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Making Rust supply chain attacks harder with Cackle

If you want a slightly shorter read, skip to Introducing Cackle.

A hypothetical story about Alex

Alex is a software engineer who has built a tool which she licences to her customers. She only has a small number of clients, but they like her tool. She built her tool using Rust, with about 20 direct dependencies from crates.io. When you count indirect dependencies, her tool has about 250 dependencies.

One of those indirect dependencies is a crate named foobar, which was written by someone named Chris. Chris wrote foobar a few years ago, but has lost interest in maintaining it.

Someone called Bob has filed a couple of PRs against foobar and is now asking when they might get merged and if the project is still maintained. Bob says that they’d be happy to maintain the crate if Chris is too busy. Bob seems enthusiastic, so Chris adds Bob as an owner.

Some months go by and Alex is fixing a bug that one of her clients noticed. After fixing the bug, she runs cargo update, runs the tests, does some manual testing, then pushes out the updated version of her tool to her clients. The updated version of her tool includes an updated version of the crate foobar.

A week later she gets a call from one of her clients who is extremely upset. It seems that the client’s user database has been leaked and the attackers are threatening to publish it if a ransom isn’t paid. Her client has determined that Alex’s tool is sending data to an unknown address on the Internet.

After some investigation, Alex finds some code in the new version of foobar that is doing this. She pins an old, unaffected version of the foobar crate and does a new release, but the damage to her small business and her reputation is already done.

Supply-chain attacks

The story about Alex is an example of a supply-chain attack. There are many ways something like this could happen:

This kind of thing hasn’t happened much yet in the Rust ecosystem, but as it grows, it’s expected to happen more often. It already happens semi-regularly in other larger ecosystems like node.js and in Python’s package systems.

Practices to help prevent supply-chain attacks

There are numerous things you can do to help prevent supply-chain attacks:

For crate authors there are some additional steps you can take:

Introducing Cackle aka cargo-acl

Cackle is a code ACL checker and is an additional tool to help make supply-chain attacks harder. It’s intended to be used in addition to the above approaches. Cackle is configured via cackle.toml that sits alongside Cargo.toml. In the configuration file, you can define classes of APIs, such as “net”, “fs” (filesystem) and “process” that you’d like to restrict. You then say which crates that you depend on are permitted to use these APIs. When run, Cackle checks for any crates in your dependency tree that are using restricted APIs that they’re not permitted to use.

An API definition says what names are included or excluded from that API. For example, we might define the “process” API as follows:

include = [
exclude = [

Exclusions take precedence over inclusions, so should be more specific. Here we’re defining an API named “process” and classifying any functions in the std::process module as belonging to it. We then exclude std::process::exit. So a reference to std::process::Command::new would count as using the process API, but a reference to std::process::exit would not.

We can then allow specific packages to use this API. For example:

allow_apis = [
allow_unsafe = true

This says that the rustyline package is allowed to use filesystem APIs and also allowed to use unsafe code.

In the case of Alex’s story, had she been using Cackle, then the foobar crate might have been flagged as now using the “net” API where previously it wasn’t.

Installing Cackle

For the time being, Cackle only supports Linux. Assuming you’ve already got Rust installed, you can run:

cargo install --locked cargo-acl

Building an initial config

Cackle has a built-in terminal UI that helps with creation of your cackle.toml. We’ll use that to create our initial configuration. From the directory containing your Cargo.toml, run:

cargo acl

The problems pane shows problems that have been detected so far with the permissions used by your dependencies. Initially, it also shows action items that help with creating your configuration.

Screenshot of missing config in UI

We select a problem and press ‘f’ to show possible fixes.

Screenshot of fixes for missing config in UI

Here we can see two possible initial configurations that we can create. We select that we’d like to use the recommended initial configuration and press ‘f’ to apply the fix.

Screenshot of selecting a sandbox

Next, the UI will ask us to select what kind of sandbox we’d like to use. At the moment, the only supported sandbox is Bubblewrap. The sandbox is used for running build scripts, for running rustc (and thus procedural macros) and for running tests. APIs used by each binary are checked by cackle before they get run, so depending on how carefully you’re checking those API usages, you may decide not to worry about sandboxing.

At this point, we’ve imported APIs that restrict network access, filesystem access and command access via the standard library. We haven’t however restricted similar APIs that might be provided by third-party crates in our dependency tree. For example, tokio can be used to perform network access, but we haven’t classified any of its APIs as doing so.

Third-party crates can export cackle API definitions. If any do, then the cackle UI will ask us if we’d like to import those API definitions. While cackle is fairly new however, it’s expected that we’ll need to write such API definitions ourselves. We might write a “net” API definition for tokio as follows:

include = [

Here we’re saying that references to anything in the tokio crate’s net module should be classified as a use of the net API.

We can manually edit our cackle.toml to add this API definition. It will be merged with the definition of the net API for the standard library that is built into Cackle and which we imported when we created our initial configuration.

Cackle will now proceed to build your crate and its dependencies. As the build proceeds, cackle will analyse object files, executables and source code to see what APIs are used from where and which crates use unsafe. As problems are found, they’ll be added to the “problems” pane in the UI.

Screenshot of problem list and package details

Details about the package involved are shown in the bottom pane. You can use this to help understand what the package does, which can be useful for deciding if it’s reasonable for it to use a particular API.

If you’d like to see how a package was included, you can view the tree from current problem’s package to your package by pressing ‘t’.

Screenshot of a package tree

For API usages and unsafe code, you can press ‘d’ to see further details of each usage location of that API or unsafe code.

Screenshot of UI showing unsafe usage locations

If you’re happy for the crate to use that API or unsafe, you can press ‘f’ to see available fixes to the configuration file.

Screenshot of fix to allow unsafe

Press ‘f’ again to apply the selected fix.

Similar to the unsafe usages, the usage locations for a disallowed API can be shown by pressing ‘d’.

Screenshot of disallowed API usage locations

Here we can see that the build script for the quote crate is using the process API by referencing std::process::Command.

Like with other problems, we can press ‘f’ to see available fixes.

Screenshot of fix to allow an API

We have a few options for allowing an API usage. The quote crate used the process API from its build script. We can allow just this, which is the first available fix.

Alternatively, we might choose to allow the quote crate to use the process API, but only as part of build scripts. This would mean that code in for example quote’s lib.rs could use the process API if that code was then used by a build script from another package. It would also allow quote’s own build.rs to use the process API.

Lastly we might allow quote to use the process API regardless of what kind of binary is being built.

The bottom pane shows a description of the change being made as well as a diff of your cackle.toml.

Only API usages in reachable code are considered. If you’d like to see how the code is reachable you can press ‘b’ to get a backtrace showing a path of function references from main to the function that used the API.

Screenshot of backtrace for an API usage

Here we can see that the ripgrep build script is calling clap’s App::gen_completions, which calls Parser::gen_completions which is what’s using File::create.

Note that this isn’t a runtime backtrace - the build script hasn’t been executed yet. It’s a hypothetical backtrace built from the graph of what functions reference what other functions. Press escape to leave the backtrace.

Other kinds of problems that cackle might detect with your dependencies are:

Once all problems have been resolved, Cackle will exit.

We might like to integrate Cackle into our CI. To do so, we’d run:

cargo acl -n

And if we’d like to also then run the tests under cackle, we’d do:

cargo acl -n test

In a github action, we might do this as follows:

name: cackle
on: [push, pull_request]

    name: Cackle check and test
    runs-on: ubuntu-latest
      - uses: actions/checkout@v3
      - uses: dtolnay/rust-toolchain@stable
      - uses: cackle-rs/cackle-action@latest
      - run: cargo acl -n
      - run: cargo acl -n test

This will do a non-interactive check of our dependencies against the configuration. If any problems are encountered, details will be printed and it will exit with a failure status.

If your Cargo.lock is checked into your repository, you might like to add rm Cargo.lock to your CI before running cargo acl, that way we’ll be checking the latest semver-compatible versions of your dependencies.

How it works

When you run cargo acl, Cackle invokes cargo build, but wraps rustc, the linker and any build scripts. As the build progresses, the wrappers communicate back to the parent cackle process, which analyses the build artefacts in order to determine what APIs are being used. It does this by parsing the object files to determine what functions reference what other functions. It also parses the debug information in the linked executable in order to determine the source locations for each reference. Source files are then mapped back to the package that provided that source file via deps files written by rustc.

One nice thing about the fact that Cackle analyses the final executable is that dead code is not considered with regard to API usage. So for example if you depend on the image package to encode PNGs, but don’t use functions from the image crate that read or write files, then those functions shouldn’t go into the executable, which means Cackle won’t classify the image package as using filesystem APIs. This means that if later, the image package started doing filesystem access from a function that wasn’t previously, it would be flagged as using a disallowed API.


There are of course ways to circumvent Cackle and use an API without detection.

One way is if your configuration is incomplete. For example, if your crate depends on tokio, but you don’t add tokio::net to the includes for api.net then another of your dependencies could use tokio::net to perform network access without being detected. Cackle tries to mitigate this to some extent by looking for top-level modules with the same name as one of your APIs. So in the case of tokio, Cackle will suggest that you add tokio::net to the net API.

Once you’ve granted a package permission to use an API, it has carte blanche to do whatever it likes with that permission. Cackle provides strongest protection where crates have been granted no special permissions. Similarly, once a crate is granted use of unsafe, it could in theory do just about anything with it. That said, using unsafe to say perform network access without linking to C code, is harder than just using Rust’s std::net APIs, so we’re at least making it harder for a would-be attacker.

More problematic is that platform-specific or config-specific malicious code might be missed. For example, malicious code that is only present on Windows or Mac would be missed since Cackle currently only works on Linux.

Lastly, there are undoubtedly bugs that might allow API usage to go undetected.

Observations from running on a few different binaries

When running cackle on a few popular binaries published to crates.io, what I’ve observed is that usually, a bit under half of crates need no special permissions. This is great, because if at any point any of these crates start using a restricted API or unsafe, we should notice.

Of the crates that need special permissions, by far the most commonly required is unsafe. Most crates using unsafe provide some low level API that can’t be provided, or can’t be provided efficiently without unsafe. I did however notice a number of crates where it’s not clear why they would need unsafe.

Filesystem and process APIs are less used than unsafe, but still used a moderate amount, especially from build scripts.

Network APIs are relatively uncommon and for a program that doesn’t talk over the network - e.g. Cackle itself or something like ripgrep, I’d expect to see no dependencies using network APIs. Indeed, for these two crates, this is what we see.

Future plans

More granular sandboxing of proc macros

Right now, proc macros are sandboxed by virtue of Cackle running rustc in a sandbox. However this means that all your proc macros are granted the same sandbox permissions. So if you have one proc macro in your dependencies that needs network access, you need to grant this to all proc macros. Fortunately most proc macros don’t need any network access, so this isn’t too much of a problem in common cases.

If rustc at any point gets support for running proc macros as subprocesses rather than by loading dylibs into the main rustc process, then we can sandbox each proc macro individually which will allow us to fix this.

Runtime analysis

At the moment, we’re mostly only doing static analysis. It could be interesting to add some runtime analysis to Cackle. Specifically, we could trace the syscalls made by build scripts (and ideally also proc macros) and see what file paths they try to access and what subprocesses they spawn.

Support for more platforms

As mentioned previously, if we can’t work on Mac and Windows, then any attacks that target only those platforms will go undetected. Making it work on Mac is hopefully not too much work, since Mac uses the same debug information format as Linux. Windows is a little harder, since it uses a different format for debug info. There is a crate that parses it though, so it’s probably doable. Help is needed with both as I only have Linux.


Cackle won’t (and can’t) stop all supply-chain attacks. However, hopefully it can be a tool that can at least make it substantially harder for an attacker to sneak something malicious into your dependencies without you noticing.


Huge thank you to Embark Studios and Johan Andersson for their generous sponsorship.