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This is the technical companion to our update on Distilled, “Keeping the web open and private in the bot era.” Here we take a deeper look at the problem space, the design we’re proposing, and the problems still left to solve.

Bots (and privacy-preserving browsers) not welcome

Browse a news site in a private window. Shop at a major retailer with a VPN. Visit a video streaming platform with anti-fingerprinting defenses tuned up. You’ll see the same responses: registration walls, block pages, and endless CAPTCHAs. The message is clear: if we think you might be a bot, you’re not welcome.

Websites have valid reasons for wanting to block bots. Bots enable volumetric abuse, abuse that wouldn’t otherwise be feasible if they had to be carried out by humans.  For example: SEO comment spam, credential stuffing and DDoSing. Consequently many sites employ dedicated anti-abuse tooling which aims to keep the bots out whilst minimizing friction for human visitors.

Unfortunately, that tooling is increasingly failing at both tasks. Browser privacy protections are dismantling the passive signals that anti-abuse systems depended on to identify and distinguish visitors. Meanwhile advances in generative AI have rendered CAPTCHAs ineffective: bots now solve them faster and more reliably than humans.

Many sites are switching to more invasive mechanisms and now ask visitors to disclose identifying information, e.g. an email address, a federated login or disabling their VPN. This means greater friction for users, since providing these details on a first visit takes time. It also compromises their privacy, since these details enable the same kinds of cross-site tracking that browser privacy protections were intended to mitigate.

This leaves users with a dilemma. The more effectively they protect their privacy, the harder it is for websites to distinguish them from bots and the worse the treatment they receive. Website operators are also suffering. The additional friction they inflict upon well-behaved visitors harms their site, but many are willing to pay the costs if it mitigates volumetric abuse.

Browser-based AI agents make this tension more acute. Sites may want to allow agents which are acting on behalf of individual users while blocking agents engaged in volumetric abuse. However, with no effective mechanisms to distinguish the two, websites are opting to block both. That hurts users, who should be free to choose the user agent they use to access the web; it hurts new browsers and agents, which struggle to interoperate; and it hurts sites, which lose legitimate visitors.

The consequence is that the web gets worse for everyone. Users get more friction or less privacy or both. Website operators see more volumetric abuse and the friction they add drives away users who would otherwise want to consume their content or services. New user agents struggle to access the same content as conventional browsers.

The Costs of Convenient Solutions

Some large ecosystem players have put forward solutions that leverage their control of the dominant operating systems and their deep integration with consumer hardware. These rely on device attestation: identifiers and privileged code baked into devices at the hardware level, which let manufacturers prove what software is running on a user’s device. Exposing this functionality to the web means attesting to sites that the user is running approved software with trusted hardware and therefore isn’t a bot. There have been two substantive proposals.

Google’s Web Environment Integrity, abandoned in 2023, was the blunt version. It attested to the user agent itself, as well as the operating system and device in use. Users would have lost control in two ways: once to the attester, which would decide which operating systems and devices could be blessed, and again to the website, which would decide which software to accept. If sites had adopted allow-lists of approved user agents, building a new browser would have become virtually impossible, and sites could have withdrawn access from any user agent they chose.

Apple’s Private Access Tokens, deployed across their ecosystem in 2022, have more subtle issues. Built on the Privacy Pass protocol standardized at the IETF, they get a lot right: a user receives a renewed, limited batch of one-time tokens that can be presented to websites without linking their visits together. This provides privacy for users and has shown rate limits to be an effective tool for sites – both points we’ll return to later in this post.

However, Private Access Tokens rely on device attestation, requiring that the hardware manufacturer be in overall control of the user’s device. Presenting a PAT tells a website you are locked into Apple’s rules for what counts as acceptable software. Due to PAT’s technical design^[1], there’s no way to open the system to other sources of scarcity without compromising the system’s privacy properties, meaning that if more widely deployed, access to the web would become tied to having bought expensive hardware from a small, hard to change set of vendors.

Both approaches are ultimately hostile to users and to the openness of the web. Both are premised on parts of a user’s device that sit within the manufacturer’s control and beyond the user’s own. Were they widely deployed, the web would become just another walled garden with centralized gatekeepers controlling acceptable hardware, operating systems and software. As convenient as these solutions are for the players who already dominate the ecosystem, we think there’s a better path.

A Better Path Forward

Bots’ harms arise from their ability to operate beyond human scale. For sites to prevent volumetric abuse they don’t actually need to know the user’s identity or receive cryptographic proof that they’re running approved software. If sites knew their visitors were restricted to a rate limit set by a site, that would be enough.  

Rate limits only make sense if they’re tied to something scarce; something an attacker can’t cheaply replicate to evade the limit. Without anchoring to a scarce resource, like the trusted hardware used in Private Access Tokens, attackers can generate as many fresh identities as they need to bypass the rate limit.

However, hardware is just one option for scarcity. Anything a user already has that an attacker can’t trivially spin up at scale will work: email addresses and phone numbers are naturally scarce. A paid subscription costs an attacker the same as a real user.  Even maintaining an account on a free service requires some non-trivial work.

What if we could use these scarce signals across the web? We could build an open ecosystem with many parties offering scarcity signals, each site choosing which to accept. By opening up who can provide a signal, and letting sites choose which to accept, we can avoid transferring control to device manufacturers and the resulting harms.

As a concrete example of who might be well positioned to provide such a signal, we can consider VPN providers acting as a subscription service. Sites routinely block VPN users indiscriminately, whether through a deliberate policy choice or through an indirect consequence of rate limiting visitors per IP address. But a VPN subscription is a perfect source of scarcity. If the VPN provider could vouch for its users so that sites could rate limit each user individually – then users would be able to browse the web with less friction and without giving up their VPN usage.

The catch is that building a system that can enable this on the open web whilst maintaining user’s privacy is genuinely difficult. It requires that we take information from one site — that this user holds some scarce thing — and expose it to other sites so that they can use that as the basis for their rate limiting. Letting one site verify a signal from another is the sort of information flow that privacy-preserving browsers have spent the last decade locking down to prevent cross-site tracking.

Our goal would be that no more than the minimum information gets through: a single bit communicating whether the user is below the rate limit set by the site. Leaking anything more – like the source of the scarcity that the rate limit is anchored to – would be unacceptable. Enabling a new cross-site information flow might feel like compromising privacy to gain better access, but reality is more nuanced. If a new system moves sites away from demanding that visitors be identifiable (whether through fingerprinting or login forms), it can be a win for both privacy and access.

The Foundations

The good news is that the cryptographic foundations for a privacy preserving approach already exist. The Privacy Pass protocol, originally developed in 2018 to reduce the friction of Cloudflare CAPTCHAs for Tor users, introduced the core primitive: a token that is unlinkable between issuance and redemption. You prove something to an issuer (e.g. by solving a CAPTCHA), receive some tokens, and later present a token to a website. The website can verify the token is legitimate, but can’t link it to the user it was issued to.

Figure 1: In Privacy Pass, a CAPTCHA provider can issue tokens to a client which can then be used to bypass challenges for future site visits. Even if the CAPTCHA provider and sites collude, they can’t use the tokens to identify the user or their browsing history.

Privacy Pass has gone on to be successfully deployed in systems where the issuer and verifier have a prior trust relationship: Apple uses it to authenticate users of Private Cloud Compute and Private Relay without linking their activity to their identity, Chrome uses it for two-hop IP protection, and Kagi uses it to provide private search. These deployments work in part because a small number of parties have agreed in advance on who issues tokens and who accepts them.

Applying this approach to an open system where any site can act as an issuer brings real challenges. Firstly, even though tokens are unlinkable, knowing a user has access to a specific issuer is a privacy leak on its own, because you can infer that the user meets the relevant issuance criteria. If one site can learn that you have a token from another site, that reveals that you have been to that site, which can be a major privacy problem. This compounds if sites can learn the set of issuers you have visited, since it becomes a fingerprint which can be used to identify you.

Generic techniques exist for proving a statement in zero knowledge: we can prove that a client has a token from a set of acceptable issuers without revealing which specific issuer it is. We’ll call this issuer blinding. The generic approach is often slow, but bespoke approaches tailored to the underlying cryptography can improve this considerably.

Another challenge is how sites using rate limits decide who to trust to issue tokens. If an issuer misbehaves then the site’s rate limits become ineffective, enabling volumetric abuse. However, if we need to prevent the site from learning which issuers a user has access to, the site is only going to know that one of its trusted issuers was used, not which one. This makes mistakes or misbehaviour by an issuer difficult to detect, and makes it hard for sites to evaluate new issuers. Solving this challenge is essential for openness. Without adequate information, sites are likely to lean towards conservative issuer selection. That could lead to less choice between Anchors, which in turn could lead to a new form of gatekeeper being created. 

To solve this, sites at least need a way to calculate an aggregate score for each issuer they use. This should roughly correspond to how much of the traffic it considers abusive to have come from users using that particular issuer. Mozilla has long invested in systems like Prio which use multiparty computation (MPC) to protect user privacy whilst enabling aggregate measurements of system behaviour.

Privacy Pass also struggles to handle dynamic adjustments to rate limits. Once tokens have been issued, they’re difficult to invalidate without either revoking all active tokens or risking attacks which can compromise the privacy of users. It’s also beneficial if sites can adjust rate limits on a per client basis, for example by increasing rate limits where they become more confident the client is benign and withdrawing access when abuse is detected.

Anonymous Credit Tokens offer a useful building block to solve this problem. Conventional Privacy Pass schemes rely on issuing a bucket of tokens but ACT works differently by enabling the use of a credential with state. For example, an ACT credential can hold an internal counter. When the credential is presented, the site can check the counter is over some threshold and mutate it, increasing or decreasing the counter whenever the site’s perception of the holder has improved or worsened. Critically, the exact value is never leaked to the site, preventing the site from tracking the holder and ensuring successive presentations of the same credential can’t be linked.

Putting it together

So how can we combine these techniques to build a system which can enable privacy-preserving rate limiting on the open web? In May 2026, we participated in a W3C CG Meeting in collaboration with Cloudflare, Chrome and other web stakeholders in which we started sketching out a design we’re calling PACT – Private Access Control Tokens.

Rate limits need a starting point, a source of scarcity to anchor on. We’ll call an entity that provides such a source an Anchor. To a user who meets the Anchor’s criteria, like having a subscription, an account in good standing, or a verified phone number, an Anchor issues a batch of Endorsement tokens, following the Privacy Pass model. In practice, Anchors could be any website which has access to this kind of signal. An Endorsement conveys scarcity to other sites.

That’s enough for a simple system where access is either granted or denied. But as we discussed earlier, we also want the ability to increase access where a visitor behaves benignly and decrease it where they don’t. The state needed to enforce a rate limit can’t live in the Endorsement, because Endorsements cross trust boundaries between unrelated sites. We need a second object that can hold that state, scoped to the party that maintains it.

We’ll call that the party that handles rate limiting for a site a Moderator and the stateful object a Credential. A Credential is specific to a Moderator and, unlike endorsements, we limit each site to nominating a single Moderator. In the common case the site itself plays the Moderator role, so there’s no new entity or trust boundary. A Moderator can also be a third-party service shared across many sites, allowing those sites to cooperatively share a rate limit. 

In the terminology of the previous section, the Anchor is the issuer of Endorsements, and the Moderator both verifies Endorsements and issues Credentials. A Moderator manages rate-limit policy: it decides which Anchors it trusts, accepts their Endorsements, and issues a Credential in return.

Figure 2: (1) Clients acquire Endorsements from Anchors in the course of normal browsing to sites they have relationships with. (2) Clients can exchange Endorsements for a stateful Credential from a Moderator. (3) Credentials can be used to access sites which use that Moderator. Credentials can be updated over time.

Directly revealing which Anchor backed an Endorsement would leak a lot of information about the user. The issuer blinding techniques from the previous section solve this: when an Endorsement is redeemed, the Moderator only learns that it came from one of the Anchors it trusts, but not which one.

When a Moderator covers more than one site, we let Credentials be presented across all of them but partition cookies and storage as we would for any other third party site. The unlinkability of Credential presentations keeps this from creating a new cross-site identifier. The benefit is that good behaviour on one site improves access on every site the Moderator covers, and bad behaviour cuts it everywhere. Websites can already build the same capability with a shared account system, so this doesn’t create a new way to lock users out, but it does provide a new way to grant access without requiring users to give up their privacy.

Enabling Moderators that cover many sites carries a centralisation risk, similar to the concentration we see today in anti-abuse providers. The mitigation is that the choice of Moderator stays with each site, and the choice of trusted Anchors stays with each Moderator. This can’t reverse the centralisation pressure the web already faces, but it ensures this system won’t lead to additional lock-in: a new Anchor or a new Moderator can be adopted without coordinating with a dominant vendor.

The system then has three flows. First, the user receives Endorsements from an Anchor in the course of normal interaction, based on the Anchor’s positive view of the user. This is a relatively rare operation for any given user and Anchor. After all, as our source of scarcity, Endorsements should not be too easy to accumulate.

Figure 3: In the course of normal browsing, clients browse to websites they have a relationship with. These sites can act as Anchors by issuing Endorsements to clients.

Second, when the user arrives at a site that works with a Moderator, the browser spends an Endorsement from an Anchor the Moderator trusts and receives a Credential in return. The presentation hides which Anchor was used, and neither the Anchor nor the Moderator can trace the Endorsement back to where it was issued. The Moderator decides what initial balance the Credential starts with. If the user has no Endorsements from suitable Anchors at all, existing mechanisms (CAPTCHAs, account creation, federated login) could be used to bootstrap a Credential the same way, so the system degrades to today’s experience rather than locking the user out.

Figure 4: When the client browses to a site, it can prompt the client for a Credential from the Moderator it uses. If the Client doesn’t have a suitable Credential, but does have a suitable Endorsement, it can exchange it for a Credential with the Moderator. In practice, the Moderator and the Site might be the same server.  

Third, as the user browses, the browser presents the Credential and the Moderator updates the internal state of the Credential. The Moderator can reward behaviour that looks benign and penalize suspicious activity, but can’t track the use of the Credential or identify it if it’s used on other sites the Moderator covers. Revocation falls out of the same mechanism: a Moderator can refuse to return an updated Credential. 

Figure 5: The Client can present the Credential on sites which use the matching Moderator. Sites can check if the Credential is in good standing. The sites can then adjust the access the Credential has in response to behaviour. E.g. increasing it when they gain confidence in the client or reducing it in response to malicious behaviour.

In practice, all of this would happen transparently to the user through a WebAPI that sites acting as Anchors or Moderators would call from JavaScript. In an ideal ecosystem, users would accumulate Endorsements through normal browsing, just by virtue of the sites they already visit, and the rest of the flow would happen in the background as they move around the web, leaving users with meaningfully less friction.

AI agents acting on behalf of a user slot into the same flow. An agent can carry its user’s Credentials, in which case the user remains accountable for how the agent behaves. Sites would not need to grant any more access than they would to the user themselves. Alternatively, the operator of an agent can run its own Anchor and vouch for its agents the way other Anchors vouch for human users. Sites retain control over which Anchors they accept, so they can choose how to treat agent traffic without needing a separate detection mechanism.

Several mechanisms combine to keep the information about a user that flows out close to a single bit. Cryptographic unlinkability ensures successive Credential presentations cannot be tied to each other or to the original issuance, so a user’s visits cannot be joined into a history. Each site is bound to a single Moderator, so the set of Moderators a user has Credentials with never becomes a cross-site fingerprint. The Anchor-to-Credential exchange happens in an isolated browsing context, so during ordinary browsing the only thing the site or its Moderator ever observes is a Credential presentation: the site only learns if the user has a valid Credential below the rate limit, or nothing. When the Moderator updates a Credential, it adjusts the credentials state without learning what it is.

The additional privacy given to users from Issuer blinding makes participating in the system more challenging for Moderators. Because the Moderator can’t see which Anchor backed a Credential at issuance, it can’t give a Credential from a strong Anchor more access than one from a weak Anchor: doing so would itself leak which Anchor was used. The initial access has to be uniform across the Moderator’s whole pool of Anchors, which in practice means setting it at the strength of the weakest. However, this is only relevant for that initial access, the Moderator can update credentials according to the holder’s behavior, enabling Credential’s to accrue access over time.

Building an open ecosystem also requires that sites can make effective decisions about the Anchors they choose to trust. Multiparty computation systems like Prio enable aggregate scoring without compromising privacy. When users present Credentials, they can provide an encrypted share which identifies the anchor they used and can be privately aggregated to compute the quality of an issuer.

Next Steps

We think the architecture we’ve sketched for PACT has the right shape, but many of the details still need to be worked out and the entire system needs rigorous privacy and security analysis.

We want to do that work in the open. The IETF is the natural venue for the cryptographic protocols underneath, and the W3C for the WebAPI surface that sits on top. We’ll be bringing draft specifications to these bodies as soon as they’re ready, and we welcome collaborators from across the ecosystem: browser vendors, site operators, anti-abuse providers, and the cryptography community.

If successful, we think we can provide a system which will keep the web open and private, while still giving sites the rate-limiting signal they need.

Acknowledgements

The ideas described here are the result of collaboration and conversations with many people, including: Watson Ladd, Thibault Meunier, Michele Orrù, Trevor Perrin, Eric Rescorla, Samuel Schlesinger, Martin Thomson, Eric Trouton, Benjamin Vandersloot & Cathie Yun. 

The post PACT: Anonymous Credentials for the Web appeared first on Mozilla Hacks - the Web developer blog.

Support for Web Serial in Firefox 151 for Desktop

Firefox can now connect directly to microcontrollers, development boards, 3D printers, power meters, and other serial-connected hardware from the web. Starting in Firefox 151 for Desktop, support for the Web Serial API allows web applications to communicate with compatible devices without requiring native software.

Web Serial compatible devices are popular among hobbyists, hardware hackers, educators, makers, and developers with use cases ranging from home automation to hardware prototyping and 3D printing. Web Serial support makes Firefox more useful for these kinds of projects.

Here’s an example using an Adafruit ESP32-S2 based board where messages sent from web code can be directly displayed on the device over Web Serial.

We’ve collaborated with Adafruit to test Firefox’s implementation against real hardware workflows commonly used by this community. The result: Firefox is a more practical browser for programming and interacting with hardware directly using web technology.

As an example of how you can combine Web Serial with electronics, Mozilla engineer Alex Franchuk created an amazingly fun and functional device that melds electronics and web editing. Check out the Page Playground.

The list of serial compatible devices includes Espressif ESP-based boards such as the popular ESP32 chips, Raspberry Pi Picos, 3D printers, LEGO devices, and many more. There are many tools for running your own code on these small affordable microcontroller boards, and with Web Serial it’s easier than ever to connect them to a computer and interact through a web-based user interface.

What is Web Serial?

Web Serial is a web API that allows a website to read and write to serial devices using JavaScript. See the MDN documentation for the details. While modern computers don’t typically include serial ports, serial devices connected to a USB port or paired via Bluetooth can advertise themselves as serial-capable devices so they appear as serial ports in the operating system.

The Web Serial API lets developers use the web platform to communicate with these devices. For example, websites can control devices or deliver firmware without requiring native applications or installers.

Mozilla’s own Florian Quèze, who has experimented with many projects to measure power consumption, demonstrated how Web Serial could be used to read power data from an off-the-shelf USB power meter and display it in Firefox. Florian’s code can also export the data into the Firefox Profiler, making it easy to visualize and share power data. Here’s the page and GitHub repo. The screenshots below show the page in action and the data in the Firefox Profiler after recording the power usage of a light with three brightness modes.

Home Assistant is another example. It’s a popular (and growing) open source project for home automation. The ESPHome project offers Home Assistant-compatible firmware for affordable ESP32 and similar devices which can be installed and configured over Web Serial in just a few clicks.

Security and Privacy

There are clear security and privacy concerns with allowing the web platform to read and write to hardware devices. Most importantly, with Web Serial, websites do not have visibility or access to serial ports until the user explicitly allows it.

Ports are allowed on a per-site and per-port basis. The Web Serial API requires websites to call navigator.serial.requestPort(), which lets the user choose which port to allow access to, or disallow all access entirely. This means websites do not receive a list of connected devices and there is no useful fingerprinting information outside of the port the user selects.

To help users understand when and why a site requests access to a serial port, Firefox uses add-on gating which we introduced with our Web MIDI API implementation. Compared to other web permission prompts, this gives the user a more detailed explanation of what they’re allowing. The add-on gating prompts appear before the port selection prompt the first time a site requests port access.

For organizations using Firefox Enterprise Policies, Web Serial is disabled by default. Administrators can explicitly allow or disallow Web Serial functionality across their organization using the DefaultSerialGuardSetting policy setting.

Standardization

While Web Serial still resides in the Web Incubator Community Group (WICG), we’re optimistic there’s a path to standardization given its scope and long-running incubation. We are pursuing standardizing the Web Serial API in the WHATWG in a new Workstream proposal and are excited to work with ecosystem partners and standards bodies to help shape access to peripherals on the web.

Feedback

If you already have a Web Serial workflow with a device you can test on, give Firefox a try. We’d love to hear what you’re building and which workflows matter most to you. Mozilla Connect is a great place to share projects, ask questions, and give feedback.

For technical issues, browse to support.mozilla.org or file a bug here.

The post Announcing Web Serial Support in Firefox appeared first on Mozilla Hacks - the Web developer blog.

Two weeks ago we announced that we had identified and fixed an unprecedented number of latent security bugs in Firefox with the help of Claude Mythos Preview and other AI models. In this post, we’ll go into more detail about how we approached this work, what we found, and advice for other projects on making good use of emerging capabilities to harden themselves against attack.

Suddenly, the bugs are very good

Just a few months ago, AI-generated security bug reports to open source projects were mostly known for being unwanted slop. Dealing with reports that look plausibly correct but are wrong imposes an asymmetric cost on project maintainers: it’s cheap and easy to prompt an LLM to find a “problem” in code, but slow and expensive to respond to it.

It is difficult to overstate how much this dynamic changed for us over a few short months. This was due to a combination of two main factors. First, the models got a lot more capable. Second, we dramatically improved our techniques for harnessing these models — steering them, scaling them, and stacking them to generate large amounts of signal and filter out the noise.

Ordinarily we keep detailed bug reports private for several months after shipping fixes and issuing security advisories, largely as a precaution to protect any users who, for whatever reason, were slow to update to the latest version of Firefox. Given the extraordinary level of interest in this topic and the urgency of action needed throughout the software ecosystem, we’ve made the calculated decision to unhide a small sample of the reports behind the fixes we recently shipped. We’ve attempted to draw them from a range of browser subsystems, but the selection process was still somewhat arbitrary. Nevertheless, we hope that the depth and diversity of these reports lends credence to our assessment of the capabilities and our calls for defenders to begin applying these techniques:

Note that a number of these bugs are sandbox escapes, which would need to be combined with other exploits to achieve a full-chain Firefox compromise. These reports presume that the sandboxed process that renders site content has already been compromised with some separate bug, and is now running attacker-controlled machine code attempting to escalate control into the privileged parent process. When crafting a sandbox escape, the model is permitted to patch the Firefox source code, so long as the modified code is restricted to run only in the sandboxed process^[1]. Such bugs are notoriously difficult to find with fuzzing, and while we’ve had some success developing new techniques to close this gap, AI analysis provides much more comprehensive coverage of this critical surface.

Just as interesting as what the models found is what they didn’t find — not because they didn’t try, but because they were unable to circumvent Firefox’s layered defenses. For example, in recent years we received several clever reports from security researchers that managed to escape the process sandbox by triggering prototype pollution in the privileged parent process. Rather than fixing these problems one-by-one, we made an architectural change to freeze these prototypes by default. While auditing logs from the harness, we saw many attempts to pursue this line of escape that were thwarted by this design. Observing such direct payoff from previous hardening work was even more rewarding than finding and fixing more bugs.

Harnessing Models to Build a Hardening Pipeline

We’ve experimented internally with LLM code audits over the past few years, with early attempts using models like GPT 4 or Sonnet 3.5 to statically analyze high risk code for vulnerabilities. These experiments showed some promise, but the high rate of false positives made them impractical to scale.

The introduction of agentic harnesses that can reliably detect security issues has completely changed this. These can find real bugs and dismiss unreproducible speculation. The key feature of such a harness is that, given the right interfaces and instructions, it can create and run reproducible test cases to dynamically test hypotheses about bugs in code. After fixing the initial set of issues that Anthropic sent to us in February, we built our own harness atop our existing fuzzing infrastructure.

We began with small-scale experiments prompting the harness to look for sandbox escapes with Claude Opus 4.6. Even with this model, we identified an impressive amount of previously-unknown vulnerabilities which required complex reasoning over multiprocess browser engine code. At first, we supervised the process in the terminal to observe the process in real-time and tune the prompts and logic. Once this was working well, we parallelized the jobs across multiple ephemeral VMs, each tasked to hunt for bugs within a specific target file and write its findings back to a bucket.

A discovery subsystem is necessary but not sufficient. In order to scale the effort, we needed to integrate it with our full security bug lifecycle: determining what to look for, where to look, and how to handle what it produces. This last part includes deduplicating against known issues, tracking bugs, triaging them, and getting fixes shipped. While the model is the core primitive powering the harness, this full pipeline is necessary to make it useful at scale.

While harnesses may be reusable across projects, this pipeline is inherently project-specific, reflecting each codebase’s semantics, tooling, and processes. Standing this up required significant iteration, with a tight feedback loop alongside the Firefox engineers who were fielding the incoming bugs.

Upgrading the Models

Once the end-to-end pipeline is in place, it’s trivial to swap in different models when they become available. Building this pipeline early helped us find a number of serious bugs using publicly-available models, and it also helped us hit the ground running when we had the opportunity to evaluate Claude Mythos Preview. In our experience, model upgrades increase the effectiveness of the entire pipeline: the system gets simultaneously better at finding potential bugs, creating proof-of-concept test cases to demonstrate them, and articulating their pathology and impact.

In addition to fixing the 271 bugs identified by Claude Mythos Preview in the 150 release, we’ve shipped more of these fixes in 149.0.2, 150.0.1, and 150.0.2. We also continue to find bugs with other means internally, and, similar to other projects, we’ve seen a significant uptick in external reports in the last few months.

Ultimately, every bug requires care and attention to properly fix. Staying on top of this unprecedented volume has led to a lot of work and long days over the last few months, and we’re extremely proud of how the team has stepped up to meet this challenge. Over 100 people contributed code to this effort to ship the most secure Firefox yet. In addition to writing and reviewing patches, others have been building and scaling this pipeline, triaging, testing the fixes, and managing the release process for each bug.

Takeaways

Anyone building software can start using a harness with a modern model to find bugs and harden their code today. We recommend getting started now. You will find bugs, and you will set yourself up to take advantage of new models as soon as they become available.

You can start with very simple prompting, then observe and iterate. Our initial prompts were not dissimilar from those described here. Through iteration we’ve built out a lot of orchestration and tooling to optimize and scale the pipeline, but the essence of the inner loop remains the same: there is a bug in this part of the code, please find it and build a testcase.

We haven’t bottomed on all the latent bugs in Firefox, but are quite pleased with the trajectory. Today, our scanning is largely focused on specific areas of the code (files, functions) where we instruct the system to look, based on a mix of human judgement and automated signals. In the near future, we intend to integrate this analysis into our continuous integration system to scan patches as they land in the tree. Models are quite flexible with the form of context provided, and we expect patch-based scanning to work as well or even better than file-based scanning.

The current moment is a perilous one, but also full of opportunity. Let’s work together to secure the internet.

FAQ

The announcement said “271 bugs”, but I count something different. What’s going on?

On the advisories web page we group all internally-reported bugs as “rollup” CVEs with multiple bugs underneath them. The web page is built from yaml in the foundation-security-advisories repo, the canonical location for our CVE assignments. While some browsers do not create CVE identifiers for internally-discovered issues at all, we provide this information in order to be as transparent as possible.

In Firefox 150, there were three internal rollups: CVE-2026-6784 (154 bugs), CVE-2026-6785 (55 bugs), and CVE-2026-6786 (107 bugs).

Astute readers will notice the number of bugs in those internal rollups adds up to 316, which is more than the 271 we announced finding with Claude Mythos Preview. That’s because our security team hunts for new bugs every day by attacking Firefox with a combination of (a) fuzzing systems (b) manual inspection and (c) this new agentic pipeline across a variety of models.

We fixed a total of 423 security bugs in releases in April. In addition to the 271 bugs announced two weeks ago, there were 41 externally reported bugs, with the remaining 111 discovered internally and split roughly in third between:

1. Bugs found using this pipeline with Claude Mythos Preview but fixed in releases other than Firefox 150
2. Bugs found using this pipeline with other models
3. Bugs found with other techniques like fuzzing

Note that we also directly credited 3 CVEs to Anthropic separate from this latest effort (CVE-2026-6746, CVE-2026-6757, CVE-2026-6758). These were fixes for bugs sent to us by the outstanding Anthropic Frontier Red team a couple months ago and we assigned unique CVEs for each as per our normal process.

What do security ratings mean?

As additional context, we apply security severity ratings from critical to low to indicate the urgency of a bug:

• sec-critical and sec-high are assigned to vulnerabilities that can be triggered with normal user behavior, like browsing to a web page. We make no technical difference between these, but sec-critical bugs are reserved for issues that are publicly disclosed or known to be exploited in the wild.
• sec-moderate is assigned to vulnerabilities that would otherwise be rated sec-high but require unusual and complex steps from the victim.
• sec-low is assigned to bugs that are annoying but far from causing user harm (e.g, a safe crash).

Of the 271 bugs we announced for Firefox 150: 180 were sec-high, 80 were sec-moderate, and 11 were sec-low.

While we care most about critical/high bugs, it’s normal for us to prioritize moderate and low security bugs in order to fix correctness issues and as a defense-in-depth mechanism.

Is a sec-high or sec-critical bug the same as a practical exploit?

Not necessarily.

In most cases, a single critical/high bug is not actually enough to compromise Firefox. This is because Firefox has a defense-in-depth architecture, so for example exploiting a JIT bug only achieves remote code execution in a sandboxed and site-specific process. Real-world attackers generally need to chain multiple exploits together to escalate privileges through one or more layers of sandboxing along with OS-level mitigations like ASLR.

We also generally don’t build exploits to see whether a bug could be used by an attacker in the real world. We classify sec-high based on predictable crash symptoms such as use-after-free or out-of-bounds memory issues being reported by AddressSanitizer, and our threat model assumes that any of them could be exploitable with sufficient effort. This reduces the risk of a false negative during exploitability analysis, and more importantly it allows us to focus our resources on finding and fixing more vulnerabilities.

[1] Our bug bounty program has similar rules.

The post Behind the Scenes Hardening Firefox with Claude Mythos Preview appeared first on Mozilla Hacks - the Web developer blog.

The open web is a critical platform for applications that handle highly sensitive data, from private communications to financial transactions and medical records. Traditionally, servers are trusted to deliver the appropriate code and resources for their web applications to browsers, who then provide a secure and isolated environment for their execution. In some circumstances, this trust model falls short.

Consider a browser-based messaging application, like Signal or WhatsApp, which uses end-to-end encryption. The browser depends on the server to provide a trustworthy javascript implementation of the app; which ensures the user’s messages and cryptographic keys are suitably protected. A malicious or compromised server could selectively serve modified code to some users, undermining their security with little risk of detection. This challenges the basic premise of end-to-end encryption: that a misbehaving server should not be able to compromise user security.

Towards Verifiable Security on the Web

For web applications to be trustworthy in the presence of malicious servers, two properties are essential:

• Integrity: The code executed by the user matches what the developer committed to in a manifest.
• Transparency: These manifests are publicly logged and can be independently audited.

Web Application Integrity, Consistency and Transparency (WAICT) brings these properties to the web platform.

WAICT allows websites to cryptographically bind their client-side code to a manifest and commit that manifest to a publicly auditable log. Sites which need this stronger trust model can then opt in to WAICT enforcement. If an opted-in site delivers code that has not been publicly logged, the browser rejects it and attacks that were previously invisible become observable and attributable. This ensures that the code delivered to user’s machines is consistent with the publicly available code which security researchers can inspect.

Bringing Integrity and Transparency to the Open Web

We are collaborating with partners across the ecosystem – including Cloudflare, the Freedom of the Press Foundation and Meta – to ensure the deployment model is practical, secure, and as simple as possible. You can learn more about WAICT in our joint talk at Real World Cryptography 2026.

An early prototype of WAICT is available behind a pref in Firefox Nightly to help validate the approach in real-world scenarios. You can test drive the prototype on https://waict.dev/ – including an end-to-end encrypted video calling app secured by WAICT. The implementation is a work in progress, not a finished solution, but it provides a concrete foundation for iteration and standardization. We’re developing the specifications in the open and welcome early feedback.

WAICT marks an important step toward making strong, verifiable application security a first-class property of the open web.

With special thanks to Anna Weine, Benjamin Beurdouche, Christoph Kerschbaumer, Dennis Jackson, Frederik Braun, and Tom Schuster.

The post Trustworthy JavaScript for the Open Web appeared first on Mozilla Hacks - the Web developer blog.

In January, we introduced our Nightly package for RPM-based Linux distributions. Today, we are thrilled to announce it is now available for Firefox Beta!

Firefox Beta is great for testing your sites in a version of Firefox that will reach regular users in the coming weeks. If you find any issues, please file them on Bugzilla.

Switching to Mozilla’s RPM repository allows Firefox Beta to be installed and updated like any other application, using your favorite package manager. It also provides a number of improvements:

•  Better performance thanks to our advanced compiler-based optimizations,
• Updates as fast as possible because the .rpm management is integrated into Firefox’s release process,
• Hardened binaries with all security flags enabled during compilation,
• No need to create your own .desktop file.

If you have Mozilla’s RPM repository already set up, you can simply install Firefox Beta with your package manager. Otherwise, follow the setup steps below.

If you are on Fedora (41+), or any other distribution using dnf5 as the package manager

sudo dnf config-manager addrepo --id=mozilla --set=baseurl=https://packages.mozilla.org/rpm/firefox --set=gpgkey=https://packages.mozilla.org/rpm/firefox/signing-key.gpg --set=gpgcheck=1 --set=repo_gpgcheck=0
sudo dnf makecache --refresh
sudo dnf install firefox-beta

Note: repo_gpgcheck=0 deactivate the signature of metadata with GPG. However, this is safeguarded instead by HTTPS and package signatures (gpgcheck=1).

If you are on openSUSE or any other distribution using zypper as the package manager

sudo rpm --import https://packages.mozilla.org/rpm/firefox/signing-key.gpg
sudo zypper ar --gpgcheck-allow-unsigned-repo https://packages.mozilla.org/rpm/firefox mozilla
sudo zypper refresh
sudo zypper install firefox-beta

For other RPM based distributions (RHEL, CentOS, Rocky Linux, older Fedora versions)

sudo tee /etc/yum.repos.d/mozilla.repo >  /dev/null << EOF
[mozilla]
name=Mozilla Packages
baseurl=https://packages.mozilla.org/rpm/firefox
enabled=1
gpgcheck=1
repo_gpgcheck=0
gpgkey=https://packages.mozilla.org/rpm/firefox/signing-key.gpg
EOF

# For dnf users
sudo dnf makecache --refresh
sudo dnf install firefox-beta

# For zypper users
sudo zypper refresh
sudo zypper install firefox-beta

The firefox-beta package will not conflict with your distribution’s Firefox package if you have it installed, you can have both at the same time!

Adding language packs

If your distribution language is set to a supported language, language packs for it should automatically be installed. You can also install them manually with the following command (replace fr with the language code of your choice):

sudo dnf install firefox-beta-l10n-fr

You can list the available languages with the following command:

dnf search firefox-beta-l10n

Don’t hesitate to report any problem you encounter to help us make your experience better.

The post Firefox Developer Edition and Beta: Try out Mozilla’s .rpm package! appeared first on Mozilla Hacks - the Web developer blog.

This post is an expanded version of a presentation I gave at the 2025 WebAssembly CG meeting in Munich.

WebAssembly has come a long way since its first release in 2017. The first version of WebAssembly was already a great fit for low-level languages like C and C++, and immediately enabled many new kinds of applications to efficiently target the web.

Since then, the WebAssembly CG has dramatically expanded the core capabilities of the language, adding shared memories, SIMD, exception handling, tail calls, 64-bit memories, and GC support, alongside many smaller improvements such as bulk memory instructions, multiple returns, and reference values.

These additions have allowed many more languages to efficiently target WebAssembly. There’s still more important work to do, like stack switching and improved threading, but WebAssembly has narrowed the gap with native in many ways.

Yet, it still feels like something is missing that’s holding WebAssembly back from wider adoption on the Web.

There are multiple reasons for this, but the core issue is that WebAssembly is a second-class language on the web. For all of the new language features, WebAssembly is still not integrated with the web platform as tightly as it should be.

This leads to a poor developer experience, which pushes developers to only use WebAssembly when they absolutely need it. Oftentimes JavaScript is simpler and “good enough”. This means its users tend to be large companies with enough resources to justify the investment, which then limits the benefits of WebAssembly to only a small subset of the larger Web community.

Solving this issue is hard, and the CG has been focused on extending the WebAssembly language. Now that the language has matured significantly, it’s time to take a closer look at this. We’ll go deep into the problem, before talking about how WebAssembly Components could improve things.

What makes WebAssembly second-class?

At a very high level, the scripting part of the web platform is layered like this:

WebAssembly can directly interact with JavaScript, which can directly interact with the web platform. WebAssembly can access the web platform, but only by using the special capabilities of JavaScript. JavaScript is a first-class language on the web, and WebAssembly is not.

This wasn’t an intentional or malicious design decision; JavaScript is the original scripting language of the Web and co-evolved with the platform. Nonetheless, this design significantly impacts users of WebAssembly.

What are these special capabilities of JavaScript? For today’s discussion, there are two major ones:

1. Loading of code
2. Using Web APIs

Loading of code

WebAssembly code is unnecessarily cumbersome to load. Loading JavaScript code is as simple as just putting it in a script tag:

<script src="script.js"></script>

WebAssembly is not supported in script tags today, so developers need to use the WebAssembly JS API to manually load and instantiate code.

let bytecode = fetch(import.meta.resolve('./module.wasm'));
let imports = { ... };
let { exports } =
  await WebAssembly.instantiateStreaming(bytecode, imports);

The exact sequence of API calls to use is arcane, and there are multiple ways to perform this process, each of which has different tradeoffs that are not clear to most developers. This process generally just needs to be memorized or generated by a tool for you.

Thankfully, there is the esm-integration proposal, which is already implemented in bundlers today and which we are actively implementing in Firefox. This proposal lets developers import WebAssembly modules from JS code using the familiar JS module system.

import { run } from "/module.wasm";

run();

In addition, it allows a WebAssembly module to be loaded directly from a script tag using type=”module”:

<script type="module" src="/module.wasm"></script>

This streamlines the most common patterns for loading and instantiating WebAssembly modules. However, while this mitigates the initial difficulty, we quickly run into the real problem.

Using Web APIs

Using a Web API from JavaScript is as simple as this:

console.log("hello, world");

For WebAssembly, the situation is much more complicated. WebAssembly has no direct access to Web APIs and must use JavaScript to access them.

The same single-line console.log program requires the following JavaScript file:

// We need access to the raw memory of the Wasm code, so
// create it here and provide it as an import.
let memory = new WebAssembly.Memory(...);

function consoleLog(messageStartIndex, messageLength) {
  // The string is stored in Wasm memory, but we need to
  // decode it into a JS string, which is what DOM APIs
  // require.
  let messageMemoryView = new UInt8Array(
      memory.buffer, messageStartIndex, messageLength);
  let messageString =
    new TextDecoder().decode(messageMemoryView);

  // Wasm can't get the `console` global, or do
  // property lookup, so we do that here.
  return console.log(messageString);
}

// Pass the wrapped Web API to the Wasm code through an
// import.
let imports = {
  "env": {
    "memory": memory,
    "consoleLog": consoleLog,
  },
};
let { instance } =
  await WebAssembly.instantiateStreaming(bytecode, imports);

instance.exports.run();

And the following WebAssembly file:

(module
  ;; import the memory from JS code
  (import "env" "memory" (memory 0))

  ;; import the JS consoleLog wrapper function
  (import "env" "consoleLog"
    (func $consoleLog (param i32 i32))
  )

  ;; export a run function
  (func (export "run")
    (local i32 $messageStartIndex)
    (local i32 $messageLength)

    ;; create a string in Wasm memory, store in locals
    ...

    ;; call the consoleLog method
    local.get $messageStartIndex
    local.get $messageLength
    call $consoleLog
  )
)

Code like this is called “bindings” or “glue code” and acts as the bridge between your source language (C++, Rust, etc.) and Web APIs.

This glue code is responsible for re-encoding WebAssembly data into JavaScript data and vice versa. For example, when returning a string from JavaScript to WebAssembly, the glue code may need to call a malloc function in the WebAssembly module and re-encode the string at the resulting address, after which the module is responsible for eventually calling free.

This is all very tedious, formulaic, and difficult to write, so it is typical to generate this glue automatically using tools like embind or wasm-bindgen. This streamlines the authoring process, but adds complexity to the build process that native platforms typically do not require. Furthermore, this build complexity is language-specific; Rust code will require different bindings from C++ code, and so on.

Of course, the glue code also has runtime costs. JavaScript objects must be allocated and garbage collected, strings must be re-encoded, structs must be deserialized. Some of this cost is inherent to any bindings system, but much of it is not. This is a pervasive cost that you pay at the boundary between JavaScript and WebAssembly, even when the calls themselves are fast.

This is what most people mean when they ask “When is Wasm going to get DOM support?” It’s already possible to access any Web API with WebAssembly, but it requires JavaScript glue code.

Why does this matter?

From a technical perspective, the status quo works. WebAssembly runs on the web and many people have successfully shipped software with it.

From the average web developer’s perspective, though, the status quo is subpar. WebAssembly is too complicated to use on the web, and you can never escape the feeling that you’re getting a second class experience. In our experience, WebAssembly is a power user feature that average developers don’t use, even if it would be a better technical choice for their project.

The average developer experience for someone getting started with JavaScript is something like this:

There’s a nice gradual curve where you use progressively more complicated features as the scope of your project increases.

By comparison, the average developer experience for someone getting started with WebAssembly is something like this:

You immediately must scale “the wall” of wrangling the many different pieces to work together. The end result is often only worth it for large projects.

Why is this the case? There are several reasons, and they all directly stem from WebAssembly being a second class language on the web.

1. It’s difficult for compilers to provide first-class support for the web

Any language targeting the web can’t just generate a Wasm file, but also must generate a companion JS file to load the Wasm code, implement Web API access, and handle a long tail of other issues. This work must be redone for every language that wants to support the web, and it can’t be reused for non-web platforms.

Upstream compilers like Clang/LLVM don’t want to know anything about JS or the web platform, and not just for lack of effort. Generating and maintaining JS and web glue code is a specialty skill that is difficult for already stretched-thin maintainers to justify. They just want to generate a single binary, ideally in a standardized format that can also be used on platforms besides the web.

2. Standard compilers don’t produce WebAssembly that works on the web

The result is that support for WebAssembly on the web is often handled by third-party unofficial toolchain distributions that users need to find and learn. A true first-class experience would start with the tool that users already know and have installed.

This is, unfortunately, many developers’ first roadblock when getting started with WebAssembly. They assume that if they just have rustc installed and pass a –target=wasm flag that they’ll get something they could load in a browser. You may be able to get a WebAssembly file doing that, but it will not have any of the required platform integration. If you figure out how to load the file using the JS API, it will fail for mysterious and hard-to-debug reasons. What you really need is the unofficial toolchain distribution which implements the platform integration for you.

3. Web documentation is written for JavaScript developers

The web platform has incredible documentation compared to most tech platforms. However, most of it is written for JavaScript. If you don’t know JavaScript, you’ll have a much harder time understanding how to use most Web APIs.

A developer wanting to use a new Web API must first understand it from a JavaScript perspective, then translate it into the types and APIs that are available in their source language. Toolchain developers can try to manually translate the existing web documentation for their language, but that is a tedious and error prone process that doesn’t scale.

4. Calling Web APIs can still be slow

If you look at all of the JS glue code for the single call to console.log above, you’ll see that there is a lot of overhead. Engines have spent a lot of time optimizing this, and more work is underway. Yet this problem still exists. It doesn’t affect every workload, but it’s something every WebAssembly user needs to be careful about.

Benchmarking this is tricky, but we ran an experiment in 2020 to precisely measure the overhead that JS glue code has in a real world DOM application. We built the classic TodoMVC benchmark in the experimental Dodrio Rust framework and measured different ways of calling DOM APIs.

Dodrio was perfect for this because it computed all the required DOM modifications separately from actually applying them. This allowed us to precisely measure the impact of JS glue code by swapping out the “apply DOM change list” function while keeping the rest of the benchmark exactly the same.

We tested two different implementations:

1. “Wasm + JS glue”: A WebAssembly function which reads the change list in a loop, and then asks JS glue code to apply each change individually. This is the performance of WebAssembly today.
2. “Wasm only”: A WebAssembly function which reads the change list in a loop, and then uses an experimental direct binding to the DOM which skips JS glue code. This is the performance of WebAssembly if we could skip JS glue code.

The duration to apply the DOM changes dropped by 45% when we were able to remove JS glue code. DOM operations can already be expensive; WebAssembly users can’t afford to pay a 2x performance tax on top of that. And as this experiment shows, it is possible to remove the overhead.

5. You always need to understand the JavaScript layer

There’s a saying that “abstractions are always leaky”.

The state of the art for WebAssembly on the web is that every language builds their own abstraction of the web platform using JavaScript. But these abstractions are leaky. If you use WebAssembly on the web in any serious capacity, you’ll eventually hit a point where you need to read or write your own JavaScript to make something work.

This adds a conceptual layer which is a burden for developers. It feels like it should just be enough to know your source language, and the web platform. Yet for WebAssembly, we require users to also know JavaScript in order to be a proficient developer.

How can we fix this?

This is a complicated technical and social problem, with no single solution. We also have competing priorities for what is the most important problem with WebAssembly to fix first.

Let’s ask ourselves: In an ideal world, what could help us here?

What if we had something that was:

1. A standardized self-contained executable artifact
2. Supported by multiple languages and toolchains
3. Which handles loading and linking of WebAssembly code
4. Which supports Web API usage

If such a thing existed, languages could generate these artifacts and browsers could run them, without any JavaScript involved. This format would be easier for languages to support and could potentially exist in standard upstream compilers, runtimes, toolchains, and popular packages without the need for third-party distributions. In effect, we could go from a world where every language re-implements the web platform integration using JavaScript, to sharing a common one that is built directly into the browser.

It would obviously be a lot of work to design and validate a solution! Thankfully, we already have a proposal with these goals that has been in development for years: the WebAssembly Component Model.

What is a WebAssembly Component?

For our purposes, a WebAssembly Component defines a high-level API that is implemented with a bundle of low-level WebAssembly code. It’s a standards-track proposal in the WebAssembly CG that’s been in development since 2021.

Already today, WebAssembly Components…

• Can be created from many different programming languages.
• Can be executed in many different runtimes (including in browsers today, with a polyfill).
• Can be linked together to allow code re-use between different languages.
• Allow WebAssembly code to directly call Web APIs.

If you’re interested in more details, check out the Component Book or watch “What is a Component?”.

We feel that WebAssembly Components have the potential to give WebAssembly a first-class experience on the web platform, and to be the missing link described above.

How could they work?

Let’s try to re-create the earlier console.log example using only WebAssembly Components and no JavaScript.

NOTE: The interactions between WebAssembly Components and the web platform have not been fully designed, and the tooling is under active development.

Take this as an aspiration for how things could be, not a tutorial or promise.

The first step is to specify which APIs our application needs. This is done using an IDL called WIT. For our example, we need the Console API. We can import it by specifying the name of the interface.

component {
  import std:web/console;
}

The std:web/console interface does not exist today, but would hypothetically come from the official WebIDL that browsers use for describing Web APIs. This particular interface might look like this:

package std:web;

interface console {
  log: func(msg: string);
  ...
}

Now that we have the above interfaces, we can use them when writing a Rust program that compiles to a WebAssembly Component:

use std::web::console;

fn main() {
  console::log(“hello, world”);
}

Once we have a component, we can load it into the browser using a script tag.

<script type="module" src="component.wasm"></script>

And that’s it! The browser would automatically load the component, bind the native web APIs directly (without any JS glue code), and run the component.

This is great if your whole application is written in WebAssembly. However, most WebAssembly usage is part of a “hybrid application” which also contains JavaScript. We also want to simplify this use case. The web platform shouldn’t be split into “silos” that can’t interact with each other. Thankfully, WebAssembly Components also address this by supporting cross-language interoperability.

Let’s create a component that exports an image decoder for use from JavaScript code. First we need to write the interface that describes the image decoder:

interface image-lib {
  record pixel {
    r: u8;
    g: u8;
    b: u8;
    a: u8;
  }

  resource image {
    from-stream:
      static async func(bytes: stream<u8>) -> result<image>;
    get: func(x: u32, y: u32) -> pixel;
  }
}

component {
    export image-lib;
}

Once we have that, we can write the component in any language that supports components. The right language will depend on what you’re building or what libraries you need to use. For this example, I’ll leave the implementation of the image decoder as an exercise for the reader.

The component can then be loaded in JavaScript as a module. The image decoder interface we defined is accessible to JavaScript, and can be used as if you were importing a JavaScript library to do the task.

import { Image } from "image-lib.wasm";

let byteStream = (await fetch("/image.file")).body;
let image = await Image.fromStream(byteStream);

let pixel = image.get(0, 0);

console.log(pixel); // { r: 255, g: 255, b: 0, a: 255 }

Next Steps

As it stands today, we think that WebAssembly Components would be a step in the right direction for the web. Mozilla is working with the WebAssembly CG to design the WebAssembly Component Model. Google is also evaluating it at this time.

If you’re interested to try this out, learn to build your first component and try it out in the browser using Jco or from the command-line using Wasmtime. The tooling is under heavy development, and contributions and feedback are welcome. If you’re interested in the in-development specification itself, check out the component-model proposal repository.

WebAssembly has come very far from when it was first released in 2017. I think the best is still yet to come if we’re able to turn it from being a “power user” feature, to something that average developers can benefit from.

The post Why is WebAssembly a second-class language on the web? appeared first on Mozilla Hacks - the Web developer blog.

Cross-site scripting (XSS) remains one of the most prevalent vulnerabilities on the web. The new standardized Sanitizer API provides a straightforward way for web developers to sanitize untrusted HTML before inserting it into the DOM. Firefox 148 is the first browser to ship this standardized security enhancing API, advancing a safer web for everyone. We expect other browsers to follow soon.

An XSS vulnerability arises when a website inadvertently lets attackers inject arbitrary HTML or JavaScript through user-generated content. With this attack, an attacker could monitor and manipulate user interactions and continually steal user data for as long as the vulnerability remains exploitable. XSS has a long history of being notoriously difficult to prevent and has ranked among the top three web vulnerabilities (CWE-79) for nearly a decade.

Firefox has been deeply involved in solutions for XSS from the beginning, starting with spearheading the Content-Security-Policy (CSP) standard in 2009. CSP allows websites to restrict which resources (scripts, styles, images, etc.) the browser can load and execute, providing a strong line of defense against XSS. Despite a steady stream of improvements and ongoing maintenance, CSP did not gain sufficient adoption to protect the long tail of the web as it requires significant architectural changes for existing web sites and continuous review by security experts.

The Sanitizer API is designed to help fill that gap by providing a standardized way to turn malicious HTML into harmless HTML — in other words, to sanitize it. The setHTML( ) method integrates sanitization directly into HTML insertion, providing safety by default. Here is an example of sanitizing a simple unsafe HTML:

document.body.setHTML(`<h1>Hello my name is <img src="x" 
onclick="alert('XSS')">`);

This sanitization will allow the HTML <h1> element while removing the embedded <img> element and its onclick attribute, thereby eliminating the XSS attack resulting in the following safe HTML:

<h1>Hello my name is</h1>

Developers can opt into stronger XSS protections with minimal code changes by replacing error-prone innerHTML assignments with setHTML(). If the default configuration of setHTML( ) is too strict (or not strict enough) for a given use case, developers can provide a custom configuration that defines which HTML elements and attributes should be kept or removed. To experiment with the Sanitizer API before introducing it on a web page, we recommend exploring the Sanitizer API playground.

For even stronger protections, the Sanitizer API can be combined with Trusted Types, which centralize control over HTML parsing and injection. Once setHTML( ) is adopted, sites can enable Trusted Types enforcement more easily, often without requiring complex custom policies. A strict policy can allow setHTML( ) while blocking other unsafe HTML insertion methods, helping prevent future XSS regressions.

The Sanitizer API enables an easy replacement of innerHTML assignments with setHTML( ) in existing code, introducing a new safer default to protect users from XSS attacks on the web. Firefox 148 supports the Sanitizer API as well as Trusted Types, which creates a safer web experience. Adopting these standards will allow all developers to prevent XSS without the need for a dedicated security team or significant implementation changes.

Image credits for the illustration above: Website, by Desi Ratna; Person, by Made by Made; Hacker by Andy Horvath.

The post Goodbye innerHTML, Hello setHTML: Stronger XSS Protection in Firefox 148 appeared first on Mozilla Hacks - the Web developer blog.

The Interop Project is a cross-browser initiative to improve web compatibility in areas that offer the most benefit to both users and developers.

The group, including Apple, Google, Igalia, Microsoft, and Mozilla, takes proposals of features that are well defined in a sufficiently stable web standard, and have good test suite coverage. Then, we come up with a subset of those proposals that balances web developer priorities (via surveys and bug reports) with our collective resources.

We focus on features that are well-represented in Web Platform Tests as the pass-rate is how we measure progress, which you can track on the Interop dashboard.

Once we have an agreed set of focus areas, we use those tests to track progress in each browser throughout the year. And after that, we do it all again!

But, before we talk about 2026, let’s take a look back at Interop 2025…

Interop 2025

Firefox started Interop 2025 with a score of 46, so we’re really proud to finish the cycle on 99. But the number that really matters is the overall Interop score, which is a combined score for all four browsers – and the higher this number is, the fewer developer hours are lost to frustrating browser differences.

The overall Interop score started at 25, and it’s now 95. As a result, huge web platform features became available cross-browser, such as Same-Document View Transitions, CSS Anchor Positioning, the Navigation API, CSS @scope, and the URLPattern API.

That’s the headline-grabbing part, but in my experience, it’s way more frustrating when a feature is claimed to be supported, but doesn’t work as expected. That’s why Interop 2025 also focused on improving the reliability of existing features like WebRTC, CSS Flexbox, CSS Grid, Pointer Events, CSS backdrop-filter, and more.

But it’s not just about passing tests

With some focus areas, in particular CSS Anchor Positioning and the Navigation API, we noticed that it was possible to achieve a good score on the tests while having inconsistent behavior compared to other browsers.

In some cases this was due to missing tests, but in some cases the tests contradicted the spec. This usually happens when tests are written against a particular implementation, rather than the specified behavior.

I experienced this personally before I joined Mozilla – I tried to use CSS Anchor Positioning back when it was only shipping in Chrome and Safari, and even with simple use-cases, the results were wildly inconsistent.

Although it caused delays in these features landing in Firefox, we spent time highlighting these problems by filing issues against the relevant specs, and ensured they got priority in their working groups. As a result, specs became less ambiguous, tests were improved, and browser behavior became more reliable for developers.

Okay, that’s enough looking at the past. Let’s move on to…

Interop 2026

Over 150 proposals were submitted for Interop 2026. We looked through developer feedback, on the issues themselves, and developer surveys like The State of HTML and The State of CSS. As an experiment for 2026, we at Mozilla also invited developers to stack-rank the proposals, the results of which we used in combination with the other data to compare developer preferences between individual features – this is something we want to expand on in the future.

After carefully examining all the proposals, the Interop group has agreed on 20 focus areas (formed of 33 proposals) and 4 investigation areas. See the Interop repository for the full list, but here are the highlights:

New features

As with 2025, part of the effort is about bringing new features to all browser engines.

Cross-document View Transitions allow transitions to work across documents, without any JavaScript. The sub-features rel="expect" and blocking="render" are included in this focus area..

Scroll-driven animations allow you to drive animations based on the user’s scroll position. This replaces heavy JavaScript solutions that run on the main thread.

WebTransport provides a low-level API over HTTP/3, allowing for multiple unidirectional streams, and optional out-of-order delivery. This is a modern alternative to WebSockets.

CSS container style queries allow you to apply a block of styles depending on the computed values of custom properties on the nearest container. This means, for example, you can have a simple --theme property that impacts a range of other properties.

JavaScript Promise Integration for Wasm allows WebAssembly to asynchronously ‘suspend’, waiting on the result of an external promise. This simplifies the compilation of languages like C/C++ which expect APIs to run synchronously.

CSS attr() has been supported across browsers for over 15 years, but only for pseudo-element content. For Interop 2026, we’re focusing on more recent changes that allow attribute values to be used in most CSS values (with URLs being an exception).

CSS custom highlights let you register a bunch of DOM ranges as a named highlight, which you can style via the ::highlight(name) pseudo-element. The styling is limited, but it means these ranges can span between elements, don’t impact layout, and don’t disrupt things like text selection.

Scoped Custom Element Registries allow different parts of your DOM tree (such as a shadow root) to use a different set of custom elements definitions, meaning the same tag name can refer to different custom elements depending on where they are in the DOM.

CSS shape() is a reimagining of path() that, rather than using SVG path syntax, uses a CSS syntax, allowing for mixed units and calc(). In practice, this makes it much easier to design responsive clip-paths and offset-paths.

And more, including CSS contrast-color, accent-color, dialog closedby, popover=”hint”, fetch upload streams, IDB getAllRecords(), media pseudo-classes such as :playing, and the Navigation API’s precommitHandler.

Existing feature reliability improvements

Like in previous years, the backbone of Interop is in improving the reliability of existing features, removing frustrations for web developers.

In 2026, we’ll be focusing these efforts on particular edge cases in:

• Range headers & form data in fetch
• The Navigation API
• CSS scroll snap
• CSS anchor positioning
• Same-document View Transitions
• JavaScript top-level await
• The event loop
• WebRTC
• CSS user-select
• CSS zoom

Some of these are carried over from 2025 focus areas, as shortcomings in the tests and specs were fixed, but too late to be included in Interop 2025.

Again, these are less headline-grabbing than the shiny new features, but it’s these edge cases where us web developers lose hours of our time. Frustrating, frustrating, hours.

Interop investigations

Sometimes, we see a focus area proposal that’s clearly important, but doesn’t fit the requirements of Interop. This is usually because the tests for the feature aren’t sufficient, are in the wrong format, or browsers are missing automation features that are needed to make the feature testable.

In these cases, we identify what’s missing, and set up an investigation area.

For interop 2026, we’re looking at…

Accessibility. This is a continuation of work in 2025. Ultimately, we want browsers to produce consistent accessibility trees from the same DOM and CSS, but before we can write tests for this, we need to improve our testing infrastructure.

Mobile testing. Another continuation from 2025. In particular, in 2026, we want to figure out an approach for testing viewport changes caused by dynamic UI, such as the location bar and virtual keyboard.

JPEG XL. The current tests for this are sparse. Existing decoders have more comprehensive test suites, but we need to figure out how these relate to browsers. For example, progressive rendering is an important feature for developers, but how and when browsers should do this (to avoid performance issues) is currently being debated.

WebVTT. This feature allows for text to be synchronised to video content. The investigation is to go through the test suite and ensure it’s fit for purpose, and amend it where necessary.

It begins… again

The selected focus areas mean we’ve committed to more work compared to the other browsers, which is quite the challenge being the only engine that isn’t owned by billionaires. But it’s a challenge we’re happy to take on!

Together with other members of the Interop group, we’re looking forward to delivering features and fixes over the next year. You can follow along with the progress of all browsers on the Interop dashboard.

If your favorite feature is missing from Interop 2026, that doesn’t mean it won’t be worked on. JPEG XL is a good example of this. The current test suite meant it wasn’t a good fit for Interop 2026, but we’ve challenged the JPEG XL team at Google Research to build a memory-safe decoder in Rust, which we’re currently experimenting with in Firefox, as is Chrome.

Interop isn’t the limit of what we’re working on, but it is a cross-browser commitment.

If you’re interested in details of features as they land in Firefox, and discussions of future features from spec groups, you can follow us on:

• BlueSky
• Mastodon
• LinkedIn
• Threads
• YouTube
• TikTok
• Instagram

Partner Announcements

This is a team effort, and we’ve all made announcement posts like this one. Get other members’ take on it:

• Apple
• Google
• Igalia
• Microsoft

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