For a hobby project built in my spare time to provide a simple community service, Have I Been Pwned sure has, well, "escalated". Today, we support hundreds of thousands of website visitors each day, tens of millions of API queries, and hundreds of millions of password searches. We're processing billions of compromised records each year provided by breached companies, white hat researchers, hackers and law enforcement agencies. And it's used by every conceivable demographic: infosec pros, "mums and dads", customer support services, and, according to the data, more than half the Fortune 500 who are actively monitoring the exposure of their domains. So yeah, "escalated" seems fair!

Amidst all the time spent processing data, we've been trying to figure out where to invest energy in building new stuff. In essence, data breaches are pretty simple: you've got a bunch of exposed email addresses attributed to a source, sitting next to a whole bunch of fields we describe with metadata. Our goal has always been to help people use this data to do good after bad things happen, and today we're launching a bunch of new features to do just that. So, here goes:

New Features, New Plans

In the beginning (ok, in "recent years"), there was one plan we referred to as "Pwned", and within that, there were various levels. For example, the entry-level plan has been "Pwned 1," and to this day, more than half our subscriptions are on it. That's "a coffee a month" for a simple service that, by the raw numbers, does precisely what most of our subscribers are looking for. These are typically small businesses that make a handful of API queries or monitor a domain or two with a few email addresses. It's simple, effective and... insufficient for larger organisations. So, we added Pwned 2, 3 and 4, and they all added more RPMs for email searches and more capacity for searching larger domains. Then we added Pwned 5, which added stealer log support, and somewhere along the way also added Pwned Ultra tiers for making large numbers of API requests. As a result, that one "plan" added more and more stuff at different levels and ultimately became a bit kludgy.

Today, we're launching a bunch of new features to better support the volume and privacy needs of our subscribers, and we're shuffling our existing plans to help do this. Here's what they now look like:

1. Core: The fundamentals, largely being what we already had and designed for entry-level use cases
2. Pro: Contains a bunch of the new features designed for larger orgs and those searching domains on behalf of customers
3. High RPM: The old "Ultra" plan levels, designed solely for making large volumes of requests to the email search API
4. Enterprise: We've had this for many years now, and it's a more tailored offering

So, that's the high-level overview. Let's now look at all the new stuff and everything that changes:

Supporting MSPs Monitoring on Behalf of Third Parties

For most people, this won't sound particularly exciting, but I'm putting it up front because I'll refer to it when describing the more important stuff shortly. In the past, we've had the following carve-out in our terms of use, namely, what you're not permitted to use the service for:

the benefit of a third party (including for use by a related entity or for the purpose of reselling or otherwise making the Services available to any third party for commercial benefit)

This excluded managed service providers from, for example, monitoring their customers' domains as part of their services. That clause has now been revised with the preceding text:

unless you have purchased a Paid Service which expressly allows you to do so

Which means we can now welcome MSPs to the Pro and High RPM tiers. They can't just take HIBP and use it to create a competing product (for obvious reasons, that's a pretty standard clause within many online services), but they can absolutely add it to the offerings they provide to their own customers. And we're adding new features to make it easier to do just that, for example:

Automating Domain Verification

Preserving privacy whilst still providing a practical, effective service has always been a balancing act, one I think we've gotten pretty spot on. But the hoops people have had to jump through for domain verification, in particular, have been cumbersome. An organisation wanting to add a bunch of its domains has had to go through the process one by one via the web interface, then verify control over them one by one. They'd spend a lot of time doing kludgy, repetitive work. Today, we're launching two new ways of adding domains in a much more automated fashion, and the first is the verifying via DNS API:

Successfully adding a pre-defined TXT record to DNS is solid proof that whoever is attempting to search that domain genuinely controls it. As well as the old kludgy way of doing it in the browser, waiting for DNS to propagate, then coming back to the browser to complete the verification, we can now fully automate the process via API. Here's how it works:

1. Call the HIBP API to generate the TXT record token
2. Call the API on your DNS provider to add the token to the TXT record
3. Call another HIBP API to validate that the token exists

This is easily scripted in your language of choice, and you can enumerate it over as many domains as you like. You can also keep retrying step 3 above as often as needed when DNS takes a little while to do its thing. It's all now fully documented in the latest version of the API, and ready to roll. But what if you don't control the DNS? Perhaps it's a cumbersome process in your org, or you're an MSP monitoring your customers' domains, but you don't have control of DNS. That's where the verifying by email API comes in:

We've long had a verification process that involves choosing one of several standard aliases on a domain to email a verification token to. You do this via the dashboard, grab the token sent to the email, paste it back into the dashboard and the domain is now verified. The new API makes that much easier, especially when multiple domains are being verified. Here's how it works:

1. Call the HIBP API and specify one of the pre-defined aliases to send a verification email to
2. Click the link in the email and approve the domain to be added to the requester's account

And that's it. We see this being particularly useful for MSPs who can now send a heap of emails on their customers' domains, and so long as someone receives it and clicks the link, that's the verification process done. That API is also now fully documented and ready to roll and is accessible to all Pro plan subscribers.

Auto-verifying Subdomains

This one was just unnecessarily frustrating for larger customers who spread email addresses over multiple subdomains. Let's say a company owns example.com and they successfully verify control of it, but then they distribute their email addresses by region. They end up with addresses @apac.example.com and @emea.example.com and so on, and in the past, needed to verify each subdomain separately.

Turns out we have 154 votes for this feature in User Voice, which is substantially more than I expected. So, in keeping with the theme of the Pro plan making it easier on larger orgs, anyone on that level can now add their apex domain, verify it accordingly, then go to town adding all the subdomains they want without the need for verifying each one.

Bringing K-Anonymity Searches to the Masses

Until today, every time you took out a subscription via the public website and started searching email addresses, it looked like this:

GET https://haveibeenpwned.com/api/v3/breachedaccount/test@example.com

Clearly, this involved sending the email address to HIBP's service. Whilst we don't store those addresses, if you're sending data to a service in this fashion, there's always the technical capability for us to see that piece of PII and associate it back to the requester via their API key. This approach is what we'll refer to as "direct email search". Let's now look at k-anonymity searches, and I'll break it down into a few simple steps:

1. Start by creating a SHA-1 hash of the address to be searched, so for test@example.com, that's:

   567159D622FFBB50B11B0EFD307BE358624A26EE

2. Take the first 6 characters of the hash and pass them to the new API:

   GET https://haveibeenpwned.com/api/v3/breachedaccount/range/567159

   What's really important here is that those 6 characters are the only identifier sent to HIBP and they're completely useless in identifying which address was actually searched for (that link also explains why SHA-1 is perfectly reasonable for this)
3. HIBP then responds with the suffixes of every hash we have that matches that prefix and for each one, the breaches it's appeared against:

   {
     "hashSuffix": "D622FFBB50B11B0EFD307BE358624A26EE",
     "websites": [
         "Adobe",
         "Stratfor",
         "Yahoo",
         ...
     ]
   },
   ...

   The prefix presently contains 393 suffixes, and if one of them matches the remaining characters of the hash of the full email address, you know that's the address you're looking for.

This is the same methodology we've been using for years with the Pwned Passwords search, and we're currently serving about 18 billion requests a month, so it seems that lots of people have easily gotten to grips with it. It's a pretty simple technical concept with great privacy attributes, and it's fully documented on the API page.

K-anonymity searches are now available to all Pro and High RPM subscribers at the same rate limit as the direct searches. That rate limit is shared, so you can either make 100% of them to k-anon or 100% to the direct search or go 50/50. We're really happy with the privacy aspects of this API and we know it ticks a box a lot of orgs have been asking for.

Unsmoothing the API Rate Limit

Previously, when you took out a 10-request-per-minute API key, we implemented a rate limit of 1 request every 6 seconds. The same logic applied to all the higher-tier products, too, and the reason was simply to distribute the load across each minute more evenly or in other words, "smoothing" the rate at which requests were made. That was important earlier on as the underlying Azure infrastructure had to support that traffic, and sudden bursts could be problematic.

But the other thing that was problematic is that people (quite reasonably) assumed that they could make 6 fast requests, wait a minute, then go again. This led to support overhead for us and customer frustration, and neither is good.

With these latest updates, 10RPM (and all the other RPMs) is now implemented exactly as it sounds - 10 requests in any one-minute block. Here's out Azure API Management policy:

In other words, we've "unsmoothed" it. You can hammer the service 10 times in quick succession, then wait a minute, and you won't see a single HTTP 429 "Too many requests" response. Equally, if you're on a 12,000 RPM plan (and you can actually send that many requests quickly!), you won't see an unexpected 429. We can do this now because of the way we serve a huge amount of content from Cloudflare's edge, unburdening the underlying infrastructure from sudden spikes.

It's a little thing, but it'll solve a lot of unnecessary frustration for a bunch of people, including us. That's implemented across every single plan, too, so everyone benefits.

We Just Wanna Go (Even) Fast(er)

Here's our challenge today: how do we enable millions of people a day to search through billions of records with near instantaneous results... and do it affordably? They're somewhat competing objectives, but every now and then, we find this one neat trick that dramatically improves things. About 18 months ago, I wrote about how we were Hyperscaling HIBP with Cloudflare Workers and Caching. The basic premise is that, as people search the service, we build a cache in Cloudflare's 300+ edge nodes that includes the entire hash range just searched for (see the k-anon section above). We flush that out on every new breach load and as it builds back up to the full 16^6 possible cachable hash ranges, our origin load approaches zero and everything gets served from the edge. Almost, because we have the following problem I described in the post:

However, the second two models (the public and enterprise APIs) have the added burden of validating the API key against Azure API Management (APIM), and the only place that exists is in the West US origin service. What this means for those endpoints is that before we can return search results from a location that may be just a short jet ski ride away, we need to go all the way to the other side of the world to validate the key and ensure the request is within the rate limit.

Or at least we had that problem, which we've just solved with a simple fix. The quoted problem stemmed from the fact that, to ensure everyone adhered to the rate limit, we performed the APIM check before returning any data. That meant always waiting for packets to make a round trip to America, even when the data was cached nearby. But what we realised is that adhering to the rate limit can be eventually enforced; it really doesn't matter too much if a request or two in excess of the rate limit slips through, then we enforce it. The reason why that epiphany is important is that with that in mind, we can start returning data to the client immediately whilst doing the APIM check asynchronously. If the request exceeds the rate limit, Cloudflare will block subsequent requests until the client starts making requests within their limit. So, the rate limit check is no longer a blocking call; it's a background process that doesn't delay us returning results.

What that means is a dramatic reduction in the time til first byte:

That's almost a 40% reduction in wait time! It's an awesome example of how continuous investment in the way we run this thing yields tangible results that make a meaningful difference to the value people get from the service.

Passkeys!

Just one more thing...

This is all new, all free and all available to everyone, whether they have a paid subscription or not. Remember when I got phished last year? I sure do, and I vowed to use that experience to maximise the adoption of passkeys wherever possible. So, putting my money (and time) where my mouth is, we've now launched passkeys as an alternate means of signing into your dashboard:

This saves you needing a "magic" link via email on every sign-in, and whilst it doesn't constitute 2FA (the passkey becomes a single factor used to sign in), it massively streamlines how you access the dashboard. And because we never used passwords for access in the first place, the only account-takeover risk our customers face is someone gaining access to either their email account or to where they store their passkeys (in either case, they have much bigger problems!).

Here's how it works: start by signing into your dashboard, then heading over to the "Passkeys" section on the left of the screen and adding a new one:

The name is so you can keep track of which passkey you save where. I save most of mine in 1Password, but you can also save them on a physical U2F key or in your browser, for example. Clicking "Continue" will cause your browser to prompt you for the location where you'd like to store it and again, that's 1Password for me:

And that's it - we're done!

So, how does it work? Check this out, and don't blink or you'll miss it:

Compared to typing in your email address, hitting the "Sign In" button, flicking over to the mailbox, waiting for the mail to arrive, then clicking the link, we're down from let's call it 30 seconds to about 3 seconds. Nice 😎

Even though there isn't much security benefit to doing this on HIBP (you can still sign in via email, too), we wanted to build this as an example of just how easy it is. It took Stefán about an hour to build a first cut of this (with support from Copilot), and, aside from the dev time, building passkey support into your website is totally free. There are no external services you need to pay for, no hardware to buy or special crypto concepts to grasp. Passkeys are dead simple, and web developers with even a passing interest in security and usability should be adding support for them right now. We also wanted to make sure they were freely available to anyone, regardless of whether you have a paid subscription, because security like this should be the baseline, not a paid extra. So, go and give them a go in HIBP now.

And just in case you want to really geek out on how passkeys work, Stefán presented this at NDC Security in Oslo earlier this month:

All the Plans and Future Changes for Existing Subscribers

It's easiest just to see the whole overview all in one image (or jump over to the pricing page on the website), and it largely reflects everything described above:

One immediate difference to how we've previously represented the plans is that the annual price is now shown as a monthly figure. It turns out that the vast majority of our subscribers choose annual billing, so leading with the per-month pricing puts the least relevant figures front and centre. As we looked around at other services, that was a pretty consistent trend, especially when one annual subscription is more cost-effective than renewing a monthly one 12 times (annual is roughly 10x a year's worth of month-by-month payments).

Another change is that we're going to cap the number of larger domains (those with over 10 breached addresses) that can be searched on each subscription. Let me explain why: Every time we load a data breach, each record in the breach is checked against each domain being monitored. In 2025, we added 2.9 billion breached records, and we have 400k monitored domains. Multiply those out, and we're looking at 1.16 quadrillion checks for our subscribers each year. This is all handled by SQL queries, so it's not like we're getting hit with human overhead at scale, but we're getting hit hard with SQL costs. Across everything we pay to run this service (storage, app hosting, functions, API management, App Insights, bandwidth, etc.), the SQL bill is more than the total for all other services combined. In addition to how we currently calculate plan size based on breached email count, we're adding a cap on the number of domains per plan.

Only domains with more than 10 breached addresses are included in the cap.

The “10” threshold aligns with the existing requirement for a domain to need a subscription at all, and means this change impacts only a single-digit percentage of subscribers. It also helps filter out noise so the cap reflects domains that actually matter. For those larger domains beyond the cap, all current alerts will continue to work just fine until they run a search. At that time, they'll have the option to upgrade the plan or reduce the number of domains. But none of that affects existing subscribers now:

There will be no changes to existing plans until at least August 2 this year.

We do an annual price revision each August, and that's already factored into the table above. That applies to any new subscriptions immediately, but it won't touch existing ones until August 2 at the earliest. The revised pricing only kicks in on the next subscription renewal after that date, so it could be as late as August 2027 if you're an existing subscriber. The same goes for the cap on the number of domains being monitored - there's no impact on existing subscribers until at least August. That leaves plenty of time to cancel, downgrade, upgrade, or just do nothing, and the plan will automatically roll over to the new one. We'll be emailing everyone in the coming days with details of precisely what will change.

Note: if you had an old Pwned 5 subscription for the sake of stealer log access, we'll be rolling all those folks over to Pro 1 and applying a permanent discount code to ensure there's no change in price by moving to the higher plan (it'll actually drop slightly). That'll be explained in the upcoming email, it just made more sense to keep stealer logs in Pro and move people over, and this'll just give them free access to all the new stuff too.

Speaking of which, the thing that (almost) nobody reads but everyone is subject to has been revised to reflect the changes described above - the Terms of Use. For the first time, we've also summarised all the changes and linked through to an archive of the old ones, so if you really love digging through a long document prepared by lawyers, this should make you happy 😊

We're Still Doing Credit Cards via Stripe

While I'm here, just a quick comment on our ongoing Stripe dependency and, as a result, the necessity to pay for public services via credit card. I've written before about some of the challenges we've faced with customers' requests to pay by other means and how, push comes to shove, they (almost) always find a way around internal barriers. Let me share a recent empirical anecdote about this:

Just the other day, I had a call with a Fortune 500 company that was initially interested in our enterprise services. As the discussion unfolded, it became evident that the public services would more than suffice and that the enterprise route was too burdensome for their particular use case. Be that as it may, the procurement lady on the call was adamant that payment by credit card was impossible, even going to the extent of making a pretty bold statement:

No Fortune 500 company is going to pay for services like this via credit card!

O RLY? If only I had the data to check that claim... 😊 Based on a list of their domains, 132 unique Fortune 500 companies have paid for our services by credit card. The real number will be higher because many more of their domains are not on that list, or purchases have been made via an email address not on the corporate domain. Let's call it somewhere between a quarter and a third of the Fortune 500 who've puschased direct via the world's most common payment method. In other words, a significantly different number from the "zero" claim.

I've dropped the hard facts here out of both frustration from our dealings with unnecessarily artificial barriers and in support of the folks out there who, just like me in my corporate days, had to deal with "Neville" in procurement. Per that linked blog post, push back against "corporate policy" prohibiting payment by card, and statistically, you'll likely find you're not the 1 in 160 who can't make a simple payment.

Summary

We're continuing to massively invest in expanding HIBP in every way we can find. Nearly 3 billion additional breached records last year, hundreds of billions of free Pwned Passwords queries during that time, a bunch of new tweaks and features everyone gets access to and, of course, all the new stuff we've rolled into the higher plans. These new features are the culmination of a huge volume of work dating back to November, when I took this pic of our little team during our planning meeting together in Oslo.

We all hope it helps people use our Have I Been Pwned services to do more good after bad things happen.

Remember the Ashley Madison data breach? That was now more than a decade ago, yet it arguably remains the single most noteworthy data breach of all time. There are many reasons for this accolade, but chief among them is that by virtue of the site being expressly designed to facilitate extramarital affairs, there was massive social stigma attached to it. As a result, we saw some pretty crazy stuff:

1. Various websites were stood up to publicly disclose the presence of people in the data and out them as “cheaters”
2. Churches trawled through the data and contacted the spouses of exposed parishioners
3. The media outed noteworthy individuals they searched for in the breach
4. A radio station back home in Australia encouraged listeners to dial in to check if their spouse was in the data

Arguably, we now live in a more privacy-conscious era, one full of acronyms such as GDPR and CCPA, among others, in different parts of the world. The right to be forgotten, the right to erasure, and, indeed, privacy as a fundamental human right feature very differently in 2026 than they did in 2015. But arguably, even back then, the impact of outing someone as a member of the site should have been obvious. It was certainly obvious to me, which is why I introduced the concept of a sensitive data breach before the data even went public. HIBP wouldn’t show results for this breach publicly because I was concerned about the impact on people being outed. My worst fear was a spouse coming home to find someone having taken their own life, an HIBP search result on the screen in front of their lifeless body.

People died as a result of the breach. Marriages ended and lives were turned upside down. People lost their jobs. The human toll of the breach was profound. The decision I made after witnessing this was that if a breach was likely to have serious personal or social consequences for people in there, it would be flagged as sensitive and not publicly searchable.

The public doxing of members of the service was often justified on a moral basis: “adultery is bad, they deserve to be outed”. But there are two massive problems with this attitude, and I’ll begin with the purpose for which accounts were sometimes made:

An email address appearing in that breach implied that the person was there to have an extramarital affair because that was literally the catch-phrase of the service: “Life is short, have an affair”. But the reality was that people were members of the service for many, many different reasons. Have a read of my post titled Here’s What Ashley Madison Members Have Told Me and you’ll begin to understand how much more nuanced the situation was:

1. Single people had joined the service, and later married before the breach occurred
2. People who were worried about a cheating spouse joined the service in order to try to catch them
3. Accounts were made with some people’s names and email addresses without their consent (there are many “Barrack Obamas” in the data)

So, should everyone with an email address on Ashley Madison be considered an adulterer? Clearly, no, that completely misses the nuances of what an email address in a data breach really means. But what about the people who were there to have an affair? Well, that brings us to the second problem:

Our own personal belief systems are not a valid basis for outing people publicly because their belief systems differ. I used more generic terms than “extramarital affair” or “cheating” because there are many other data breaches that are flagged as sensitive in HIBP for the very same reason. Fur Affinity, for example: there is a social stigma around furries and outing someone as a member of that community could have negative consequences for them. Rosebutt Board is another example: anal fisting is evidently something a bunch of people are into, and equally, I’m sure there are many who take a moral objection to it. And finally, to get to the catalyst for this post, WhiteDate: the website that is ostensibly designed for white people to date other white people. Flagging that as sensitive resulted in some unsavoury commentary being directed at me:

U are a Nazi end of story

— 𝔗𝔥𝔢ℑ𝔡𝔦𝔬𝔱 (@fuckelonsob) January 6, 2026

Now, I emphasised “ostensibly” because the more you dig into this breach, the more you find tones of white supremacy and other behaviours that definitely don’t align with my personal value system. That societal view doesn’t sit well with me, and I think I’m safe in saying it wouldn’t sit well with most people. Would someone being outed as a member of that service be likely to result in “serious personal or social consequences”? Yes, and you can see that in the messaging from the same account:

Context matters. U are literally shielding Nazi hate mongering scoundrels. We can't doxx white supremacists?

If ISIS had a dating site & it got breached, would you protect it out of fear of doxxing? No.

Every database leaked is sensitive in a way.

— 𝔗𝔥𝔢ℑ𝔡𝔦𝔬𝔱 (@fuckelonsob) January 6, 2026

This behaviour is precisely what I don’t want HIBP being used for: as a weapon to attack people solely on the basis of their email address being affiliated with a website that has had a data breach.

Imagine, for a moment, if ISIS did have a dating site and it was breached, should it be flagged as sensitive? Contrary to the comment about "every database leaked is sensitive", there is a clear legal definition for sensitive personal information and it includes:

personal data revealing racial or ethnic origin, political opinions, religious or philosophical beliefs;

trade-union membership;

genetic data, biometric data processed solely to identify a human being;

health-related data;

data concerning a person’s sex life or sexual orientation.

An ISIS dating website breach would tick many of the boxes above and would therefore constitute a sensitive data breach. That's not an endorsement of what they stand for; it's simply a data-processing decision. But there may be a nuance in there which I didn't see present in the WhiteDate data - what if it contained illegal activity? (Sidenote: for the most part, HIBP is used by people in Western Europe, North America and Australasia, so when I say "illegal", I'm looking at it through that lens. Clearly, there are parts of the world where our "illegal" is their "normal", which further complicates how I run a service accessible from every corner of the world.) I had another example recently that went well beyond moral contention and deep into the realm of illegality:

New sensitive breach: "AI girlfriend" site Muah[.]ai had 1.9M email addresses breached last month. Data included AI prompts describing desired images, many sexual in nature and many describing child exploitation. 24% were already in @haveibeenpwned. More: https://t.co/NTXeQZFr2x

— Have I Been Pwned (@haveibeenpwned) October 8, 2024

Of all the different things people can disagree on when it comes to our moral compasses, paedophilia is where we unanimously draw the line. But I still flagged it as sensitive because of the reasons outlined above. Many people using the service were just lonely guys trying to create an AI girlfriend with no prompts around age. There would be email addresses in there that weren’t entered by the rightful owner. And then, there are cases like this:

That's a firstname.lastname Gmail address. Drop it into Outlook and it automatically matches the owner. It has his name, his job title, the company he works for and his professional photo, all matched to that AI prompt. pic.twitter.com/wpXQMBLf3B

— Troy Hunt (@troyhunt) October 9, 2024

I sat there with my wife, looking at the LinkedIn profile that used the same email address as the person who posted that comment. We looked at his photo and at the veneer of professionalism that surrounded him on that site, knowing what he had written in that prompt above. It was repulsive. Further, beyond being solely an affront to our morals, it was clearly illegal. So, I had many conversations with law enforcement agencies around the world and ensured they had access to the data. Involving law enforcement where data sets contain illegal activity is absolutely the right approach here, but equally, not being the vehicle for implying someone’s affiliation or beliefs and doxing them publicly without due process is also absolutely the right approach.

I understand the gut reaction that flagging a breach like WhiteDate as sensitive protects people whom most of us do not like. But a dozen years of running this service have caused me to consider individual privacy and rights literally hundreds of times, and these conclusions aren’t arrived at hastily. Imagine for a moment, the possible ramifications for HIBP if the service were used to publicly shame someone as a "Nazi" and that, in turn, had serious real-world consequences for them. Whether that implication was right or not, there are potentially serious ramifications for us that could well leave us unable to operate at all. And, as the Ashley Madison examples show, there are also potentially life-threatening outcomes for individuals.

I don't particularly care about one random, anonymous X account making poorly thought-out statements, but the same sentiment has been expressed after loading previous similar breaches, and it deserves a blog post. Equally, I've written before about why all the other data breaches are publicly searchable and again, that conclusion is not arrived at lightly.

I’ll finish with a note about privacy that relates to my earlier comment about it being a human right. It's literally a human right under Article 12 of the Universal Declaration of Human Rights:

No one shall be subjected to arbitrary interference with his privacy, family, home or correspondence, nor to attacks upon his honour and reputation. Everyone has the right to the protection of the law against such interference or attacks.

Breaches with legally defined sensitive data will continue to be flagged as sensitive, and breaches with illegal data will continue to be forwarded to law enforcement agencies.

The sheer scope of cybercrime can be hard to fathom, even when you live and breathe it every day. It's not just the volume of data, but also the extent to which it replicates across criminal actors seeking to abuse it for their own gain, and to our detriment.

We were reminded of this recently when the FBI reached out and asked if they could send us 630 million more passwords. For the last four years, they've been sending over passwords found during the course of their investigations in the hope that we can help organisations block them from future use. Back then, we were supporting 1.26 billion searches of the service each month. Now, it's... more:

Just as it's hard to wrap your head around the scale of cybercrime, I find it hard to grasp that number fully. On average, that service is hit nearly 7 thousand times per second, and at peak, it's many times more than that. Every one of those requests is a chance to stop an account takeover. But the real scale goes well beyond the API itself. Because the data model is open source and freely available, many organisations use the Pwned Passwords Downloader to take the entire corpus offline and query it directly within their own applications. That tool alone calls the API around a million times during download, but the resulting data is then queried… well, who knows how many times after that. Pretty cool, right?

This latest corpus of data came to us as a result of the FBI seizing multiple devices belonging to a suspect. The data appeared to have originated from both the open web and Tor-based marketplaces, Telegram channels and infostealer malware families. We hadn't seen about 7.4% of them in HIBP before, which might sound small, but that's 46 million vulnerable passwords we weren't giving people using the service the opportunity to block. So, we've added those and bumped the prevalence count on the other 584 million we already had.

We're thrilled to be able to provide this service to the community for free and want to also quickly thank Cloudflare for their support in providing us with the infrastructure to make this possible. Thanks to their edge caching tech, all those passwords are queryable from a location just a handful of milliseconds away from wherever you are on the globe.

If you're hitting the API, then all the data is already searchable for you. If you're downloading it all offline, go and grab the latest data now. Either way, go forth and put it to good use and help make a cybercriminal's day just that much harder 😊

Normally, when someone sends feedback like this, I ignore it, but it happens often enough that it deserves an explainer, because the answer is really, really simple. So simple, in fact, that it should be evident to the likes of Bruce, who decided his misunderstanding deserved a 1-star Trustpilot review yesterday:

Now, frankly, Trustpilot is a pretty questionable source of real-world, quality reviews anyway, but the same feedback has come through other channels enough times that let's just sort this out once and for all. It all begins with one simple question:

What is an Email Address?

You think you know - and Bruce thinks he knows - but you might both be wrong. To explain the answer to the question, we need to start with how HIBP ingests data, and that really is pretty simple: someone sends us a breach (which is typically just text files of data), and we run the open source Email Address Extractor tool over it, which then dumps all the unique addresses into a file. That file is then uploaded into the system, where the addresses are then searchable.

The logic for how we extract addresses is all in that Github repository, but in simple terms, it boils down to this:

1. There must be an @ symbol
2. There can be up to 64 characters before it (the alias)
3. There can be up to 255 characters after it (the domain)
4. The domain must contain a period
5. The domain must also have a valid TLD
6. A few other little criteria that are all documented in the public repo

That is all! We can't then tell if there's an actual mailbox behind the address, as that would require massive per-address processing, for example, sending an email to each one and seeing if it bounces. Can you imagine doing that 7 billion times?! That's the number of unique addresses in HIBP, and clearly, it's impossible. So, that means all the following were parsed as being valid and loaded into HIBP (deep links to the search result):

1. test@example.com
2. _test@google.com
3. fuckingwasteoftime@foo.com

I particularly like that last one, as it feels like a sentiment Bruce would express. It's also a great example as it's clearly not "real"; the alias is a bit of a giveaway, as is the domain ("foo" is commonly used as a placeholder, similar to how we might also use "bar", or combine them as "foo bar"). But if you follow the link and see the breach it was exposed in, you'll see a very familiar name:

Which brings us to the next question:

How Do "Fake" Email Addresses End up in Real Websites?

This is also going to seem profoundly simple when you see it. Here goes:

Any questions, Bruce? This is just as easily explainable as why we considered it a valid address and ingested it into HIBP: the email address has a valid structure. That is all. That's how it got into Adobe, and that's how it then flowed through into HIBP.

Ah, but shouldn't Adobe verify the address? I mean, shouldn't they send an email to the address along the lines of "Hey, are you sure you want to sign up for this service?" Yes, they should, but here's the kicker: that doesn't stop the email address from being added to their database in the first place! The way this normally works (and this is what we do with HIBP when you sign up for the free notification service) is you enter the email address, the system generates a random token, and then the two are saved together in the database. A link with the token is then emailed to the address and used to verify the user if they then follow that link. And if they don't follow that link? We delete the email address if it hasn't been verified within a few days, but evidently, Adobe doesn't. Most services don't, so here we are.

How Can I Be Really Sure Actual Fake Addresses Aren't in HIBP?

This is also going to seem profoundly obvious, but genuinely random email addresses (not "thisisfuckinguseless@") won't show up in HIBP. Want to test the theory? Try 1Password's generator (yes, Bruce, they also sponsor HIBP):

Now, whack that on the foo.com domain and do a search:

Huh, would you look at that? And you can keep doing that over and over again. You’ll get the same result because they are fabricated addresses that no one else has created or entered into a website that was subsequently breached, ipso facto proving they cannot appear in the dataset.

Conclusion

Today is HIBP's 12th birthday, and I've taken particular issue with Bruce's review because it calls into question the integrity with which I run this service. This is now the 218th blog post I've written about HIBP, and over the last dozen years, I've detailed everything from the architecture to the ethical considerations to how I verify breaches. It's hard to imagine being any more transparent about how this service runs, and per the above, it's very simple to disprove the Bruces of the world. If you've read this far and have an accurate, fact-based review you'd like to leave, that'd be awesome 😊

I hate hyperbolic news headlines about data breaches, but for the "2 Billion Email Addresses" headline to be hyperbolic, it'd need to be exaggerated or overstated - and it isn't. It's rounded up from the more precise number of 1,957,476,021 unique email addresses, but other than that, it's exactly what it sounds like. Oh - and 1.3 billion unique passwords, 625 million of which we'd never seen before either. It's the most extensive corpus of data we've ever processed, by a significant margin.

Edit: Just to be crystal clear about the origin of the data and the role of Synthient (who you’ll read about in the next paragraph): this data came from numerous locations where cybercriminals had published it. Synthient (run by Ben during his final year of college) indexed that data and provided it to Have I Been Pwned solely for the purpose of notifying victims. He’s the good guy shining a light on the bad guys, so keep that in mind as you read on. (Some of the feedback Ben has received is exactly what I foreshadowed in the final paragraph of this post.)

A couple of weeks ago, I wrote about the 183M unique email addresses that Synthient had indexed in their threat intelligence platform and then shared with us. I explained that this was only part of the corpus of data they'd indexed, and that it didn't include the credential stuffing records. Stealer log data is obtained by malware running on infected machines. In contrast, credential stuffing lists usually originate from other data breaches where email addresses and passwords are exposed. They're then bundled up, sold, redistributed, and ultimately used to log in to victims' accounts. Not just the accounts they were initially breached from, either, because people reuse the same password over and over again, the data from one breach is frequently usable on completely unrelated sites. A breach of a forum to comment on cats often exposes data that can then be used to log in to the victim's shopping, social media and even email accounts. In that regard, credential stuffing data becomes "the keys to the castle".

Let me run through how we verified the data, what you can do about it and for the tech folks, some of the hoops we had to jump through to make processing this volume of data possible.

Data Verification

The first person whose data I verified was easy - me 😔 An old email address I've had since the 90s has been in credential stuffing lists before, so it wasn't too much of a surprise. Furthermore, I found a password associated with my address, which I'd definitely used many eons ago, and it was about as terrible as you'd expect from that era. However, none of the other passwords associated with my address were familiar. They certainly looked like passwords that other people might have feasibly used, but I'm pretty sure they weren't mine. One was even just an IP address from Perth on the other side of the country, which is both infeasible as a password I would have used, yet eerily close to home. I mean, of all the places in the world an IP address could have appeared from, it had to be somewhere in my own country I've been many times before...

Moving on to HIBP subscribers, I reached out to a handful and asked for support verifying the data. I chose a mix of subscribers with many who'd never been involved in any data breach we'd ever seen before; my experience above suggested that there's recycled data in there, and we had previously verified that when investigating those other incidents. However, is the all-new stuff legitimate? The very first response I received was exactly what I was looking for:

#1 is an old password that I don't use anymore. #2 is a more recent password. Thanks for the heads up, I've gone and changed the password for every critical account that used either one. 

Perfectly illustrating most people's behaviour with passwords, #2 referred to above was just #1 with two exclamation marks at the end!! (Incidentally, these were simple six and eight-character passwords, and neither of them was in Pwned Passwords either.) He had three passwords in total, which also means one of them, like with my data, was not familiar. However, the most important thing here is that this example perfectly illustrates why we put the effort into processing data like this: #2 was a real, live password that this guy was actively using, and it was sitting right next to his email address, being passed around among criminals. However, through this effort, that credential pair has now become useless, which is precisely what we're aiming for with this exercise, just a couple of billion times over.

The second respondent only had one password against their address:

Yes that was a password I used for many years for what I would call throw away or unimportant accounts between 20 and 10 years ago

That was also only eight characters, but this time, we'd seen it in Pwned Passwords many times before. And the observation about the password's age was consistent with my own records, so there's definitely some pretty old data in there.

The following response was not at all surprising:

I am familiar with that password... I used it almost 10 years ago... and cannot recall the last time I used it.

That was on a corporate account, too, and the owner of the address duly forwarded my email to the cybersecurity team for further investigation. The single password associated with this lady's email address had a massive nine characters, and also hadn't previously appeared in Pwned Passwords.

Next up was a respondent who replied inline to my questions, so I'll list them below with the corresponding answers:

Is this familiar? Yes  

Have you ever used it in the past? Yes and is still on some accounts I do not use any longer.

And if so, how long ago? Unfortunately, it is still on some active accounts that I have just made a list of to change or close immediately.

This individual's eight-character password with uppercase, lowercase, numbers and a "special" character also wasn't in Pwned Passwords. Similarly, as with the earlier response, that password was still in active use, posing a real risk to the owner. It would pass most password complexity criteria and slip through any service using Pwned Passwords to block bad ones, so again, this highlights why it was so important for us to process the data.

The next person had three different passwords against rows with their email address, and they came back with a now common response:

Yes, these are familiar, last used 10 years ago

We'd actually seen all three of them in Pwned Passwords before, many times each. Another respondent with precisely the kind of gamer-like passwords you'd expect a kid to use (one of which we hadn't seen before), also confirmed (I think?) their use:

maybe when i was a kid lol

Responses that weren't an emphatic "yes, that's my data" were scarce. The two passwords against one person's name were both in Pwned Passwords (albeit only once each), yet it's entirely possible that neither of them had been used by this specific individual before. It's also possible they'd forgotten a password they'd used more than a decade ago, or it may have even been automatically assigned to them by the service that was subsequently breached. Put it down as a statistical anomaly, but I thought it was worth mentioning to highlight that being in this data set isn't a guarantee of a genuine password of yours being exposed. If your email address is found in this corpus then that's real, of course, so there must be some truth in the data, but it's a reminder that when data is aggregated from so many different sources over such a long period of time, there's going to be some inconsistencies.

Searching Pwned Passwords

As a brief recap, we load passwords into the service we call Pwned Passwords. When we do so, there is absolutely no association between the password and the email address it appeared next to. This is for both your protection and ours; can you imagine if HIBP was pwned? It's not beyond the realm of possibility, and the impact of exposing billions of credential pairs that can immediately unlock an untold number of accounts would be catastrophic. It's highly risky, and completely unnecessary when you can search for standalone passwords anyway without creating the risk of it being linked back to someone.

Think about it: if you have a password of "Fido123!" and you find it's been previously exposed (which it has), it doesn't matter if it was exposed against your email address or someone else's; it's still a bad password because it's named after your dog followed by a very predictable pattern. If you have a genuinely strong password and it's in Pwned Passwords, then you can walk away with some confidence that it really was yours. Either way, you shouldn't ever use that password again anywhere, and Pwned Passwords has done its job.

Checking the service is easy, anonymous and depending on your level of technical comfort, can be done in several different ways. Here's a copy and paste from the last Synthient blog post:

1. Use the Pwned Passwords search page. Passwords are protected with an anonymity model, so we never see them (it's processed in the browser itself), but if you're wary, just check old ones you may suspect.
2. Use the k-anonymity API. This is what drives the page in the previous point, and if you're handy with writing code, this is an easy approach and gives you complete confidence in the anonymity aspect.
3. Use 1Password's Watchtower. The password manager has a built-in checker that uses the abovementioned API and can check all the passwords in your vault. (Disclosure: 1Password is a regular sponsor of this blog, and has product placement on HIBP.)

My vested interest in 1Password aside, Watchtower is the easiest, fastest way to understand your potential exposure in this incident. And in case you're wondering why I have so many vulnerable and reused passwords, it's a combination of the test accounts I've saved over the years and the 4-digit PINs some services force you to use. Would you believe that every single 4-digit number ever has been pwned?! (If you're interested, the ABC has a fantastic infographic using a heatmap based on HIBP data that shows some very predictable patterns for 4-digit PINs.)

This Is Not a Gmail Breach

It pains me to say it, but I have to, given the way the stealer logs made ridiculous, completely false headlines a couple of weeks ago:

This story has suddenly gained *way* more traction in recent hours, and something I thought was obvious needs clarifying: this *is not* a Gmail leak, it simply has the credentials of victims infected with malware, and Gmail is the dominant email provider: https://t.co/S75hF4T1es

— Troy Hunt (@troyhunt) October 27, 2025

There are 32 million different email domains in this latest corpus, of which gmail.com is one. It is, of course, the largest and has 394 million unique email addresses on it. In other words, 80% of the data in this corpus has absolutely nothing to do with Gmail, and the 20% of Gmail addresses have absolutely nothing to do with any sort of security vulnerability on Google's behalf. There - now let reporting sanity prevail!

The Technical Bits

I wanted to add this just to highlight how painful it has been to deal with this data. This corpus is nearly 3 times the size of the previous largest breach we'd loaded, and HIBP is many times larger than it was in 2019 when we loaded the Collection #1 data. Taking 2 billion records and adding the ones we hadn't already seen in the existing 15 billion corpus, whilst not adversely impacting the live system serving millions of visitors a day, was very non-trivial. Managing the nuances of SQL Server indexes such that we could optimise both inserts and queries is not my idea of fun, and it's been a pretty hard couple of weeks if I'm honest. It's also been a very expensive period as we turned the cloud up to 11 (we run on Azure SQL Hyperscale, which we maxed out at 80 cores for almost two weeks).

A simple example of the challenge is that after loading all the email addresses up into a staging table, we needed to create SHA1 hashes of each. Normally, that would involve something to the effect of "update table set column = sha1(email)" and you're done. That crashed completely, so we ended up doing "insert into new table select email, sha1(email)". But on other occasions the breach load required us to do updates on other columns (with no hash creation), which, on mulitple occasions, we had to kill after a day or more of execution with no end in sight. So, we ended up batching in loops (usually 1M records at a time), reporting on progress along the way so we had some idea of when it would actually finish. It was a painful process of trial, waiting ages, error then taking a completely different approach.

Notifying our subscribers is another problem. We have 5.9 million of them, and 2.9 million are in this data 🫨 Simply sending that many emails at once is hard. It's not so much hard in terms of firing them off, rather it's hard in terms of not ending up on a reputation naughty list or having mail throttled by the receiving server. That's happened many times in the past when loading large, albeit much smaller corpuses; Gmail, for example, suddenly sees a massive spike and slows down the delivery to inboxes. Not such a biggy for sending breach notices, but a major problem for people trying to sign into their dashboard who can no longer receive the email with the "magic" link.

What we've done to address that for this incident is to slow down the delivery of emails for the individual breach notification. Whilst I'd originally intended to send the emails at a constant rate over the period of a week, someone listening to me on my Friday live stream had a much better suggestion:

the strategy I've found to best work with large email delivery is to look at the average number of emails you've sent over the last 30 days each time you want to ramp up, and then increase that volume by around 50% per day until you've worked your way through the queue

Which makes a lot of sense, and stacked up as I did more research (thanks Joe!). So, here's what our planned delivery schedule now looks like:

That's broken down by hour, increasing in volume by 1.015 times per hour, such that the emails are spread out in a similar, gradually increasing cadence. On a daily basis, that works out at a 45% increase in each 24-hour period, within Joe's suggested 50% threshold. Plus, we obviously have all the other mechanisms such as a dedicated IP, properly configured DKIM, DMARC and SPF, only emailing double-opted-in subscribers and spam-friendly message body construction. So, it could be days before you receive a notification, or just run a haveibeenpwned.com search on demand if you're impatient.

We've sent all the domain notification emails instantly because, by definition, they're going to a very wide range of different mail servers; it's just the individual ones we're drop-feeding.

Lastly, if you've integrated Pwned Passwords into your service, you'll now see noticeably larger response sizes. The numbers I mentioned in the opening paragraph increase the size of each hash range by an average of about 50%, which will push responses from about 26kb to 40kb. That's when brotli compressed, so obviously, make sure you're making requests that make the most of the compression.

Conclusion

This data is now searchable in HIBP as the Synthient Credential Stuffing Threat Data. It's an entirely separate corpus from that previous Synthient data I mentioned earlier; they're discrete datasets with some crossover, but obviously, this one is significantly larger. And, of course, all the passwords are now searchable per the Pwned Passwords guidance above.

If I could close with one request: this was an extremely laborious, time-consuming and expensive exercise for us to complete. We've done our best to verify the integrity of the data and make it searchable in a practical way while remaining as privacy-centric as possible. Sending as many notifications as we have will inevitably lead to a barrage of responses from people wanting access to complete rows of data, grilling us on precisely where it was obtained from or, believe it or not, outright abusing us. Not doing those things would be awesome, and I suggest instead putting the energy into getting a password manager, making passwords strong and unique (or even better, using passkeys where available), and turning on multi-factor auth. That would be an awesome outcome for all 😊

Edit: I've closed off comments on this blog post. As you'll see below, there was a constant stream of questions that have already been answered in the post itself, plus some comments that were starting to verge on precisely what I predicted in the last para above. Reading, responding and engaging is time-consuming and at this point, all the answers are already here both above and below this edit in the comments.