Rust Blog

Announcing a Maintainer in Residence: Scott Schafer for the Cargo team

2026-09-22T00:00:00+00:00

At the end of August, we announced our first Maintainers in Residence, Rust Project contributors who are funded for their upstream contributions and maintenance work from the Rust Foundation Maintainers Fund (RFMF). Since then, the Rust Leadership Council has dedicated more funds from its Project Priorities budget to RFMF, and together with AWS also providing additional funds, this allowed us to open a new full-time Maintainer in Residence (MiR) position to support the Cargo team. We would like to thank the Rust Leadership Council, AWS, and also the Rust Foundation for providing us with this opportunity! If you would like to help us hire more maintainers to improve Rust, consider donating to RFMF.

This post explains why we chose to support the Cargo team specifically, and introduces Scott Schafer, the new Cargo Maintainer in Residence.

Why Cargo?

The new MiR full-time position is dedicated to helping with the maintenance of Cargo, our build system and package manager. The Cargo project is deeply involved in many new Rust features, improvements, and Project Goals. Combined with its cross-cutting nature, where it has to support many different use-cases and integrate with several other tools, it takes a lot of work just to keep up with its maintenance needs, let alone support so many feature requests and proposed changes.

Because of that, the Cargo team has sometimes struggled with meeting its maintenance demands. You might remember that for several years, it actually held a feature freeze, to reduce Cargo's internal tech debt, perform necessary refactorings, go through the issue and pull request backlog, and come up with scalable internal development and design processes, so that they could eventually go back to even thinking about adding new features.

Recently, some changes occurred within the team, which made it more difficult for them to meet their maintenance baseline. Some members of the team left, while others lost their dedicated funding for working on Cargo maintenance and had to scale down their involvement. The Funding team thus considered it very important to support this team, given that we had an opportunity to do so. And thus we decided to hire a full-time maintainer to work on Cargo for (at least) the next 12 months.

Even though we know that a single full-time maintainer will not completely solve the maintenance struggles of the Cargo team, we hope that it will improve the situation, and provide a bit of a relief for the team.

Introducing Scott Schafer

We are very happy to welcome Scott Schafer (@muscraft) into the Maintainer in Residence role! Scott has joined the Cargo team three years ago, and apart from working on Cargo, he is also the lead of the Rust Docker team, which prepares official Docker images for every Rust version.

Apart from working on general maintenance of Cargo, Scott has implemented Cargo's Workspace inheritance feature, and has also spearheaded a complex multi-year effort to switch the rendering of diagnostics in the Rust compiler to use the annotate-snippets crate. This effort has been completed in the Rust 1.93.0 release. Thanks to it, the same diagnostics interface can now be shared between the compiler and Cargo (and also other tools), which amongst other things unblocked further development of the Cargo linting system, which has now been stabilized and will ship in the Rust 1.100.0 release.

Everyone we talked about was very excited about Scott becoming a Cargo Maintainer in Residence, and we share that feeling. We wish Scott all the best in his new role, and we are very happy that we can support his maintenance work.

Here is what Scott thinks about it:

I am incredibly excited to work on Cargo full-time! There have been so many things that I wish I could've worked on over the years, that I will now be able to get to. I hope that my efforts will bring Cargo into a more maintainable state.

Conclusion

We are incredibly happy that we keep getting more funds for the Rust Foundation Maintainers Fund, which allows us to support Rust Project contributors. The funding team will be working with the supported maintainers, and also the funders, to ensure that they are all happy with the arrangement, so that we can secure stable funding for Rust maintenance for years to come.

If you would like to help us support more Rust maintainers, consider donating to RFMF!

GitHub Actions leaking secrets when Miri output is cached

2026-09-21T00:00:00+00:00

The Rust Security Response Team was notified that Miri stores all environment variables to target/, allowing secrets to persist in caches.

While not necessary a vulnerability in and of itself, when paired with GitHub Actions caching behavior, it is possible for this to expose secrets to PRs.

Overview

GitHub Actions makes it possible to cache directories between runs. Typical setups allow CI runs on main (and other branches) to write to cache, and PRs can only read from cache (preventing cache poisoning). Rust projects tend to speed up CI by caching binaries built by cargo install and sometimes the contents of target/.

PR CI can be triggered by anyone who can open PRs on your repository. GitHub requires maintainer approval for the first PR, but future PRs will rerun CI on every push. Anyone who has previously landed a change can trigger a CI run extracting information from cached target/ and then cover their tracks by pushing a second commit to the PR.

GitHub sometimes hides overwritten commits in its UI, making this kind of attack harder to detect. CI run logs and overwritten commits are also deleted after a few months.

When cargo miri is invoked, Miri needs to retain build-relevant environment variables between runs¹. The current code to do so achieves this by storing all environment variables to target/. This, of course, persists when target/ is cached.

If your environment contained secrets, these can now be accessed by PRs via the cache.

Our fix

Our short term fix for this is to make Miri only preserve CARGO_* environment variables (excepting CARGO_*_TOKEN) and OUT_DIR. In the longer term, Miri and cargo may figure out better ways to inform Miri of the relevant list of environment variables. Note that this patch may not be available on nightly yet.

We also performed an ecosystem scan of GitHub repositories and identified 1 repository with this issue and 7 repositories that do not appear to be vulnerable but should be cautious anyway. We have reached out to those maintainers.

Am I affected?

It is likely that our scan was imperfect, so we recommend you check your own GitHub Actions setups if you run Miri.

You are vulnerable if:

You run cargo miri in CI
The step that runs cargo miri has access to secrets as an environment variable:
- By being passed in to the step itself as an environment variable
- By being set in env for the workflow
- By being passed in to a previous step that persists it in the environment somehow
The workflow being used caches the target directory, usually done via actions/cache or swatinem/rust-cache
The cache is accessible to PRs (common and often the intended use case)

Possible quick fixes include:

Disabling cache for that job.
Scoping secrets to steps in that job that do not call Miri.
Temporarily disabling Miri.

Once done, please clear the cache. Consider rotating any secrets that might have leaked.

The Miri release in the upcoming nightly (2026-09-22) will no longer have this problem.

Even if you do not run Miri, ensure jobs that can write to public caches do not have access to secrets. Many tools do not have special handling for secrets, and assume the entire environment can be written to the filesystem.

Threat model

We consider it bad practice to have a cache that can easily be tainted by secrets.

If caching target/, it is worth making sure that the inputs to processes that create target/ (anything invoking cargo) do not have secrets available. It is generally rare for standard cargo build/test subcommands to need any secrets or tokens², so this is mostly a matter of being careful about having secrets exposed as environment variables to the entire job.

Cargo/Miri/Rust does not guarantee that environment variables will be safe from being copied into target/. While we are treating this as a security issue and patching it out of an abundance of caution, this is not something you should rely on in general. Beyond official Rust tooling, it is possible for build scripts to be doing things that lead to the environment being stored in compilation artifacts.

Acknowledgements

Thanks to Predrag Gruevski of OpenAI for reporting this issue to us. Furthermore, the ecosystem scan was performed using Codex access and credits donated by OpenAI, which we also thank them for.

Issue triage and remediation was performed by Manish Goregaokar, Ralf Jung, Ben Kimock, Weihang Lo, Jacob Finkelman, Walter Pearce, Josh Stone, and Mark Rousskov.

Miri is invoked multiple times by cargo miri for complicated reasons ↩
In theory it could come up with build scripts reading from the network ↩

Be alert: targeted attacks on prominent Rustaceans

2026-09-17T00:00:00+00:00

We believe that there is an ongoing campaign targeting rust-lang members and owners of popular crates that is attempting to compromise devices and accounts in order to use them to publish malware.

What we've seen

A video call is set up for something positive — maybe for a job, maybe for a project, maybe for a contract opportunity — and then that's used as a vector to either get the target to install something on their computer (such as a purportedly missing audio codec) or execute another command (for example, via putting a command on the clipboard).

These attackers are setting up new but legitimate seeming company profiles, including plausible LinkedIn presences, in order to pass cursory inspection.

A previous attack of this form targeted many prominent Rust developers in June, and, last month, the arrayref crate was briefly compromised through similar attacks. At this moment we do not know if these are all a part of the same campaign.

This attack style is known to be used by the DPRK, and has been seen outside of the Rust community as well.

What you can do

Please take extra care in the near term. Be appropriately suspicious of cold outreaches, and ensure that any calls you have with new people are on platforms you trust — ideally, try to be the one who sets up the call on a platform you already use.

Please also re-check that your accounts look normal: MFA enabled, no unexpected logins on platforms that can track that, and so on.

If you have any concerns about your accounts, please reach out to help@crates.io (for crates.io account concerns) and/or security@rust-lang.org (for any other concerns). We're very happy to help.

Rust debugging survey 2026 results

2026-09-07T00:00:00+00:00

One of the biggest challenges Rust developers report in our annual surveys is a subpar debugging experience. So, back in February, we ran our first Rust Debugging Survey, in the hopes of identifying how Rust developers are using debuggers and what problems they are facing when doing so. We received over 2,300 responses, and we'd like to thank everyone who took the time to participate in the survey!

In this report, we'll go over some of the results of the survey. If you'd like, you can also check out the complete results of the survey.

If you'd like to skip ahead to any particular section, you can do so with this index:

Who Uses Debuggers?
How Are Debuggers Used?
Challenges
Debugger Visualizers
Closing Remarks

Who Uses Debuggers?

The first step to making sense of the survey results is understanding who took the survey. We asked respondents to rate their Rust expertise, from "Never used it" to "Advanced". Over 80% reported themselves as "Advanced" or "Intermediate", split roughly evenly between the two:

[PNG] [SVG]

We also asked respondents if they currently use or have used debuggers in Rust. Over 46% said they currently do, with the remaining responses split between "have in the past" and "never have". That means that over half of respondents do not currently use a debugger for Rust!

[PNG] [SVG]

Categorized by expertise, the responses reveal that roughly half of "beginners" have never used debuggers in Rust! On the other hand, nearly half of "advanced users" currently do use debuggers in Rust:

[PNG] [SVG]

For respondents who indicated they had previously used Rust but no longer did, we asked if challenges with debugging support were why they stopped. For nearly 3%, the answer was "yes", with an additional 24% reporting debugging issues as being partially responsible (though mind the small response count; most respondents were active users of Rust):

[PNG] [SVG]

How Are Debuggers Used?

Knowing what debuggers developers are using and how is another important part of understanding the challenges they face. To this end, we asked respondents how they were debugging their programs. Unsurprisingly, most developers make use of print debugging and the dbg! macro. Excluding those, using lldb inside an IDE was the most popular choice, followed by gdb on the command line:

[PNG] [SVG]

We can get a more detailed breakdown of these results if we include the operating system on which the respondents use a given debugging approach. We examine this from two different angles. The first angle being, "On operating system X, what percent of responses are using debugger Y?". Print debugging and the dbg! macro are consistently the top two yet again, but looking beyond that, things get more interesting. On Linux, using gdb on the command line was the most popular choice by a thin margin, beating lldb in an IDE by only 0.4%. On Windows, Windows Subsystem for Linux (WSL), and macOS, lldb in an IDE was the top pick by at least 6%, making it a very popular choice in general. On Windows, the three least popular choices were the command line debuggers (gdb CLI, lldb CLI, and BugStalker), and on both Windows and macOS the third most popular pick was, "I don't know". Those who were debugging on operating systems not listed (Other) most frequently used some kind of special embedded debugger or gdb:

[PNG] [SVG]

The other angle we can look at these responses from is, "For users of debugger X, what percent of responses are using it on operating system Y?". For most debuggers, Linux makes up the largest portion of uses, ranging from about 45% to about 77%, followed by Windows, then macOS. The most notable exceptions are WinDbg and the Visual Studio debugger, which are primarily used on Windows, and lldb, which is used more on macOS than Windows in an IDE and on the command line:

[PNG] [SVG]

To the 6 respondents who use WinDbg on Linux: we wish you luck!

As for how people actually use their debugger of choice, the aggregate results are not particularly surprising. Roughly 87% of users are using debuggers for stepping line-by-line through programs and a little over half of users are using debuggers to obtain stack traces from hung/crashed processes. Only a quarter of the respondents use a debugger to debug async code. That might be partially caused by the async Rust debugging experience being clumsy and incomplete, or it could just be that users aren't writing much async code:

[PNG] [SVG] [Wordcloud of open answers]

If we break these results down by expertise, we can learn a bit more about usage patterns. As users become more experienced with Rust, their use of debuggers for learning purposes decreases, and they get more stack traces from crashed processes:

[PNG] [SVG]

The final bit of insight into how Rustaceans use debuggers is if they are debugging programs that use Rust alongside other programming languages. For 44% of respondents, the answer is "yes", which is a pretty high number!

As for which languages those are, C dominates the scene at a little over 70%, followed by C++ at about 43% and Python at about 20%:

[PNG] [SVG] [Wordcloud of open answers]

Challenges

Instead of diving right into asking, "what problems do you face when using debuggers?", or something to that effect, we first asked respondents why they decide against using debuggers whenever they do, including for reasons that aren't necessarily "problems with debuggers".

The most commonly reported reason was that it was easier or faster to use logs or print debugging to solve problems, reported by a little over 81% of respondents. This could partially be explained by the open responses, which featured complaints that debuggers were too difficult to set up and/or use (especially on Windows, when dealing with Web Assembly, or in embedded contexts) and sentiment suggesting that small and/or simple problems just don't really need a debugger. It does leave one wondering if the user experience could be made convenient enough to dethrone print debugging, but it seems hard to beat something so intuitive. This is followed by roughly 37% of respondents who write code that Just Works. Fair enough. After that, about 26% of respondents indicated that they've decided not to use debuggers in situations where the language features they were working with had poor support. This is slightly more than issues with standard library types, at about 22%, which is slightly more than issues with external library types, at about 20%:

[PNG] [SVG] [Wordcloud of open answers]

As stepping through code was anticipated to be one of the most common uses for debuggers, we directly asked respondents if they faced any issues when doing so. A little over 51% of respondents said they did! Of those who reported that they experienced issues stepping through code, we asked when they were experiencing issues. Async code was the most common case reported at slightly over 28%, followed by code involving macros at about 23%. The least common case reported was code involving function pointers, at almost 6%:

[PNG] [SVG] [Wordcloud of open answers]

We also directly asked respondents which types in the standard library were hard to work with, if any. This was an open-response question, and reading through the responses, some particularly common complaints were with enums and collections, particularly std::collections::HashMap and std::vec::Vec. This is also visible in the word cloud in the full report.

We asked respondents to indicate which pain points, if any, they have encountered when using debuggers with Rust. At slightly over 74%, poor representation of values was the most common pain point by a decent margin, followed by being unable to print variables at just over 55%:

[PNG] [SVG]

Debugger Visualizers

We asked respondents to indicate if they were library authors, and if so, if they were aware of and using the debugger_visualizer attribute. Nearly 62% of respondents indicated that they were library authors who were not aware of this attribute:

[PNG] [SVG]

For those who indicated that they were library authors who knew about the attribute but did not use it, we also asked why. This represented a much smaller fraction of respondents, so keep that in mind! That said, half of these library authors indicated that they didn't have the time to maintain visualizer attributes, and just under half indicated they didn't know how to write visualizer scripts:

[PNG] [SVG] [Wordcloud of open answers]

For those of you who have been reading this section asking yourself what the debugger_visualizer attribute is, you can read up on it in The Rust Reference: Debugger Attributes. The quick explanation is that the debugger_visualizer attribute can be applied to modules or the crate root to embed files in the debug information which improve the display of values with certain debuggers. The two currently supported file types are Natvis files, used by Microsoft debuggers such as WinDbg, and GDB "pretty printers", which are structured Python scripts used by GDB.

Closing Remarks

Thanks to your participation in this survey, we've gained some great insights about how Rustaceans are using debuggers and what issues they are facing. For example, knowing that such a high number of users are dealing with poor representation of values pairs well with knowing which standard library types are causing issues, knowing that many library authors haven't heard of the debugger_visualizer attribute, and knowing that many of those who have but don't use it either don't know how or don't have time to maintain visualizer scripts.

Looking to the future, the survey results have suggested that there are a few notable ways we could most significantly improve the debugging experience in Rust, such as:

Fixing the way enums are represented by debuggers so they show actual variants
Fixing the way collections (such as HashMap) are represented by debuggers so they show their contents, rather than their implementation details
Fixing the way string types (such as String and CString) are represented by debuggers so they render as text, rather than their implementation details
Improving the async debugging experience, particularly with stack traces
Improving stepping through certain state machines (such as iterators and Futures)
Providing documentation on basic set up and use of some common debuggers

A common suggestion that could resolve those first three points is to use the Debug implementation of types to display them in debuggers. There are challenges to that approach, such as the fact that the Debug implementation is not present in the final binary unless it is actually used somewhere in the program, but it isn't impossible. Notably, this is already supported by the BugStalker debugger (given the same condition that the Debug implementation must actually be used), which some of you first heard about from the survey! It also appears to have some support for async, with plans to expand.

One notable way the debugger experience is currently being improved is through the ongoing Google Summer of Code project improving how we test debug info and visualizer scripts, making it easier to maintain and improve our own visualizer scripts and general compatibility with visualizer scripts without silent breakage or regressions.

Once again, we'd like to thank everyone who took the time to participate in the survey!

Announcing Rust 1.98.1

2026-09-03T00:00:00+00:00

The Rust team has published a new point release of Rust, 1.98.1. Rust is a programming language that is empowering everyone to build reliable and efficient software.

If you have a previous version of Rust installed via rustup, getting Rust 1.98.1 is as easy as:

rustup update stable

If you don't have it already, you can get rustup from the appropriate page on our website.

What's in 1.98.1

Rust 1.98.1 fixes a miscompilation in vtable generation.

In Rust 1.98.0, in some circumstances, rustc would incorrectly generate a trait object vtable with a null pointer where a function pointer should be. This leads to undefined behavior in the emitted code. In some cases this may 'just' cause segfaults due to the null pointer being loaded, but it is possible for it to be justification for arbitrary effects (as is typical for UB).

If you'd like to help us out by testing future releases, you might consider using the beta (rustup default beta) and nightly (rustup default nightly) channels locally and in your CI. Please report any bugs you might come across!

Contributors to 1.98.1

Many people came together to create Rust 1.98.1. We couldn't have done it without all of you. Thanks!

Announcing rustup 1.29.1

2026-09-01T00:00:00+00:00

The rustup team is happy to announce the release of rustup version 1.29.1.

Rustup is the recommended tool to install Rust, a programming language that empowers everyone to build reliable and efficient software.

What's new in rustup 1.29.1

The headlines of this release are:

Concurrency in certain rustup operations has been improved:
- When running rustup update, rustup will first check for possible updates in parallel. pr#4752
- When running rustup component add with multiple components, they will be installed concurrently. pr#4790
Implicit installation of the active toolchain in rustup-init and rustup invocations has been deprecated where deemed unnecessary and will now produce a warning. pr#4840
- Please see our blog post for more details regarding this change.
rustup doc now supports the --serve flag which allows serving the docs over local HTTP. This should help users with containerized browser and/or rustup setups. pr#4986
Installing i686-pc-windows-* host toolchains on 64-bit Windows now requires --force-non-host. pr#4935
rustup-init will no longer leave unexpected files on disk after cancelled installations. pr#4996
A bug has been fixed which might cause Windows installation to fail when using rustup-init.sh. pr#4756
"Target triple" has been renamed to "target tuple" across the project to reflect the new terminology. pr#4743 pr#4827 pr#4834
- Please note that this is not a breaking change in the CLI since the existing options such as --target are not using this terminology.

In addition, rustup now officially supports aarch64-pc-windows-gnullvm as a host platform. pr#4523

Further details are available in the changelog!

How to update

If you have a previous version of rustup installed, getting the new one is as easy as stopping any programs which may be using rustup (e.g. closing your IDE) and running:

$ rustup self update

Rustup will also automatically update itself at the end of a normal toolchain update:

$ rustup update

If you don't have it already, you can get rustup from the appropriate page on our website.

Rustup's documentation is also available in the rustup book.

Caveats

Rustup releases can come with problems not caused by rustup itself but just due to having a new release.

In particular, anti-malware scanners might block rustup or stop it from creating or copying files, especially when installing rust-docs which contains many small files.

Issues like this should be automatically resolved in a few weeks when the anti-malware scanners are updated to be aware of the new rustup release.

Thanks

Thanks again to all the contributors who made this rustup release possible!

Announcing our first Maintainers in Residence

2026-08-26T00:00:00+00:00

We are very happy to announce the Rust Project's first round of Maintainers in Residence: Gen Li (@rami3l), Chris Denton (@ChrisDenton), Alejandra González (@blyxyas), León Liehr (@fmease), and Maintainer Grant recipients: Jason Newcomb (@Jarcho) and Jonas Böttiger (@joboet). These contributors will be funded for their rust-lang maintenance activities for (at least) the following 12 months!

The funding of the Maintainer in Residence (MiR) and Maintainer Grantee roles is possible thanks to generous donations to the Rust Foundation Maintainers Fund (RFMF) from Google, AWS, OpenAI, the Rust Project Leadership Council and also individual sponsors. We also want to thank the people who advocated for maintainer funding within their companies; Tyler Mandry from Google, Niko Matsakis and Jess Izen from AWS and Predrag Gruevski from OpenAI, and also the whole Rust Leadership Council and our funding advisors. If you would like to help us support even more Rust contributors, consider donating to RFMF.

The Rust Foundation has published a press release and a blog post, where you can learn more about the sponsors and the supported contributors.

Read more below to learn about the MiR program, how we chose the funded contributors, and of course who they are!

Background

The Maintainer in Residence program, established in RFC 3931, is designed to provide stable financial support for Rust contributors, so that they can truly focus on crucial maintenance activities. Currently, there are three categories of support that we offer:

Full-time MiR: funded for 5 days/week of Rust Project work
Half-time MiR: funded for ~2.5 days/week of Rust Project work
Maintainer Grant: funded for ~1 day/week of Rust Project work

Funding for this program comes from the Rust Foundation Maintainers Fund, which was launched recently, and the whole program is managed by the Rust Funding team.

When deciding who to fund, we took a systematic approach. First, we looked at Rust teams to understand their maintenance baseline (the smallest number of maintainers they need to ensure a healthy long-term status of the given project or repository), and how far they currently are from that baseline. From there, we identified and prioritized Rust teams who were both critically underfunded, and have a high impact on the language and its users. These teams (in no particular order) were rustdoc, rustup, cargo, compiler, libs, clippy, rustfmt, rust analyzer and mods.

The next step was pairing these teams with maintainers looking for funding. And it turns out that finding such maintainers for some teams turned out to be much more difficult than we originally assumed! For example, some maintainers are already employed, some do not want to be funded, and while we did our best to promote our funding efforts, not everyone looking for funding actually asked us for it. We also realized that some teams on our list have essentially no active members, which makes it tricky to onboard new contributors, even if they would like to help out.

In the end, we decided to start by supporting six contributors, who will help maintain several critical Rust projects and teams and who could start immediately. However, we are not stopping there. Our funding efforts are ongoing, so stay tuned for more MiR announcements in the near future! If you would like to learn more about our process, check out our recent post.

And now, without further ado, let's meet our newly funded maintainers!

Gen Li (@rami3l)

Gen Li (@rami3l) is a full-time MiR focusing on Rustup.

He has been a Rustup team member since 2023 and its lead since 2025. He deeply cares about the facets of Rust that many might have taken for granted, and embodies all attributes we were looking for in a MiR: he wants to take on complex issues, continue mentoring, and work on important Rustup features, among many other things.

Turning volunteering into an actual job has really been an empowering experience so far! I finally have the bandwidth to take a careful look at my inbox and can actually read each message without the fear of missing crucial details while rushing prompt replies, which has really helped me retain the essential compassion as a maintainer. I also get to interact with regular contributors a lot more often. Finally, I can't wait to see what I can come up with in terms of Project Goals :)

Chris Denton (@ChrisDenton)

Chris Denton (@ChrisDenton) is a half-time MiR focusing on the standard library, compiler, Rustup and anything Windows-related.

For the past five years Chris has been bringing his deep knowledge of Windows to help Rust sustain and improve its great cross-platform support. He will be unblocking other contributors in various Windows use cases, performing refactoring and code reviews and implementing new features across several areas of the Project.

Even though it is still early days, I'm feeling pretty optimistic about the health of the Rust Project going forward, thanks to the recent funding efforts.

Alejandra González (@blyxyas)

Alejandra González (@blyxyas) is a half-time MiR focusing on Clippy.

She is a Clippy team member always keen on improving performance and helping new contributors. She will focus on making Clippy faster and also reviewing its pull requests, to help get the ~300 pull request backlog down. Additionally, she is excited to mentor people from the Rust for Linux project to work on Clippy, and fine tune the open peer review system that Clippy started using earlier this year.

Funding is the system that helps me pour my heart into a project without worrying about making ends meet. Having those needs met is a game-changer and boosts my productivity. One of the areas where I want to focus my efforts is mentoring new contributors. If new people coming is the lifeblood of a project, I want to be the cardiologist!

León Liehr (@fmease)

León Liehr (@fmease) is a half-time MiR focusing on rustdoc and the compiler.

He is a member of the rustdoc and compiler teams, who is usually working on the Rust type system or issues related to parsing. He will continue working on complex features that he started a few years ago, and also focus on general maintenance, code reviews, refactoring and mentoring.

Being funded to work on Rust means I can sustainably focus my time and energy on a project I call a passion of mine.

Jonas Böttiger (@joboet)

Jonas Böttiger (@joboet) is a maintainer grantee focusing on the standard library.

He is a musicology student from Germany. When he is not playing the Cello or reading about Fanny Hensel, he applies his research skills to ensure that programs written in Rust run quickly and soundly on all platforms, no matter how quirky the operating system may be. He loves helping contributors write excellent code that they can be proud of; and considers it to be just as much fun as writing it himself.

Getting funding for my work is a dream come true. It will allow me to continue doing the thing I love instead of worrying about whether I should rather invest all that time in a money-earning job with much less positive impact on the world around me.

Jason Newcomb (@Jarcho)

Jason Newcomb (@Jarcho) is a maintainer grantee focusing on Clippy.

He is primarily working on fixing bugs and making it easier to develop and contribute to Clippy. He is also focusing on making the review process as smooth as possible.

Being funded allows me to work on something I care about and want to work on instead of what will get me paid. I'm looking forward to seeing how this will impact Clippy and the Rust project in general.

Conclusion

The contributors presented above will be funded for the next 12 months, though of course we hope that we will be able to extend their support going further, as this program is designed to be for long-term stable maintenance funding. We are very excited about them; each one of them has been with the Project for years, and we are very glad that we can support their maintenance work! All of them have already signed their contracts, so they are already being funded as we speak.

While there are many other Rust contributors who are doing awesome work, and who would also deserve to get proper funding for it, we think that this is a great start. We hope that the awesome work done by the funded maintainers will allow us to promote this program, so that we can fund even more Rust contributors!

We would like to once again sincerely thank everyone who made this possible, especially our sponsors. If you would like to help us fund more maintainers, consider donating to RFMF. You can also sponsor individual Rust contributors directly.

Enabling the next-generation trait solver on nightly

2026-08-21T00:00:00+00:00

After nearly 4 years of active development, the next-generation trait solver is close to stabilization. We are enabling it by default on nightly to surface any remaining issues and plan to stabilize it in the next months. This is the largest single change to the Rust compiler since its initial release. It completely replaces how we prove where-clauses, normalize associated types, and much more. Please try out the latest nightly and open an issue if you encounter any bugs or regressions.

This is an internal component of the compiler. The main benefits of this rework will come in the future. The removal of the old implementation will unblock features such as Type Alias Impl Trait and Return Type Notation, allow us to add new implicit default trait bounds (e.g., Move and Forget), and enable us to fix the remaining type system unsoundnesses.

Even so, this already fixes a huge number of issues. As an underapproximation, we currently know of more than 200 issues on GitHub fixed by this change. This also has a significant impact on compile times; more on that later. When developing on nightly, you may accidentally rely on behavior only supported by the new trait solver.

This is an incredibly big change which results in a non-trivial amount of breakage. Most of these changes are intended improvements to type inference or the removal of undesirable behavior. We are tracking the known issues and breakage in a pinned GitHub issue.

What can I do?

Please update to the latest nightly version by using rustup update nightly and use it to test your existing projects and libraries.

Please tell us if you encounter any breakage, compile-time performance regression, or bad diagnostics. We have not yet spent too much time on error messages for the next-generation trait solver, so we would also appreciate you using this nightly for development to find poor diagnostics and other bugs in our error handling.

If you encounter any issue, take a quick look at the pinned GitHub issue to see if the affected crate is already listed, and if not, please open a new issue! To disable the next-generation trait solver on nightly, you can pass -Znext-solver=coherence to rustc, use RUSTFLAGS=-Znext-solver=coherence, or change your project's .cargo/config.toml configuration file:

[build]
rustflags = ["-Znext-solver=coherence"]

What exactly does this mean?

We will go into more detail about the next-generation trait solver, how we got here, and what it changes when fully stabilizing it. This is a quick summary of its main impact.

`impl Trait` handling

The way opaque types — return-position impl Trait (RPIT), but also the unstable Type Alias Impl Trait (TAIT) and Return Type Notation (RTN) — are handled in the type system has nearly completely changed. This fixes a lot of bugs and edge cases with them and should make their behavior a lot more consistent in general. This change is why the next-generation trait solver is necessary to stabilize TAIT and RTN.

The implementation change mostly does not matter for RPIT as we special-cased impl Trait from the method signature when type checking the method body. This means the only way to observe the old behavior is via recursive function calls. The following snippet errors with the existing implementation, but compiles with -Znext-solver enabled: godbolt

fn foo(b: bool) -> impl Sized {
    if b {
        // The old implementation errored here.
        foo(false) + 1
    } else {
        0
    }
}

Associated types in higher-ranked types

The most impactful change is way we handle associated types referencing bound variables, i.e., lifetimes from a for<'a> binder, for example, the type for<'a> fn(<T as Trait>::Assoc<'a>). While most users don't encounter such types directly, there are widely used crates which do. This change impacts existing code by removing incorrect type inference, such as in bevy and minijinja.

It also fixes a bunch of unnecessary errors like in the following example: godbolt

trait OtherTrait {
    type Assoc<'a>;
}
impl OtherTrait for u32 {
    type Assoc<'a> = &'a u32;
}


trait Trait {}
impl<T: OtherTrait> Trait for (T, for<'a> fn(<T as OtherTrait>::Assoc<'a>)) {}


fn impls<T: Trait>() {}

fn main() {
    // The old implementation failed to prove
    // the where-bound of `impls`.
    impls::<(u32, for<'a> fn(&'a u32))>();
}

Compile-time performance

_{co-authored with jana :3}

We've spent a lot of time on the compile-time performance of the next-generation trait solver. There have been many cases where it performed quadratically or even exponentially slower than the old solver.

Especially the last few weeks were mainly spent on improving performance. This work was shared by many people, with major contributions by Nick Nethercote, jana, Rémy Rakic, and mira.

As part of this effort, Rémy Rakic compared the performance of both implementations for the top 20,000 crates on crates.io. Below you is a visualization of the performance changes over the last two months.

On the left and the right, the major outliers can be found. Note that the sample of crates here is biased towards such crates, because those are more interesting to us. Nearly all crates we tested in the top 20k had effectively the same performance with both implementations.

This graph shows that we've mainly focused our efforts on the negative outliers and made significant progress there. While many of the crates that previously took more than twice as long to compile with the new solver are still slightly slower, our work has made a few of them actually compile faster than with the old solver.

We will continue to improve its performance over the coming months, and there are still a lot of optimization opportunities compared to the existing implementation. My expectation is that, in the long term, nearly all crates will benefit from the next-generation trait solver. I am especially excited about the huge performance benefits for some trait-heavy crates.

As an example, a Chess implementation in Rust's type system hangs with the old implementation while taking a minute with the new one. There are also more practical crates with huge performance benefits, e.g., the datafusion crate compiles more than 8x faster now. For more details about the recent performance work, see this blog post by jana.

Again, thank you for testing with the latest nightly and opening a GitHub issue if you encounter any issues! We're excited to fully stabilize the next-generation trait solver soon.

Supply chain attack on arrayref

2026-08-20T00:00:00+00:00

What happened

On 2026-08-20 at 7:15 UTC we got a report that the proc-macro1 crate was malicious.

The Rust Security Response Team verified this to be the case: the crate had a build script that was downloading a malicious payload.

This crate proc-macro1 and others like it (proc-macro-en, aovine, arone, aronenao, tinymember) have been deleted.

Furthermore, we discovered that the popular arrayref crate had recently been republished and made to depend on this crate, with the most recent versions yanked. We have removed the malicious version and unyanked the maliciously-yanked versions. Other crates by that author (internment, append-only-vec) were also affected so we have done the same for those, and locked the account as a precaution. We do not believe the author of arrayref to be acting maliciously, but their computer or credentials are likely compromised, and we are attempting to contact them.

What you need to do

We recommend you check your local dependencies to ensure these crates were not pulled in. Here are the malicious versions that we deleted from crates.io:

append-only-vec@0.1.9: published at 2026-08-20T07:37:49Z, deleted at 2026-08-20T09:25:24Z. Online for 107 minutes.
arrayref@0.3.10: published at 2026-08-20T07:15:00Z, deleted at 2026-08-20T08:41:40Z. Online for 86 minutes.
internment@0.8.7: published at 2026-08-20T07:34:07Z, deleted at 2026-08-20T09:04:11Z. Online for 90 minutes.
proc-macro1, proc-macro-en, aovine, arone, aronenao, tinymember (any versions).

You can quickly check if these crates have been used locally by going through ~/.cargo/registry/cache with this command:

find ~/.cargo/registry/cache -type f \( \
  -name 'append-only-vec-0.1.9.crate' -o \
  -name 'arrayref-0.3.10.crate' -o \
  -name 'internment-0.8.7.crate' -o \
  -name 'proc-macro1-*.crate' -o \
  -name 'proc-macro-en-*.crate' -o \
  -name 'aovine-*.crate' -o \
  -name 'arone-*.crate' -o \
  -name 'aronenao-*.crate' -o \
  -name 'tinymember-*.crate' \
\) -print

Thanks

We'd like to thank the Research Team at Nextron Systems GmbH for initially discovering this and reporting it to us. We'd also like to thank Emily Albini, Manish Goregaokar, Marco Ieni, Tobias Bieniek, Ubiratan Soares, and Walter Pearce for participating in the response here.

Announcing Rust 1.98.0

2026-08-20T00:00:00+00:00

The Rust team is happy to announce a new version of Rust, 1.98.0. Rust is a programming language empowering everyone to build reliable and efficient software.

If you have a previous version of Rust installed via rustup, you can get 1.98.0 with:

$ rustup update stable

If you don't have it already, you can get rustup from the appropriate page on our website, and check out the detailed release notes for 1.98.0.

If you'd like to help us out by testing future releases, you might consider updating locally to use the beta channel (rustup default beta) or the nightly channel (rustup default nightly). Please report any bugs you might come across!

What's in 1.98.0 stable

Algebraic floating-point methods

The floating-point types f32 and f64 now have "algebraic" methods for addition, subtraction, multiplication, division, and remainder. These allow optimizations on these operations using the algebraic properties of real numbers, even though these properties do not hold with the limitations of floating-point representations. The exact set of optimizations is not specified, but may be similar to the kind of optimization you would see with the -ffast-math option in other languages.

For example, floating-point addition is not associative, so a sum like a + b + c + d must be evaluated in the left-associative order in which it is parsed, like ((a + b) + c) + d. If you write the same sum as a chain of algebraic_add calls, then the compiler is free to reorder it, perhaps like (a + b) + (c + d) to evaluate the partial sums simultaneously. Broader loop-vectorization is often enabled by using these algebraic methods as well.

These methods are non-deterministic, since the compiler is free to choose different optimizations, but they never cause undefined behavior. See the library documentation and the original API change proposal for more details.

Buffered integer formatting

All of the primitive integer types now have a format_into method that takes a &mut NumBuffer<Self> parameter, which is a buffer that is large enough to hold the decimal format of any value of that type. The buffer itself is opaque, but the method returns the formatted &str with a lifetime borrowed from that buffer.

This method also bypasses much of the dynamic dispatch that you would get with buffered write! formatting, which can be a boon to performance. The itoa-benchmark repo now shows that format_into performs similarly to itoa itself, so this could serve as a standard replacement for that dependency and others like it.

Fix interaction between `ManuallyDrop` and `Box`

Prior to Rust 1.96.0, there was a bug in the Rust compiler, which made the following code undefined behavior:

let mut x = ManuallyDrop::new(Box::new(1));
unsafe { ManuallyDrop::drop(&mut x) };
let x = x; // UB!

This is because the compiler considers it undefined behavior to move a Box that has been dropped (deallocated), and ManuallyDrop used to propagate that, such that moving ManuallyDrop<Box<_>> where the box has been dropped would also be considered UB.

In Rust 1.96.0 we fixed this, so this code was no longer UB. In this release we have updated the ManuallyDrop documentation, providing a stable guarantee that this code will continue to not be UB in the future. See ManuallyDrop docs and the related RFC 3336 for more information.

Stabilized APIs

str::substr_range
[T]::subslice_range
core::fmt::NumBuffer
<{integer}>::format_into
Send/Sync for std::process::CommandArgs
{fN}::algebraic_add
{fN}::algebraic_sub
{fN}::algebraic_mul
{fN}::algebraic_div
{fN}::algebraic_rem
NonZero<{integer}>::from_str_radix
String::from_utf16le
String::from_utf16le_lossy
String::from_utf16be
String::from_utf16be_lossy
[T]::strip_circumfix
str::strip_circumfix
Atomic<T>::from_mut
Atomic<T>::get_mut_slice
Atomic<T>::from_mut_slice
std::range::legacy

Other changes

Check out everything that changed in Rust, Cargo, and Clippy.

Contributors to 1.98.0

Many people came together to create Rust 1.98.0. We couldn't have done it without all of you. Thanks!

Rust Blog

Announcing a Maintainer in Residence: Scott Schafer for the Cargo team

Why Cargo?

Introducing Scott Schafer

Conclusion

GitHub Actions leaking secrets when Miri output is cached

Overview

Our fix

Am I affected?

Threat model

Acknowledgements

Be alert: targeted attacks on prominent Rustaceans

What we've seen

What you can do

Rust debugging survey 2026 results

Who Uses Debuggers?

How Are Debuggers Used?

Challenges

Debugger Visualizers

Closing Remarks

Announcing Rust 1.98.1

What's in 1.98.1

Contributors to 1.98.1

Announcing rustup 1.29.1

What's new in rustup 1.29.1

How to update

Caveats

Thanks

Announcing our first Maintainers in Residence

Background

Gen Li (@rami3l)

Chris Denton (@ChrisDenton)

Alejandra González (@blyxyas)

León Liehr (@fmease)

Jonas Böttiger (@joboet)

Jason Newcomb (@Jarcho)

Conclusion

Enabling the next-generation trait solver on nightly

What can I do?

What exactly does this mean?

impl Trait handling

Associated types in higher-ranked types

Compile-time performance

Supply chain attack on arrayref

What happened

What you need to do

Thanks

Announcing Rust 1.98.0

What's in 1.98.0 stable

Algebraic floating-point methods

Buffered integer formatting

Fix interaction between ManuallyDrop and Box

Stabilized APIs

Other changes

Contributors to 1.98.0

`impl Trait` handling

Fix interaction between `ManuallyDrop` and `Box`