user is supposed to generate keys in a secure way on their own. But this is not explained or made simple for the user, however. And anyone who’s been in security long enough knows that whatever’s the default is likely to be there in production.
So as an attack vector, when the link between reader and controller is encrypted, it’s worth a shot to enumerate some common weak keys. Now these are 128-bit AES keys, so we’re not going to be able to enumerate them all. Or even a meaningful portion of them. But what we can do is hit some common patterns that you see when someone hardcodes a key:
OSDP has no in-band mechansim for key exchange. What this means is that an attacker can:
You'll find proof-of-concept code for each of these attacks in attack_osdp.py. Checkout the --help command for more details on usage. This is a Python script, meant to be run from a laptop with USB<-->RS485 adapters like one of these. So you'll probably want to pick some of those up. Doesn't have to be that model, though.
If you have a controller you want to test, then great. Use that. If you don't, then we have an intentionally-vulnerable OSDP controller that you can use here: vulnserver.py.
Some of the attacks in attack_osdp.py will expect to be as a full MitM between a functioning reader and controller. To test these, you might need three USB<-->RS485 adapters, hooked together with a breadboard.
These issues are not, in isolation, exploitable but nonetheless represent a weakening of the protocol, implementation, or overall system.
Callisto is an intelligent automated binary vulnerability analysis tool. Its purpose is to autonomously decompile a provided binary and iterate through the psuedo code output looking for potential security vulnerabilities in that pseudo c code. Ghidra's headless decompiler is what drives the binary decompilation and analysis portion. The pseudo code analysis is initially performed by the Semgrep SAST tool and then transferred to GPT-3.5-Turbo for validation of Semgrep's findings, as well as potential identification of additional vulnerabilities.
This tool's intended purpose is to assist with binary analysis and zero-day vulnerability discovery. The output aims to help the researcher identify potential areas of interest or vulnerable components in the binary, which can be followed up with dynamic testing for validation and exploitation. It certainly won't catch everything, but the double validation with Semgrep to GPT-3.5 aims to reduce false positives and allow a deeper analysis of the program.
For those looking to just leverage the tool as a quick headless decompiler, the output.c file created will contain all the extracted pseudo code from the binary. This can be plugged into your own SAST tools or manually analyzed.
I owe Marco Ivaldi @0xdea a huge thanks for his publicly released custom Semgrep C rules as well as his idea to automate vulnerability discovery using semgrep and pseudo code output from decompilers. You can read more about his research here: Automating binary vulnerability discovery with Ghidra and Semgrep
Requirements:
pip install semgrep
pip install -r requirements.txt
config.txt fileTo Run: python callisto.py -b <path_to_binary> -ai -o <path_to_output_file>
-ai => enable OpenAI GPT-3.5-Turbo Analysis. Will require placing a valid OpenAI API key in the config.txt file-o => define an output file, if you want to save the output-ai and -o are optional parameters-all will run all functions through OpenAI Analysis, regardless of any Semgrep findings. This flag requires the prerequisite -ai flagpython callisto.py -b vulnProgram.exe -ai -o results.txt
python callisto.py -b vulnProgram.exe -ai -all -o results.txt
Program Output Example:
surf allows you to filter a list of hosts, returning a list of viable SSRF candidates. It does this by sending a HTTP request from your machine to each host, collecting all the hosts that did not respond, and then filtering them into a list of externally facing and internally facing hosts.
You can then attempt these hosts wherever an SSRF vulnerability may be present. Due to most SSRF filters only focusing on internal or restricted IP ranges, you'll be pleasantly surprised when you get SSRF on an external IP that is not accessible via HTTP(s) from your machine.
Often you will find that large companies with cloud environments will have external IPs for internal web apps. Traditional SSRF filters will not capture this unless these hosts are specifically added to a blacklist (which they usually never are). This is why this technique can be so powerful.
This tool requires go 1.19 or above as we rely on httpx to do the HTTP probing.
It can be installed with the following command:
go install github.com/assetnote/surf/cmd/surf@latestConsider that you have subdomains for bigcorp.com inside a file named bigcorp.txt, and you want to find all the SSRF candidates for these subdomains. Here are some examples:
# find all ssrf candidates (including external IP addresses via HTTP probing)
surf -l bigcorp.txt
# find all ssrf candidates (including external IP addresses via HTTP probing) with timeout and concurrency settings
surf -l bigcorp.txt -t 10 -c 200
# find all ssrf candidates (including external IP addresses via HTTP probing), and just print all hosts
surf -l bigcorp.txt -d
# find all hosts that point to an internal/private IP address (no HTTP probing)
surf -l bigcorp.txt -xThe full list of settings can be found below:
❯ surf -h
███████╗██╗ ██╗██████╗ ███████╗
██╔════╝██║ ██║██╔══██╗██╔════╝
███████╗██║ ██║██████╔╝█████╗
╚════██║██║ ██║██╔══██╗██╔══╝
███████║╚██████╔ ██║ ██║██║
╚══════╝ ╚═════╝ ╚═╝ ╚═╝╚═╝
by shubs @ assetnote
Usage: surf [--hosts FILE] [--concurrency CONCURRENCY] [--timeout SECONDS] [--retries RETRIES] [--disablehttpx] [--disableanalysis]
Options:
--hosts FILE, -l FILE
List of assets (hosts or subdomains)
--concurrency CONCURRENCY, -c CONCURRENCY
Threads (passed down to httpx) - default 100 [default: 100]
--timeout SECONDS, -t SECONDS
Timeout in seconds (passed down to httpx) - default 3 [default: 3]
--retries RETRIES, -r RETRIES
Retries on failure (passed down to httpx) - default 2 [default: 2]
--disablehttpx, -x Disable httpx and only output list of hosts that resolve to an internal IP address - default false [default: false]
--disableanalysis, -d
Disable analysis and only output list of hosts - default false [default: false]
--help, -h display this help and exit
When running surf, it will print out the SSRF candidates to stdout, but it will also save two files inside the folder it is ran from:
external-{timestamp}.txt - Externally resolving, but unable to send HTTP requests to from your machineinternal-{timestamp}.txt - Internally resolving, and obviously unable to send HTTP requests from your machineThese two files will contain the list of hosts that are ideal SSRF candidates to try on your target. The external target list has higher chances of being viable than the internal list.
Under the hood, this tool leverages httpx to do the HTTP probing. It captures errors returned from httpx, and then performs some basic analysis to determine the most viable candidates for SSRF.
This tool was created as a result of a live hacking event for HackerOne (H1-4420 2023).
NucleiFuzzer is an automation tool that combines ParamSpider and Nuclei to enhance web application security testing. It uses ParamSpider to identify potential entry points and Nuclei's templates to scan for vulnerabilities. NucleiFuzzer streamlines the process, making it easier for security professionals and web developers to detect and address security risks efficiently. Download NucleiFuzzer to protect your web applications from vulnerabilities and attacks.
Note: Nuclei + Paramspider = NucleiFuzzer
ParamSpider git clone https://github.com/0xKayala/ParamSpider.git
Nuclei git clone https://github.com/projectdiscovery/nuclei.git
Fuzzing Templates git clone https://github.com/projectdiscovery/fuzzing-templates.git
nucleifuzzer -hThis will display help for the tool. Here are the options it supports.
NucleiFuzzer is a Powerful Automation tool for detecting XSS, SQLi, SSRF, Open-Redirect, etc. vulnerabilities in Web Applications
Usage: /usr/local/bin/nucleifuzzer [options]
Options:
-h, --help Display help information
-d, --domain <domain> Domain to scan for XSS, SQLi, SSRF, Open-Redirect..etc vulnerabilitiesMade by Satya Prakash | 0xKayala \
A Security Researcher and Bug Hunter \
While DLL sideloading can be used for legitimate purposes, such as loading necessary libraries for a program to function, it can also be used for malicious purposes. Attackers can use DLL sideloading to execute arbitrary code on a target system, often by exploiting vulnerabilities in legitimate applications that are used to load DLLs.
To automate the DLL sideloading process and make it more effective, Chimera was created a tool that include evasion methodologies to bypass EDR/AV products. These tool can automatically encrypt a shellcode via XOR with a random key and create template Images that can be imported into Visual Studio to create a malicious DLL.
Also Dynamic Syscalls from SysWhispers2 is used and a modified assembly version to evade the pattern that the EDR search for, Random nop sleds are added and also registers are moved. Furthermore Early Bird Injection is also used to inject the shellcode in another process which the user can specify with Sandbox Evasion mechanisms like HardDisk check & if the process is being debugged. Finally Timing attack is placed in the loader which using waitable timers to delay the execution of the shellcode.
This tool has been tested and shown to be effective at bypassing EDR/AV products and executing arbitrary code on a target system.
Chimera is written in python3 and there is no need to install any extra dependencies.
Chimera currently supports two DLL options either Microsoft teams or Microsoft OneDrive.
Someone can create userenv.dll which is a missing DLL from Microsoft Teams and insert it to the specific folder to
%USERPROFILE%/Appdata/local/Microsoft/Teams/current
For Microsoft OneDrive the script uses version DLL which is common because its missing from the binary example onedriveupdater.exe
python3 ./chimera.py met.bin chimera_automation notepad.exe teams
python3 ./chimera.py met.bin chimera_automation notepad.exe onedrive
Once the compilation process is complete, a DLL will be generated, which should include either "version.dll" for OneDrive or "userenv.dll" for Microsoft Teams. Next, it is necessary to rename the original DLLs.
For instance, the original "userenv.dll" should be renamed as "tmpB0F7.dll," while the original "version.dll" should be renamed as "tmp44BC.dll." Additionally, you have the option to modify the name of the proxy DLL as desired by altering the source code of the DLL exports instead of using the default script names.
Step 1: Creating a New Visual Studio Project with DLL Template
Step 2: Importing Images into the Visual Studio Project
Step 3: Build Customization
Step 4: Enable MASM
Step 5:
Step 1: Change optimization
Step 2: Remove Debug Information's
To the maximum extent permitted by applicable law, myself(George Sotiriadis) and/or affiliates who have submitted content to my repo, shall not be liable for any indirect, incidental, special, consequential or punitive damages, or any loss of profits or revenue, whether incurred directly or indirectly, or any loss of data, use, goodwill, or other intangible losses, resulting from (i) your access to this resource and/or inability to access this resource; (ii) any conduct or content of any third party referenced by this resource, including without limitation, any defamatory, offensive or illegal conduct or other users or third parties; (iii) any content obtained from this resource
https://evasions.checkpoint.com/
https://github.com/Flangvik/SharpDllProxy
https://github.com/jthuraisamy/SysWhispers2
https://github.com/Mr-Un1k0d3r
Upload_Bypass is a powerful tool designed to assist Pentesters and Bug Hunters in testing file upload mechanisms. It leverages various bug bounty techniques to simplify the process of identifying and exploiting vulnerabilities, ensuring thorough assessments of web applications.
Please note that the use of Upload_Bypass and any actions taken with it are solely at your own risk. The tool is provided for educational and testing purposes only. The developer of Upload_Bypass is not responsible for any misuse, damage, or illegal activities caused by its usage.
While Upload_Bypass aims to assist Pentesters and Bug Hunters in testing file upload mechanisms, it is essential to obtain proper authorization and adhere to applicable laws and regulations before performing any security assessments. Always ensure that you have the necessary permissions from the relevant stakeholders before conducting any testing activities.
The results and findings obtained from using Upload_Bypass should be communicated responsibly and in accordance with established disclosure processes. It is crucial to respect the privacy and integrity of the tested systems and refrain from causing harm or disruption.
By using Upload_Bypass, you acknowledge that the developer cannot be held liable for any consequences resulting from its use. Use the tool responsibly and ethically to promote the security and integrity of web applications.
Download the latest version from Releases page.
pip install -r requirements.txt
The tool will not function properly if the file upload mechanism includes CAPTCHA implementation.
Perhaps in the future the tool will include an OCR.
The Tool is compatible exclusively with output file requests generated by Burp Suite.
Before saving the Burp file, replace the file content with the string *content* and filename.ext with the string *filename* and Content-Type header with *mimetype*(only if the tool is not able to recognize it automatically).
How a request should look before the changes:
How it should look after the changes:
If the tool fails to recognize the mime type automatically, you can add *mimetype* in the parameter's value of the Content-Type header.
Options: -h, --help
show this help message and exit
-b BURP_FILE, --burp-file BURP_FILE
Required - Read from a Burp Suite file
Usage: -b / --burp-file ~/Desktop/output
-s SUCCESS_MESSAGE, --success SUCCESS_MESSAGE
Required if -f is not set - Provide the success message when a file is uploaded
Usage: -s /--success 'File uploaded successfully.'
-f FAILURE_MESSAGE, --failure FAILURE_MESSAGE
Required if -s is not set - Provide a failure message when a file is uploaded
Usage: -f /--failure 'File is not allowed!'
-e FILE_EXTENSION, --extension FILE_EXTENSION
Required - Provide server backend extension
Usage: -e / --extension php (Supported extensions: php,asp,jsp,perl,coldfusion)
-a ALLOWED_EXTENSIONS, --allowed ALLOWED_EXTENSIONS
Required - Provide allowed extensions to be uploaded
Usage: -a /--allowed jpeg, png, zip, etc'
-l WEBSHELL_LOCATION, --location WEBSHELL_LOCATION
Provide a remote path where the WebShell will be uploaded (won't work if the file will be uploaded with a UUID).
Usage: -l / --location /uploads/
-rl NUMBER, --rate-limit NUMBER
Set rate-limiting with milliseconds between each request.
Usage: -r / --rate-limit 700
-p PROXY_NUM, --proxy PROXY_NUM
Channel the HTTP requests via proxy client (i.e Burp Suite).
Usage: -p / --proxy http://127.0.0.1:8080
-S, --ssl
If set, the tool will not validate TLS/SSL certificate.
Usage: -S / --ssl
-c, --continue
If set, the brute force will continue even if one of the methods gets a hit!
Usage: -C /--continue
-E, --eicar
If set, an Eicar file(Anti Malware Testfile) will be uploaded only. WebShells will not be uploaded (Suitable for real environments).
Usage: -E / --eicar
-v, --verbose
If set, details about the test will be printed on the screen
Usage: -v / --verbose
-r, --response
If set, HTTP response will be printed on the screen
Usage: -r / --response
--version
Print the current version of the tool.
--update
Checks for new updates. If there is a new update, it will be downloaded and updated automatically.
python upload_bypass.py -b ~/Desktop/burp_output -s 'file upload successfully!' -e php -a jpeg --response -v --eicar --continue
python upload_bypass.py -b ~/Desktop/burp_output -s 'file upload successfully!' -e asp -a zip -v
python upload_bypass.py -b ~/Desktop/burp_output -s 'file upload successfully!' -e jsp -a png -v --proxy http://127.0.0.1:8080
PrivKit is a simple beacon object file that detects privilege escalation vulnerabilities caused by misconfigurations on Windows OS.
Checks for Unquoted Service Paths
Checks for Autologon Registry Keys
Checks for Always Install Elevated Registry Keys
Checks for Modifiable Autoruns
Checks for Hijackable Paths
Enumerates Credentials From Credential Manager
Looks for current Token Privileges
[03/20 00:51:06] beacon> privcheck
[03/20 00:51:06] [*] Priv Esc Check Bof by @merterpreter
[03/20 00:51:06] [*] Checking For Unquoted Service Paths..
[03/20 00:51:06] [*] Checking For Autologon Registry Keys..
[03/20 00:51:06] [*] Checking For Always Install Elevated Registry Keys..
[03/20 00:51:06] [*] Checking For Modifiable Autoruns..
[03/20 00:51:06] [*] Checking For Hijackable Paths..
[03/20 00:51:06] [*] Enumerating Credentials From Credential Manager..
[03/20 00:51:06] [*] Checking For Token Privileges..
[03/20 00:51:06] [+] host called home, sent: 10485 bytes
[03/20 00:51:06] [+] received output:
Unquoted Service Path Check Result: Vulnerable service path found: c:\program files (x86)\grasssoft\macro expert\MacroService.exe
Simply load the cna file and type "privcheck"
If you want to compile by yourself you can use:make all
or x86_64-w64-mingw32-gcc -c cfile.c -o ofile.o
If you want to look for just one misconf you can use object file with "inline-execute" for example inline-execute /path/tokenprivileges.o
Mr.Un1K0d3r - Offensive Coding Portal
https://mr.un1k0d3r.world/portal/
Outflank - C2-Tool-Collection
https://github.com/outflanknl/C2-Tool-Collection
dtmsecurity - Beacon Object File (BOF) Creation Helper
https://github.com/dtmsecurity/bof_helper
Microsoft :)
https://learn.microsoft.com/en-us/windows/win32/api/
HsTechDocs by HelpSystems(Fortra)
https://hstechdocs.helpsystems.com/manuals/cobaltstrike/current/userguide/content/topics/beacon-object-files_how-to-develop.htm
Instagram: TMRSWRR
LFI-FINDER is an open-source tool available on GitHub that focuses on detecting Local File Inclusion (LFI) vulnerabilities. Local File Inclusion is a common security vulnerability that allows an attacker to include files from a web server into the output of a web application. This tool automates the process of identifying LFI vulnerabilities by analyzing URLs and searching for specific patterns indicative of LFI. It can be a useful addition to a security professional's toolkit for detecting and addressing LFI vulnerabilities in web applications.
This tool works with geckodriver, search url for LFI Vuln and when get an root text on the screen, it notifies you of the successful payload.
git clone https://github.com/capture0x/LFI-FINDER/
cd LFI-FINDER
bash setup.sh
pip3 install -r requirements.txt
chmod -R 755 lfi.pypython3 lfi.py
THIS IS FOR LATEST GOOGLE CHROME VERSION
For bug reports or enhancements, please open an issue here.
Copyright 2023
Cake Fuzzer is a project that is meant to help automatically and continuously discover vulnerabilities in web applications created based on specific frameworks with very limited false positives. Currently it is implemented to support the Cake PHP framework.
If you would like to learn more about the research process check out this article series: CakePHP Application Cybersecurity Research
Typical approaches to discovering vulnerabilities using automated tools in web applications are:
Both methods have disadvantages. SAST results in a high percentage of false positives – findings that are either not vulnerabilities or not exploitable vulnerabilities. DAST results in fewer false positives but discovers fewer vulnerabilities due to the limited information. It also requires some knowledge about the application and a security background of a person who runs a scan. This often comes with a custom scan configuration per application to work properly.
The Cake Fuzzer project is meant to combine the advantages of both approaches and eliminate the above-mentioned disadvantages. This approach is called Interactive Application Security Testing (IAST).
The goals of the project are:
Note: Some classes of vulnerabilities are not the target of the Cake Fuzzer, therefore Cake Fuzzer will not be able to detect them. Examples of those classes are business logic vulnerabilities and access control issues.
Drawio: Cake Fuzzer Architecture
Cake Fuzzer consists of 3 main (fairly independent) servers that in total allow for dynamic vulnerability testing of CakePHP allications.
Other components include:
Cake Fuzzer is based on the concept of Interactive Application Security Testing (IAST). It contains a predefined set of attacks that are randomly modified before the execution. Cake Fuzzer has the knowledge of the application internals thanks to the Cake PHP framework therefore the attacks will be launched on all possible entry points of the application.
During the attack, the Cake Fuzzer monitors various aspects of the application and the underlying system such as:
These sources of information allow Cake Fuzzer to identify more vulnerabilities and report them with higher certainty.
The following section describes steps to setup a Cake Fuzzer development environment where the target is outdated MISP v2.4.146 that is vulnerable to CVE-2021-41326.
Run the following commands on your host operating system to download an outdated MISP VM:
cd ~/Downloads # Or wherever you want to store the MISP VM
wget https://vm.misp-project.org/MISP_v2.4.146@0c25b72/MISP_v2.4.146@0c25b72-VMware.zip -O MISP.zip
unzip MISP.zip
rm MISP.zip
mv VMware/ MISP-2.4.146Conduct the following actions in VMWare GUI to prepare sharing Cake Fuzzer files between your host OS and MISP:
Run the following commands on your host OS (replace MISP_IP_ADDRESS with previously noted IP address):
ssh-copy-id misp@MISP_IP_ADDRESS
ssh misp@MISP_IP_ADDRESSOnce you SSH into the MISP run the following commands (in MISP terminal) to finish setup of sharing Cake Fuzzer files between host OS and MISP:
sudo apt update
sudo apt-get -y install open-vm-tools open-vm-tools-desktop
sudo apt-get -y install build-essential module-assistant linux-headers-virtual linux-image-virtual && sudo dpkg-reconfigure open-vm-tools
sudo mkdir /cake_fuzzer # Note: This path is fixed as it's hardcoded in the instrumentation (one of the patches)
sudo vmhgfs-fuse .host:/cake_fuzzer /cake_fuzzer -o allow_other -o uid=1000
ls -l /cake_fuzzer # If everything went fine you should see content of the Cake Fuzzer directory from your host OS. Any changes on your host OS will be reflected inside the VM and vice-versa.Prepare MISP for simple testing (in MISP terminal):
CAKE=/var/www/MISP/app/Console/cake
SUDO='sudo -H -u www-data'
$CAKE userInit -q
$SUDO $CAKE Admin setSetting "Security.password_policy_length" 1
$SUDO $CAKE Admin setSetting "Security.password_policy_complexity" '/.*/'
$SUDO $CAKE Password admin@admin.test admin --override_password_changeFinally instal Cake Fuzzer dependencies and prepare the venv (in MISP terminal):
source /cake_fuzzer/precheck.shCake Fuzzer scans for vulnerabilities that inside of /cake_fuzzer/strategies folder.
To add a new attack we need to add a new new-attack.json file to strategies folder. Each vulnerability contains 2 major fileds:Scenarios and Scanners. Scenarios where attack payloads base forms stored. Scanners in the other hand detecting regex or pharases for response, stout, sterr, logs, and results.
Scenarios
To create a payload first you need to have the understanding of the vulnerability and how to detect it with as few payloads as possible.
While constructing the scenario you should think of as most generic payload as possible. However, the more generic payload, the more chances are that it will produce false-positives.
It is preferable to us a canary value such as__cakefuzzer__new-attack_§CAKEFUZZER_PAYLOAD_GUID§__ in your scenarios. Canary value contains a fixed string (for example: __cakefuzzer__new-attack_) and a dynamic identifier that will be changed dynamically by the fuzzer (GUID part §CAKEFUZZER_PAYLOAD_GUID§). First canary part is used to ensure that payload is detected by Scanners. Second canary part, the GUID is translated to pseudo-random value on every execution of your payload. So whenever your payload will be injected into the a parameter used by the application, the canary will be changed to something like this: __cakefuzzer__new-attack_8383938__, where the 8383938 is unique across all other attacks.
Scanners
To create a scanner, first you need to understand how may the application behave when the vulnerability is triggered. There are few scanner types that you can use such as response, sterr, logs, files, and processes. Each scanner serves a different purpose.
For example when you building a scanner for an XSS, you will look for the indication of the vulnerability in the HTML response of the application. You can use ResultOutputScanner scanner to look for canary value and payload. In other hand SQL Injection vulnerabilities could be detected via error logs. For that purpose you can use LogFilesContentsScanner and ResultErrorsScanner.
Scanner regular expressions is generating an efficent regex. Avoid using regex that match all cases .* or .+. They are very time consuming and drasticly increase the time required to finish the entire scan.As mentioned before efficiency is important part of the vulnerabilities. Both Scenarios and Scanners should include as few elements as possible. This is because Cake Fuzzer executes every single scenario in all possible detected paths multiple times. On the other hand, all responses, new log entries, etc. are constantly checked by the Scanners. There should be a lot of parameters, paths, and end-points detected and therefore using more payload or Scanner affects the efficiency quite a lot.
If do not want to scan a specific vulnerability class, remove specified json file from the strategies folder, clean the database and run the fuzzer again.
For example if you do not want to scan your applicaiton for SQL Injection vulnerabilities, do the following steps:
First of all remove already prepared attack scenarios. To achive this delete all files inside of the /cake_fuzzer/databases folder:
rm /cake_fuzzer/databases/*
After that remove the sqlinj.json file from the /cake_fuzzer/strategies
rm /cake_fuzzer/strategies/sqlinj.json
Finally re-run the fuzzer and all cake_fuzzer running proccess without any SQL Injection attack executed.
git clone https://github.com/Zigrin-Security/CakeFuzzer /cake_fuzzer
Warning Cake Fuzzer won't work properly if it's under different path than /cake_fuzzer. Keep in mind that it has to be placed under the root directory of the file system, next/root,/tmp, and so on.
cd /cake_fuzzerEnter virtual environment if you are not already in:
source /cake_fuzzer/precheck.shOR
source venv/bin/activatecp config/config.example.ini config/config.iniConfigure config/config.ini:
WEBROOT_DIR="/var/www/html" # Path to the tested applications `webroot` directory
CONCURRENT_QUEUES=5 # [Optional] Number of attacks executed concurretnly at once
ONLY_PATHS_WITH_PREFIX="/" # [Optional] Fuzzer will generates only attacks for attacks starting with this prefix
EXCLUDE_PATHS="" # [Optional] Fuzzer will exlude from scanning all paths that match this regular expression. If it's empty, all paths will be processed
PAYLOAD_GUID_PHRASE="§CAKEFUZZER_PAYLOAD_GUID§" # [Optional] Internal keyword that is substituted right before attack with unique payload id
INSTRUMENTATION_INI="config/instrumentation_cake4.ini" # [Optional] Path to custom instrumentations of the application.
Warning During the Cake Fuzzer scan, multiple functionalities of your application will be invoked in uncontrolled manner multiple times. This may result issuing connections to external services your application is connected to, and pulling or pushing data from/to it. It is highly recommended to run Cake Fuzzer in isolated controlled environment without access to sensitive external services.
Note Cake Fuzzer bypass blackholing, CSRF protections, and authorization. It sends all attacks with privileges of a first user in the database. It is recommended that this user has the highest permissions.
The application consists of several components.
Warning All cake_fuzzer commands have to be executed as root.
Before starting the fuzzer make sure your target application is fully instrumented:
python cake_fuzzer.py instrument checkIf there are some unapplied changes apply them with:
python cake_fuzzer.py instrument applyTo run cake fuzzer do the following (It's recommended to use at least 3 separate terminal):
# First Terminal
python cake_fuzzer.py run fuzzer # Generates attacks, adds them to the QUEUE and registers new SCANNERS (then exits)
python cake_fuzzer.py run periodic_monitors # Responsible for monitoring (use CTRL+C to stop & exit at the end of the scan)
# Second terminal
python cake_fuzzer.py run iteration_monitors # Responsible for monitoring (use CTRL+C to stop & exit at the end of the scan)
# Third terminal
python cake_fuzzer.py run attack_queue # Starts the ATTACK QUEUE (use CTRL+C to stop & exit at the end of the scan)
# Once all attacks are executed
python cake_fuzzer.py run registry # Generates `results.json` based on found vulnerabilitiesNote: There is currently a bug that can change the owner of logs (or any other dynamically changed filies of the target web app). This may cause errors when normally using the web application or even false-negatives on future Cake Fuzzer executions. For MISP we recommend running the following after every execution of the fuzzer:
sudo chown -R www-data:www-data /var/www/MISP/app/tmp/logs/Once your scan finishes revert the instrumentation:
python cake_fuzzer.py instrument revertTo run cake fuzzer again, do the following:
Delete Applications Logs (as an example to this, MISP logs stored /var/www/MISP/app/tmp/logs)
rm /var/www/MISP/app/tmp/logs/*
Delete All Files Inside of /cake_fuzzer/databases folder
rm /cake_fuzzer/databases/*
Delete cake_fuzzer/results.jsonfile (Firstly do not forget to save or examine previous scan resulst)
rm /cake_fuzzer/results.json
Finally follow previous running proccess again with 3 terminals
Attack queue marks executed attacks in the database as 'executed' so to run whole suite again you need to remove the database and add attacks again.
Make sure to kill monitors and attack queues before removing the database.
rm database.db*
python cake_fuzzer.py run fuzzer
python cake_fuzzer.py run attack_queue
This is likely due to the fact that the previous log files were overwritten by root. Cake Fuzzer operates as root so new log files will be created with the root as the owner. Remove them:
chmod -R a+w /var/www/MISP/app/tmp/logs/*
If you use VM with sharing cake fuzzer with your host machine, make sure that the host directory is properly attached to the guest VM:
sudo vmhgfs-fuse .host:/cake_fuzzer /cake_fuzzer -o allow_other -o uid=1000
Cake Fuzzer has to be located under the root directory of the machine and the base directory name should be cake_fuzzer specificaly.
mv CakeFuzzer/ /cake_fuzzerinstrument apply
Instrumentation proccess is a part of Cake Fuzzer execution flow. When you run instrument apply followed by instrument check, both of these commands should result in the same number of changes.
If you get any "patch" error you could apply patches manually and delete problematic patch file. Patches are located under the /cake_fuzzer/cakefuzzer/instrumentation/pathces directory.
While installing or running if you have python dependency error, manuallay install dependencies after switching to virtual environment.
First switch to the virtual environment
source venv/bin/activateAfter that you can install dependecies with pip3.
pip3 install -r requriments.txtThis project was inspired by:
This project was commissioned by: 
jsFinder is a command-line tool written in Go that scans web pages to find JavaScript files linked in the HTML source code. It searches for any attribute that can contain a JavaScript file (e.g., src, href, data-main, etc.) and extracts the URLs of the files to a text file. The tool is designed to be simple to use, and it supports reading URLs from a file or from standard input.
jsFinder is useful for web developers and security professionals who want to find and analyze the JavaScript files used by a web application. By analyzing the JavaScript files, it's possible to understand the functionality of the application and detect any security vulnerabilities or sensitive information leakage.
jsfinder requires Go 1.20 to install successfully.Run the following command to get the repo :
go install -v github.com/kacakb/jsfinder@latestTo see which flags you can use with the tool, use the -h flag.
jsfinder -h | Flag | Description |
|---|---|
| -l | Specifies the filename to read URLs from. |
| -c | Specifies the maximum number of concurrent requests to be made. The default value is 20. |
| -s | Runs the program in silent mode. If this flag is not set, the program runs in verbose mode. |
| -o | Specifies the filename to write found URLs to. The default filename is output.txt. |
| -read | Reads URLs from stdin instead of a file specified by the -l flag. |
If you want to read from stdin and run the program in silent mode, use this command:
cat list.txt| jsfinder -read -s -o js.txt
If you want to read from a file, you should specify it with the -l flag and use this command:
jsfinder -l list.txt -s -o js.txtYou can also specify the concurrency with the -c flag.The default value is 20. If you want to read from a file, you should specify it with the -l flag and use this command:
jsfinder -l list.txt -c 50 -s -o js.txtIf you have any questions, feedback or collaboration suggestions related to this project, please feel free to contact me via:
e-mail
All in one tools for LFI VULN FINDER -LFI DORK FINDER
Instagram: TMRSWRR
LFI Space is a robust and efficient tool designed to detect Local File Inclusion (LFI) vulnerabilities in web applications. This tool simplifies the process of identifying potential security flaws by leveraging two distinct scanning methods: Google Dork Search and Targeted URL Scan. With its comprehensive approach, LFI Space assists security professionals, penetration testers, and ethical hackers in assessing the security posture of web applications.
The Google Dork Search functionality within LFI Space harnesses the power of the Google search engine to identify web pages that may be susceptible to LFI attacks. By employing carefully crafted Google dorks, the tool retrieves search results that are likely to contain vulnerable pages. These dorks are specific queries designed to target common LFI vulnerability patterns in web applications. LFI Space then analyzes the responses from these pages, meticulously examining the content to identify any signs of LFI vulnerabilities. This approach allows for a broad and automated search, rapidly surfacing potential targets for further investigation.
Additionally, LFI Space provides a Targeted URL Scan feature, enabling users to manually input a list of specific URLs for scanning. This functionality allows for a more focused approach, enabling security professionals to assess particular web applications or pages of interest. By scanning each URL individually, LFI Space thoroughly inspects the target web pages for any signs of LFI vulnerabilities. This targeted approach provides flexibility and precision in identifying potential security weaknesses.
It is important to note that LFI Space is intended for responsible and authorized use, such as security testing, vulnerability assessments, or penetration testing, with proper consent and legal permissions. It is crucial to adhere to ethical guidelines and respect the privacy and security of targeted systems.
In conclusion, LFI Space is a powerful tool that combines Google Dork Search and Targeted URL Scan functionalities to detect Local File Inclusion vulnerabilities in web applications. By automating the search for potentially vulnerable pages and providing the ability to scan specific URLs, LFI Space empowers security professionals to identify LFI vulnerabilities effectively. With its user-friendly interface and comprehensive scanning capabilities, LFI Space is an invaluable asset for enhancing the security posture of web applications.
inurl:/filedown.php?file=
inurl:/news.php?include=
inurl:/view/lang/index.php?page=?page=
inurl:/shared/help.php?page=
inurl:/include/footer.inc.php?_AMLconfig[cfg_serverpath]=
inurl:/squirrelcart/cart_content.php?cart_isp_root=
inurl:index2.php?to=
inurl:index.php?load=
inurl:home.php?pagina=
/surveys/survey.inc.php?path=
index.php?body=
/classes/adodbt/sql.php?classes_dir=
enc/content.php?Home_Path=
git clone https://github.com/capture0x/Lfi-Space/
cd Lfi-Space
pip3 install -r requirements.txtpython3 lfi.pyContributions are welcome! If you find any issues or have suggestions for improvements, please open an issue or submit a pull request.
For bug reports or enhancements, please open an issue here.
Copyright 2023
~/.kube/config) is properly configured for the target cluster.deploy/kubei.yaml is used to deploy and configure Kubei on your cluster.IGNORE_NAMESPACES env variable to ignore specific namespaces. Set TARGET_NAMESPACE to scan a specific namespace, or leave empty to scan all namespaces.MAX_PARALLELISM env variable for the maximum number of simultaneous scanners.SEVERITY_THRESHOLD threshold will be reported. Supported levels are Unknown, Negligible, Low, Medium, High, Critical, Defcon1. Default is Medium.DELETE_JOB_POLICY env variable to define whether or not to delete completed scanner jobs. Supported values are:All - All jobs will be deleted.Successful - Only successful jobs will be deleted (default).Never - Jobs will never be deleted.kubectl apply -f https://raw.githubusercontent.com/Portshift/kubei/master/deploy/kubei.yamlkubectl -n kubei get pod -lapp=kubei
kubectl -n kubei port-forward $(kubectl -n kubei get pods -lapp=kubei -o jsonpath='{.items[0].metadata.name}') 8080 kubectl -n kubei logs $(kubectl -n kubei get pods -lapp=kubei -o jsonpath='{.items[0].metadata.name}') 
deploy/kubei.yaml.
The security of mobile devices has become a critical concern due to the increasing amount of sensitive data being stored on them. With the rise of Android OS as the most popular mobile platform, the need for effective tools to assess its security has also increased. In response to this need, a new Android framework has emerged that combines three powerful tools - AndroPass, APKUtil, RMS, and MobFS - to conduct comprehensive vulnerability analysis of Android applications. This framework is known as QuadraInspect.
QuadraInspect is an Android framework that integrates AndroPass, APKUtil, RMS and MobFS, providing a powerful tool for analyzing the security of Android applications. AndroPass is a tool that focuses on analyzing the security of Android applications' authentication and authorization mechanisms, while APKUtil is a tool that extracts valuable information from an APK file. Lastly, MobFS and RMS facilitates the analysis of an application's filesystem by mounting its storage in a virtual environment.
By combining these three tools, QuadraInspect provides a comprehensive approach to vulnerability analysis of Android applications. This framework can be used by developers, security researchers, and penetration testers to assess the security of their own or third-party applications. QuadraInspect provides a unified interface for all three tools, making it easier to use and reducing the time required to conduct comprehensive vulnerability analysis. Ultimately, this framework aims to increase the security of Android applications and protect users' sensitive data from potential threats.
To install the tools you need to: First : git clone https://github.com/morpheuslord/QuadraInspect
Second Open a Administrative cmd or powershell (for Mobfs setup) and run : pip install -r requirements.txt && python3 main.py
Third : Once QuadraInspect loads run this command QuadraInspect Main>> : START install_tools
The tools will be downloaded to the tools directory and also the setup.py and setup.bat commands will run automatically for the complete installation.
Each module has a help function so that the commands and the discriptions are detailed and can be altered for operation.
These are the key points that must be addressed for smooth working:
args or using SET target withing the tool.target folder as all the tool searches for the target file with that folder.There are 2 modes:
|
└─> F mode
└─> A mode
The f mode is a mode where you get the active interface for using the interactive vaerion of the framework with the prompt, etc.
F mode is the normal mode and can be used easily
A mode or argumentative mode takes the input via arguments and runs the commands without any intervention by the user this is limited to the main menu in the future i am planning to extend this feature to even the encorporated codes.
python main.py --target <APK_file> --mode a --command install_tools/tools_name/apkleaks/mobfs/rms/apkleaksthe main menu of the entire tool has these options and commands:
| Command | Discription |
|---|---|
SET target | SET the name of the targetfile |
START install_tools | If not installed this will install the tools |
LIST tools_name | List out the Tools Intigrated |
START apkleaks | Use APKLeaks tool |
START mobfs | Use MOBfs for dynamic and static analysis |
START andropass | Use AndroPass APK analizer |
help | Display help menu |
SHOW banner | Display banner |
quit | Quit the program |
As mentioned above the target must be set before any tool is used.
The APKLeaks menu is also really straight forward and only a few things to consider:
SET output and SET json-out takes file names not the actual files it creates an output in the result directory.SET pattern option takes a name of a json pattern file. The JSON file must be located in the pattern directory| OPTION | SET Value |
|---|---|
SET output | Output for the scan data file name |
SET arguments | Additional Disassembly arguments |
SET json-out | JSON output file name |
SET pattern | The pre-searching pattern for secrets |
help | Displays help menu |
return | Return to main menu |
quit | Quit the tool |
Mobfs is pritty straight forward only the port number must be taken care of which is by default on port 5000 you just need to start the program and connect to it on 127.0.0.1:5000 over your browser.
AndroPass is also really straight forward it just takes the file as input and does its job without any other inputs.
The APK analysis framework will follow a modular architecture, similar to Metasploit. It will consist of the following modules:
Currentluy there only 3 but if wanted people can add more tools to this these are the things to be considered:
config/installer.py
config/mobfs.py , config/androp.py, config/apkleaks.py
If wanted you could do your upgrades and add it to this repository for more people to use kind of growing this tool.
OfensivePipeline allows you to download and build C# tools, applying certain modifications in order to improve their evasion for Red Team exercises.
A common use of OffensivePipeline is to download a tool from a Git repository, randomise certain values in the project, build it, obfuscate the resulting binary and generate a shellcode.
OffensivePipeline.exe list
OffensivePipeline.exe all
OffensivePipeline.exe t toolName
OffensivePipeline.exe
PS C:\OffensivePipeline> .\OffensivePipeline.exe t rubeus
ooo
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/ _ \ / _|/ _| ___ _ __ ___(_)_ _____| _ \(_)_ __ ___| (_)_ __ ___ :h .yoooMoM
| | | | |_| |_ / _ \ '_ \/ __| \ \ / / _ \ |_) | | '_ \ / _ \ | | '_ \ / _ \ oo oo
| |_| | _| _| __/ | | \__ \ |\ V / __/ __/| | |_) | __/ | | | | | __/ oo oo
\___/|_| |_| \___|_| |_|___/_| \_/ \___|_| |_| .__/ \___|_|_|_| |_|\___| oo oo
|_| MoMoooy. h:
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@aetsu
v2.0.0
[+] Loading tool: Rubeus
Clonnig repository: Rubeus into C:\OffensivePipeline\Git\Rubeus
Repository Rubeus cloned into C:\OffensivePipeline\Git\Rubeus
[+] Load RandomGuid module
Searching GUIDs...
> C:\OffensivePipeline\Git\Rubeus\Rubeus.sln
> C:\OffensivePipeline\Git\Rubeus\Rubeus\Rubeus.csproj
> C:\OffensivePipeline\Git\Rubeus\Rubeus\Properties\AssemblyInfo.cs
Replacing GUIDs...
File C:\OffensivePipeline\Git\Rubeus\Rubeus.sln:
> Replacing GUID 658C8B7F-3664-4A95-9572-A3E5871DFC06 with 3bd82351-ac9a-4403-b1e7-9660e698d286
> Replacing GUID FAE04EC0-301F-11D3-BF4B-00C04F79EFBC with 619876c2-5a8b-4c48-93c3-f87ca520ac5e
> Replacing GUID 658c8b7f-3664-4a95-9572-a3e5871dfc06 with 11e0084e-937f-46d7-83b5-38a496bf278a
[+] No errors!
File C:\OffensivePipeline\Git\Rubeus\Rubeus\Rubeus.csproj:
> Replacing GUID 658C8B7F-3664-4A95-9572-A3E5871DFC06 with 3bd82351-ac9a-4403-b1e7-9660e698d286
> Replacing GUID FAE04EC0-301F-11D3-BF4B-00C04F79EFBC with 619876c2-5a8b-4c48-93c3-f87ca520ac5e
> Replacing GUID 658c8b7f-3664-4a95-9572-a3e5871dfc06 with 11e0084e-937f-46d7-83b5-38a496bf278a
[+] No errors!
File C:\OffensivePipeline\Git\Rubeus\Rubeus\Properties\AssemblyInfo.cs:
> Replacing GUID 658C8B7F-3664-4A95-9572-A3E5871DFC06 with 3bd82351-ac9a-4403-b1e7-9660e698d286
> Replacing GUID FAE04EC0-301F-11D3-BF4B-00C04F79EFBC with 619876c2-5a8b-4c48-93c3-f87ca520ac5e
> Replacing GUID 658c8b7f-3664-4a95-9572-a3e5871dfc06 with 11e0084e-937f-46d7-83b5-38a496bf278a
[+] No errors!
[+] Load RandomAssemblyInfo module
Replacing strings in C:\OffensivePipeline\Git\Rubeus\Rubeus\Properties\AssemblyInfo.cs
[assembly: AssemblyTitle("Rubeus")] -> [assembly: AssemblyTitle("g4ef3fvphre")]
[assembly: AssemblyDescription("")] -> [assembly: AssemblyDescription("")]
[assembly: AssemblyConfiguration("")] -> [assembly: AssemblyConfiguration("")]
[assembly: AssemblyCompany("")] -> [assembly: AssemblyCompany("")]
[assembly: AssemblyProduc t("Rubeus")] -> [assembly: AssemblyProduct("g4ef3fvphre")]
[assembly: AssemblyCopyright("Copyright © 2018")] -> [assembly: AssemblyCopyright("Copyright © 2018")]
[assembly: AssemblyTrademark("")] -> [assembly: AssemblyTrademark("")]
[assembly: AssemblyCulture("")] -> [assembly: AssemblyCulture("")]
[+] Load BuildCsharp module
[+] Checking requirements...
[*] Downloading nuget.exe from https://dist.nuget.org/win-x86-commandline/latest/nuget.exe
[+] Download OK - nuget.exe
[+] Path found - C:\Program Files (x86)\Microsoft Visual Studio\2022\BuildTools\Common7\Tools\VsDevCmd.bat
Solving dependences with nuget...
Building solution...
[+] No errors!
[+] Output folder: C:\OffensivePipeline\Output\Rubeus_vh00nc50xud
[+] Load ConfuserEx module
[+] Checking requirements...
[+] Downloading ConfuserEx from https://github.com/mkaring/ConfuserEx/releases/download/v1.6.0/ConfuserEx-CLI.zip
[+] Download OK - ConfuserEx
Confusing...
[+] No errors!
[+] Load Donut module
Generating shellcode...
Payload options:
Domain: RMM6XFC3
Runtime:v4.0.30319
Raw Payload: C:\OffensivePipeline\Output\Rubeus_vh00nc50xud\ConfuserEx\Donut\Rubeus.bin
B64 Payload: C:\OffensivePipeline\Output\Rubeus_vh00nc50xud\ConfuserEx\Donut\Rubeus.bin.b64
[+] No errors!
[+] Generating Sha256 hashes
Output file: C:\OffensivePipeline\Output\Rubeus_vh00nc50xud
-----------------------------------------------------------------
SUMMARY
- Rubeus
- RandomGuid: OK
- RandomAssemblyInfo: OK
- BuildCsharp: OK
- ConfuserEx: OK
- Donut: OK
-----------------------------------------------------------------
The scripts for downloading the tools are in the Tools folder in yml format. New tools can be added by creating new yml files with the following format:
tool:
- name: Rubeus
description: Rubeus is a C# toolset for raw Kerberos interaction and abuses
gitLink: https://github.com/GhostPack/Rubeus
solutionPath: Rubeus\Rubeus.sln
language: c#
plugins: RandomGuid, RandomAssemblyInfo, BuildCsharp, ConfuserEx, Donut
authUser:
authToken: Where:
tool:
- name: SharpHound3-Custom
description: C# Rewrite of the BloodHound Ingestor
gitLink: https://github.com/aaaaaaa/SharpHound3-Custom
solutionPath: SharpHound3-Custom\SharpHound3.sln
language: c#
plugins: RandomGuid, RandomAssemblyInfo, BuildCsharp, ConfuserEx, Donut
authUser: aaaaaaa
authToken: abcdefghijklmnopqrsthtnfWhere:
tool:
- name: SeatbeltLocal
description: Seatbelt is a C# project that performs a number of security oriented host-survey "safety checks" relevant from both offensive and defensive security perspectives.
gitLink: C:\Users\alpha\Desktop\SeatbeltLocal
solutionPath: SeatbeltLocal\Seatbelt.sln
language: c#
plugins: RandomGuid, RandomAssemblyInfo, BuildCsharp, ConfuserEx, Donut
authUser:
authToken: Where:
In the OffensivePipeline.dll.config file it's possible to change the version of the build tools used.
<add key="BuildCSharpTools" value="C:\Program Files (x86)\Microsoft Visual Studio\2019\BuildTools\Common7\Tools\VsDevCmd.bat"/><add key="BuildCSharpTools" value="C:\Program Files (x86)\Microsoft Visual Studio\2022\BuildTools\Common7\Tools\VsDevCmd.bat"/>
autoSSRF is your best ally for identifying SSRF vulnerabilities at scale. Different from other ssrf automation tools, this one comes with the two following original features :
Smart fuzzing on relevant SSRF GET parameters
When fuzzing, autoSSRF only focuses on the common parameters related to SSRF (?url=, ?uri=, ..) and doesn’t interfere with everything else. This ensures that the original URL is still correctly understood by the tested web-application, something that might doesn’t happen with a tool which is blindly spraying query parameters.
Context-based dynamic payloads generation
For the given URL : https://host.com/?fileURL=https://authorizedhost.com, autoSSRF would recognize authorizedhost.com as a potentially white-listed host for the web-application, and generate payloads dynamically based on that, attempting to bypass the white-listing validation. It would result to interesting payloads such as : http://authorizedhost.attacker.com, http://authorizedhost%252F@attacker.com, etc.
Furthermore, this tool guarantees almost no false-positives. The detection relies on the great ProjectDiscovery’s interactsh, allowing autoSSRF to confidently identify out-of-band DNS/HTTP interactions.
python3 autossrf.py -hThis displays help for the tool.
usage: autossrf.py [-h] [--file FILE] [--url URL] [--output] [--verbose]
options:
-h, --help show this help message and exit
--file FILE, -f FILE file of all URLs to be tested against SSRF
--url URL, -u URL url to be tested against SSRF
--output, -o output file path
--verbose, -v activate verbose modeSingle URL target:
python3 autossrf.py -u https://www.host.com/?param1=X¶m2=Y¶m2=ZMultiple URLs target with verbose:
python3 autossrf.py -f urls.txt -v1 - Clone
git clone https://github.com/Th0h0/autossrf.git2 - Install requirements
Python libraries :
cd autossrf
pip install -r requirements.txtInteractsh-Client :
go install -v github.com/projectdiscovery/interactsh/cmd/interactsh-client@latestautoSSRF is distributed under MIT License.
Appshark is a static taint analysis platform to scan vulnerabilities in an Android app.
Appshark requires a specific version of JDK -- JDK 11. After testing, it does not work on other LTS versions, JDK 8 and JDK 16, due to the dependency compatibility issue.
We assume that you are working in the root directory of the project repo. You can build the whole project with the gradle tool.
$ ./gradlew build -x test After executing the above command, you will see an artifact file AppShark-0.1.1-all.jar in the directory build/libs.
Like the previous step, we assume that you are still in the root folder of the project. You can run the tool with
$ java -jar build/libs/AppShark-0.1.1-all.jar config/config.json5The config.json5 has the following configuration contents.
{
"apkPath": "/Users/apks/app1.apk",
"out": "out",
"rules": "unZipSlip.json",
"maxPointerAnalyzeTime": 600
} Each JSON field is explained below.
If you provide a configuration JSON file which sets the output path as out in the project root directory, you will find the result file out/results.json after running the analysis.
Below is an example of the results.json.
{
"AppInfo": {
"AppName": "test",
"PackageName": "net.bytedance.security.app",
"min_sdk": 17,
"target_sdk": 28,
"versionCode": 1000,
"versionName": "1.0.0"
},
"SecurityInfo": {
"FileRisk": {
"unZipSlip": {
"category": "FileRisk",
"detail": "",
"model": "2",
"name": "unZipSlip",
"possibility": "4",
"vulners": [
{
"details": {
"position": "<net.bytedance.security.app.pathfinder.testdata.ZipSlip: void UnZipFolderFix1(java.lang.String,java.lang.String)>",
"Sink": "<net.bytedance.security.app.pathfinder.testdata.ZipSlip: void UnZipFolderFix1(java.lang.String,java.lang.String)>->$r31",
"entryMethod": "<net.bytedance.security.app.pathfinder.testdata.ZipSlip: void f()>",
"Source": "<net.byte dance.security.app.pathfinder.testdata.ZipSlip: void UnZipFolderFix1(java.lang.String,java.lang.String)>->$r3",
"url": "/Volumes/dev/zijie/appshark-opensource/out/vuln/1-unZipSlip.html",
"target": [
"<net.bytedance.security.app.pathfinder.testdata.ZipSlip: void UnZipFolderFix1(java.lang.String,java.lang.String)>->$r3",
"pf{obj{<net.bytedance.security.app.pathfinder.testdata.ZipSlip: void UnZipFolderFix1(java.lang.String,java.lang.String)>:35=>java.lang.StringBuilder}(unknown)->@data}",
"<net.bytedance.security.app.pathfinder.testdata.ZipSlip: void UnZipFolderFix1(java.lang.String,java.lang.String)>->$r11",
"<net.bytedance.security.app.pathfinder.testdata.ZipSlip: void UnZipFolderFix1(java.lang.String,java.lang.String)>->$r31"
]
},
"hash": "ec57a2a3190677ffe78a0c8aaf58ba5aee4d 2247",
"possibility": "4"
},
{
"details": {
"position": "<net.bytedance.security.app.pathfinder.testdata.ZipSlip: void UnZipFolder(java.lang.String,java.lang.String)>",
"Sink": "<net.bytedance.security.app.pathfinder.testdata.ZipSlip: void UnZipFolder(java.lang.String,java.lang.String)>->$r34",
"entryMethod": "<net.bytedance.security.app.pathfinder.testdata.ZipSlip: void f()>",
"Source": "<net.bytedance.security.app.pathfinder.testdata.ZipSlip: void UnZipFolder(java.lang.String,java.lang.String)>->$r3",
"url": "/Volumes/dev/zijie/appshark-opensource/out/vuln/2-unZipSlip.html",
"target": [
"<net.bytedance.security.app.pathfinder.testdata.ZipSlip: void UnZipFolder(java.lang.String,java.lang.String)>->$r3",
"pf{obj{<net.bytedance.security.a pp.pathfinder.testdata.ZipSlip: void UnZipFolder(java.lang.String,java.lang.String)>:33=>java.lang.StringBuilder}(unknown)->@data}",
"<net.bytedance.security.app.pathfinder.testdata.ZipSlip: void UnZipFolder(java.lang.String,java.lang.String)>->$r14",
"<net.bytedance.security.app.pathfinder.testdata.ZipSlip: void UnZipFolder(java.lang.String,java.lang.String)>->$r34"
]
},
"hash": "26c6d6ee704c59949cfef78350a1d9aef04c29ad",
"possibility": "4"
}
],
"wiki": "",
"deobfApk": "/Volumes/dev/zijie/appshark-opensource/app.apk"
}
}
},
"DeepLinkInfo": {
},
"HTTP_API": [
],
"JsBridgeInfo": [
],
"BasicInfo": {
"ComponentsInfo": {
},
"JSNativeInterface": [
]
},
"UsePermissions": [
],
"DefinePermis sions": {
},
"Profile": "/Volumes/dev/zijie/appshark-opensource/out/vuln/3-profiler.json"
}
export PPSSWWDD=yourRootPswd More references: config/doNmapScan.sh By default, naabu is used to complete port scanning -stats=true to view the scanning progress Can I not scan ports?
noScan=true ./scan4all -l list.txt -v
# nmap result default noScan=true
./scan4all -l nmapRssuilt.xml -v| TAG | COUNT | AUTHOR | COUNT | DIRECTORY | COUNT | SEVERITY | COUNT | TYPE | COUNT |
|---|---|---|---|---|---|---|---|---|---|
| cve | 1294 | daffainfo | 605 | cves | 1277 | info | 1352 | http | 3554 |
| panel | 591 | dhiyaneshdk | 503 | exposed-panels | 600 | high | 938 | file | 76 |
| lfi | 486 | pikpikcu | 321 | vulnerabilities | 493 | medium | 766 | network | 50 |
| xss | 439 | pdteam | 269 | technologies | 266 | critical | 436 | dns | 17 |
| wordpress | 401 | geeknik | 187 | exposures | 254 | low | 211 | ||
| exposure | 355 | dwisiswant0 | 169 | misconfiguration | 207 | unknown | 7 | ||
| cve2021 | 322 | 0x_akoko | 154 | token-spray | 206 | ||||
| rce | 313 | princechaddha | 147 | workflows | 187 | ||||
| wp-plugin | 297 | pussycat0x | 128 | default-logins | 101 | ||||
| tech | 282 | gy741 | 126 | file | 76 |
281 directories, 3922 files.
Support 7000+ web fingerprint scanning, identification:
Support 146 protocols and 90000+ rule port scanning
Fast HTTP sensitive file detection, can customize dictionary
Landing page detection
Supports multiple types of input - STDIN/HOST/IP/CIDR/URL/TXT
Supports multiple output types - JSON/TXT/CSV/STDOUT
Highly integratable: Configurable unified storage of results to Elasticsearch [strongly recommended]
Smart SSL Analysis:
Automatically identify the case of multiple IPs associated with a domain (DNS), and automatically scan the associated multiple IPs
Smart processing:
Automated supply chain identification, analysis and scanning
Link python3 log4j-scan
mkdir ~/MyWork/;cd ~/MyWork/;git clone https://github.com/hktalent/log4j-scanIntelligently identify honeypots and skip targets. This function is disabled by default. You can set EnableHoneyportDetection=true to enable
Highly customizable: allow to define your own dictionary through config/config.json configuration, or control more details, including but not limited to: nuclei, httpx, naabu, etc.
support HTTP Request Smuggling: CL-TE、TE-CL、TE-TE、CL_CL、BaseErr
Support via parameter Cookie='PHPSession=xxxx' ./scan4all -host xxxx.com, compatible with nuclei, httpx, go-poc, x-ray POC, filefuzz, http Smuggling
download from Releases
go install github.com/hktalent/scan4all@2.6.9
scan4all -hmkdir -p logs data
docker run --restart=always --ulimit nofile=65536:65536 -p 9200:9200 -p 9300:9300 -d --name es -v $PWD/logs:/usr/share/elasticsearch/logs -v $PWD /config/elasticsearch.yml:/usr/share/elasticsearch/config/elasticsearch.yml -v $PWD/config/jvm.options:/usr/share/elasticsearch/config/jvm.options -v $PWD/data:/ usr/share/elasticsearch/data hktalent/elasticsearch:7.16.2
# Initialize the es index, the result structure of each tool is different, and it is stored separately
./config/initEs.sh
# Search syntax, more query methods, learn Elasticsearch by yourself
http://127.0.0.1:9200/nmap_index/_doc/_search?q=_id:192.168.0.111
where 92.168.0.111 is the target to query
go build
# Precise scan url list UrlPrecise=true
UrlPrecise=true ./scan4all -l xx.txt
# Disable adaptation to nmap and use naabu port to scan its internally defined http-related ports
priorityNmap=false ./scan4all -tp http -list allOut.txt -vmore see: discussions
Explore the nature of vulnerabilities in this episode of ThreatWise TV.
It’s shaping up to be another big year for vulnerability disclosure. Already the number of Common Vulnerabilities and Exposures (CVEs) disclosed has crossed 18,000 and it’s on track to make this another record-breaking year.
With new CVEs being disclosed daily, it has become increasingly difficult for security teams to stay abreast of the latest risks, let alone quickly determine which ones apply to their network environment. From those, prioritizing which CVEs to patch first adds an additional wrinkle to the process.
If this wasn’t challenging enough, a curve ball that’s often lobbed at security teams are the “breaking news” vulnerabilities— vulnerabilities picked up by the security media, often with much fanfare. The stories surrounding these high-profile vulnerabilities generally carry an implied threat that the CVE in question will throw the doors wide open to attackers if not addressed immediately. What security team hasn’t had someone from the C-suite share an article they’ve read, asking “are we protected from this?”
On the surface, CVEs that appear severe enough to garner media attention do seem like a good place to start when addressing vulnerabilities in your environment. But vulnerabilities are complicated, and what a security researcher manages to do within a controlled environment doesn’t always translate into real-world attacks. In fact, most disclosed vulnerabilities never see active exploitation. And of those that do, not every vulnerability ends up becoming a tool in an attacker’s arsenal. Bad actors generally follow the path of least resistance when they compromise a network, relying on tested exploits long before trying something new and unproven.
This begs the question: how much overlap is there between the most talked about vulnerabilities and those that are widely used in attacks? Moreover, if media attention isn’t a reliable indicator, what else might predict if a vulnerability will be used in an attack?
To answer these questions, we used intelligence tools available from Cisco’s Kenna Security risk-based vulnerability management (RBVM) software. In particular, Kenna.VI+ consolidates a variety of vulnerability intelligence, where a CVE ID lookup can pull back a wealth of information. In addition to this, Kenna.VI+ includes an API that brings in an additional layer of external threat intelligence, enabling further analysis.
We started with a direct comparison of Successful Exploitations and Chatter Count from within Kenna.VI+. The former is a full count of confirmed exploits within the dataset, while the latter is a count of mentions in the news, social media, various forums, and the dark web.
Our first pass at the data included a comparison of the top 50 CVEs in both Successful Exploitations and Chatter Count. However, there were only two CVEs that overlapped. The data showed that many of the top exploited CVEs were old and predated the data in Chatter Count. We quickly decided that this wasn’t a fair comparison.
To get a better look at more relevant CVEs, we limited the dataset to a range of 10 years. Unfortunately, this did not do much to improve things—only three CVEs showed up in both lists.
A more effective approach was to look at CVEs that we know are actively being exploited. The Cybersecurity and Infrastructure Security Agency (CISA) happens to maintain such a list. The Known Exploited Vulnerabilities (KEV) catalog is considered an authoritative compilation of vulnerabilities identified as being actively exploited in the wild.
Running the KEV catalog though Kenna.VI+ resulted in six CVEs that appeared in the top 50 for both lists, with a single overlap in the top 10. This leads us to conclude that the vulnerabilities with the most discussion are not the same as those being actively exploited in the majority of cases.
| CVE | Brief description | |
| 1 | CVE-2017-9841 | PHPUnit vulnerability (used to target popular CMSes) |
| 2 | CVE-2021-44228 | Log4j vulnerability |
| 3 | CVE-2019-0703 | Windows SMB information disclosure vulnerability |
| 4 | CVE-2014-0160 | Heartbleed vulnerability |
| 5 | CVE-2017-9805 | REST plugin in Apache Struts vulnerability |
| 6 | CVE-2017-11882 | Microsoft Office memory corruption vulnerability |
| 7 | CVE-2017-5638 | Apache Struts vulnerability (used in Equifax breach) |
| 8 | CVE-2012-1823 | 10-year-old PHP vulnerability |
| 9 | CVE-2017-0144 | EternalBlue vulnerability |
| 10 | CVE-2018-11776 | Apache Struts RCE vulnerability |
| CVE | Brief description | |
| 1 | CVE-2021-26855 | Microsoft Exchange vulnerability (used in Hafnium attacks) |
| 2 | CVE-2021-40444 | Microsoft MSHTML RCE vulnerability |
| 3 | CVE-2021-26084 | Confluence Server and Data Center vulnerability |
| 4 | CVE-2021-27065 | Microsoft Exchange vulnerability (used in Hafnium attacks) |
| 5 | CVE-2021-34473 | Microsoft Exchange vulnerability (used in Hafnium attacks) |
| 6 | CVE-2021-26858 | Microsoft Exchange vulnerability (used in Hafnium attacks) |
| 7 | CVE-2021-44228 | Log4j vulnerability |
| 8 | CVE-2021-34527 | One of the PrintNightmare vulnerabilities |
| 9 | CVE-2021-41773 | Apache HTTP Server vulnerability |
| 10 | CVE-2021-31207 | One of the ProxyShell vulnerabilities |
Despite the lack of overlap, there are many well-known vulnerabilities at the top of both lists. Heartbleed and EternalBlue appear on the top 10 exploited list, while Hafnium, PrintNightmare, and ProxyShell make the top 10 most talked about CVEs.
The Log4j vulnerability is the only CVE that appears in both lists. This isn’t surprising considering the ubiquity of Log4j in modern software. It’s the second-most exploited vulnerability—far outpacing the CVEs directly below it. This, coupled with its appearance in the chatter list, puts it in a class of its own. In a brief period, it’s managed to outpace older CVEs that are arguably just as well known.
The CVE that recorded the most successful exploitations is a five-year-old vulnerability in PHPUnit. This is a popular unit-testing framework that’s used by many CMSes, such as Drupal, WordPress, MediaWiki, and Moodle.
Since many websites are built with these tools, this exploit can be a handy vector for gaining initial access to unpatched webservers. This also lines up with research we conducted last year, where this vulnerability was one of the most common Snort detections seen by Cisco Secure Firewall.
All four of the Microsoft Exchange Server vulnerabilities used in the Hafnium attacks appear in the most talked about list of CVEs. However, even when you add all four of these CVEs together, they still don’t come anywhere close to the counts seen in the top exploited CVEs.
If media attention is not a good predictor of use for exploitation, then what are the alternatives?
The Common Vulnerability Scoring System (CVSS) is a well-known framework for gauging the severity of vulnerabilities. We looked for CVEs from the KEV catalog that were ranked as “critical”—9.0 and above in the CVSSv3 specification. Examining the entire KEV catalog, 28% of the CVEs have a score of 9.0 or higher. Of the top 50 successfully exploited, 38% had such scores.
This is an improvement, but the CVSSv3 specification was released in 2015. Many CVEs in the KEV catalog predate this—19% of the entire catalog and 28% of the top 50—and have no score.
Using the previous CVSS specification does fill this gap—36% overall and 52% of the top 50 score 9.0 or higher. However, the older CVSS specification comes with its share of issues as well.
Another indicator worth exploring is remote control execution (RCE). A vulnerability with RCE grants an attacker the ability to access and control a vulnerable system from anywhere. It turns out that 45% of the CVEs in our dataset allow for RCE, and 66% of the top 50, making it the most worthwhile indicator analyzed.
Let’s summarize how we’ve honed our approach to determine if media attention and exploitation line up:
| Data set | Exploitation and Chatter lists | Number of CVEs |
| All CVEs | Appears in both top 50 | 2 |
| Appears in both top 50 (last 10 years) | 3 | |
| KEV Catalog | Appears in both top 50 | 6 |
| Appears in both top 10 | 1 |
And here’s a summary of our look at other indicators:
| KEV Catalog | Top 50 exploited | |
| CVSSv3 (9.0+) | 28% | 38% |
| CVSS (9.0+) | 36% | 52% |
| Allows for RCE | 45% | 66% |
All of this analysis provides a clear answer to our original question—the most regularly exploited CVEs aren’t the most talked about. Additional work highlights that monitoring variables like RCE can help with prioritization.
For illustrative purposes we’ve only looked at a few indicators that could be used to prioritize CVEs. While some did better than others, we don’t recommend relying on a single variable in making decisions about vulnerability management. Creating an approach that folds in multiple indicators is a far better strategy when it comes to real-world application of this data. And while our findings here speak to the larger picture, every network is different.
Regardless of which list they appear on, be it Successful Exploitations or Chatter Count, it’s important to point out that all these vulnerabilities are serious. Just because Hafnium has more talk than Heartbleed doesn’t make it any less dangerous if you have assets that are vulnerable to it. The fact is that while CVEs with more talk didn’t make the top of the exploitation list, they still managed to rack up tens of thousands of successful exploitations.
It’s important to know how to prioritize security updates, fixing those that expose you to the most risk as soon as possible. From our perspective, here are some basic elements in the Cisco Secure portfolio that can help.
Kenna Security, a pioneer in risk-based vulnerability management, relies on threat intel and prioritization to keep security and IT teams focused on risks. Using data science, Kenna processes and analyzes 18+ threat and exploit intelligence feeds, and 12.7+ billion managed vulnerabilities to give you an accurate view of your company’s risk. With our risk scoring and remediation intelligence, you get the info you need to make truly data-driven remediation decisions.
To responsibly protect a network, it’s important to monitor all assets that connect to it and ensure they’re kept up to date. Duo Device Trust can check the patch level of devices for you before they’re granted access to connect to corporate applications or sensitive data. You can even block access and enable self-remediation for devices that are found to be non-compliant.
How about remote workers? By leveraging the Network Visibility Module in Cisco Secure Client as a telemetry source, Cisco Secure Cloud Analytics can capture endpoint-specific user and device context to supply visibility into remote worker endpoint status. This can bolster an organization’s security posture by providing visibility on remote employees that are running software versions with vulnerabilities that need patching.
Lastly, for some “lateral thinking” about vulnerability management, take a look at this short video of one of our Advisory CISOs, Wolfgang Goerlich. Especially if you’re a fan of the music of the 1920s…
We’d love to hear what you think. Ask a Question, Comment Below, and Stay Connected with Cisco Secure on social!
Cisco Secure Social Channels
SCodeScanner stands for Source Code scanner where the user can scans the source code for finding the Critical Vulnerabilities. The main objective for this scanner is to find the vulnerabilities inside the source code before code gets published in Prod.
SCodeScanner received 5 CVEs for finding vulnerabilities in multiple CMS plugins.
pip3 install -r requirements.txt python3 scscanner.py --help I would love to hear your feedback on this tool. Open issues if you found any. And open PR request if you have something.
Aura is a static analysis framework developed as a response to the ever-increasing threat of malicious packages and vulnerable code published on PyPI.
Project goals:
Feature list:
Didn't find what you are looking for? Aura's architecture is based on a robust plugin system, where you can customize almost anything, ranging from a set of data analyzers, transport protocols to custom out formats.
# Via pip:
pip install aura-security[full]
# or build from source/git
poetry install --no-dev -E full
Or just use a prebuild docker image sourcecodeai/aura:dev
docker run -ti --rm sourcecodeai/aura:dev scan pypi://requests -v
Aura uses a so-called URIs to identify the protocol and location to scan, if no protocol is used, the scan argument is treated as a path to the file or directory on a local system.
Diff packages:
docker run -ti --rm sourcecodeai/aura:dev diff pypi://requests pypi://requests2
Find most popular typosquatted packages (you need to call aura update to download the dataset first):
aura find-typosquatting --max-distance 2 --limit 10
While there are other tools with functionality that overlaps with Aura such as Bandit, dlint, semgrep etc. the focus of these alternatives is different which impacts the functionality and how they are being used. These alternatives are mainly intended to be used in a similar way to linters, integrated into IDEs, frequently run during the development which makes it important to minimize false positives and reporting with clear actionable explanations in ideal cases.
Aura on the other hand reports on ** behavior of the code**, anomalies, and vulnerabilities with as much information as possible at the cost of false positive. There are a lot of things reported by aura that are not necessarily actionable by a user but they tell you a lot about the behavior of the code such as doing network communication, accessing sensitive files, or using mechanisms associated with obfuscation indicating a possible malicious code. By collecting this kind of data and aggregating it together, Aura can be compared in functionality to other security systems such as antivirus, IDS, or firewalls that are essentially doing the same analysis but on a different kind of data (network communication, running processes, etc).
Here is a quick overview of differences between Aura and other similar linters and SAST tools:
# nosec that will suppress the alert at that positionAura framework is licensed under the GPL-3.0. Datasets produced from global scans using Aura are released under the CC BY-NC 4.0 license. Use the following citation when using Aura or data produced by Aura in research:
@misc{Carnogursky2019thesis,
AUTHOR = "CARNOGURSKY, Martin",
TITLE = "Attacks on package managers [online]",
YEAR = "2019 [cit. 2020-11-02]",
TYPE = "Bachelor Thesis",
SCHOOL = "Masaryk University, Faculty of Informatics, Brno",
SUPERVISOR = "Vit Bukac",
URL = "Available at WWW <https://is.muni.cz/th/y41ft/>",
}
