This looks interesting and useful (I haven't tried it yet), but it is important to realize that every single useful Rust program has unsafe. Every single one. Why? Stdlib usage is full of it, and it must be by definition of what it does. In the same way you can't have a useful program without some side effects, so also you can't really have a useful program without doing some level of I/O and FFI, and I/O/FFI is always going to use unsafe under the covers.

That said, there is value in limiting your own unsafe use, and there might be value in limiting unsafe in the crates you use. However, this is really a question of "who do I trust to use unsafe? How much? Under what circumstances?" and NOT "is okay to have any unsafe?" because any useful program will contain a lot of unsafe if traced far enough in its call paths.

I think what would matter from this kind of measure is whether a project's use of unsafe actually has undefined behavior. Like the number of unsafe blocks is not really my concern as much as what the unsafe blocks are doing. If you build a single faulty abstraction via unsafe, anything that uses it is broken.

In my projects, it usually comes down to a scenario like needing to write inline assembly or invoke a foreign function, where there are close to zero guarantees the language can give me.

I worry a little that perfectly cromulent Rust will get a bad name when the culture tends towards “unsafe is bad.”

Is there real value in these statistics vs. an approach where the measure is test coverage of unsafe blocks?

In my projects, it usually comes down to a scenario like needing to write inline assembly or invoke a foreign function, where there are close to zero guarantees the language can give me.

I worry a little that perfectly cromulent Rust will get a bad name when the culture tends towards “unsafe is bad.”

Is there real value in these statistics vs. an approach where the measure is test coverage of unsafe blocks?

I agree that unsafe isn’t evil and shouldn’t be “avoided at all costs”, especially when using unsafe could be eg eliminated by the compiler (very common usage, actually!) or give you far superior codegen or code complexity.

But test coverage of unsafe blocks is not a meaningful metric. The best automated solution is standalone Miri runners exercising all branches of the code (via tests or otherwise) because tests on their own won’t catch things like out of counts reads or heap corruption unless you get lucky.

Penalizing the stdlib for using `unsafe` would be extremely counter-productive, because you could almost trivially remove all `unsafe` in the stdlib by moving those "unsafe" operations into codegen emitted by compiler (which is essentially how every other memory-safe language under the sun works, including Java, Python, etc.). Voila, no more unsafe in the stdlib... except now you have exactly the same code existing in a form that's both harder to inspect and doesn't benefit from the bevy of tools that exist to audit unsafe blocks in regular Rust code, meaning you have an implementation that's less safe in practice. And outside of the code contained in the stdlib, the majority of Rust crates don't use `unsafe` at all (exact proportion varying by domain; e.g. embedded use cases will probably all use `unsafe` somewhere).

cargo-geiger ☢️

A tool that lists statistics related to the usage of unsafe Rust code in a Rust crate and all its dependencies.

This cargo plugin was originally based on the code from two other projects:

Installation

Try to find and use a system-wide installed OpenSSL library:

cargo install --locked cargo-geiger

Or, build and statically link OpenSSL as part of the cargo-geiger executable:

cargo install --locked cargo-geiger --features vendored-openssl

Alternatively pre-built binary releases are available from GitHub releases.

Usage

Navigate to the same directory as the Cargo.toml you want to analyze.
cargo geiger

Intended Use

This tool is not meant to advise directly whether the code ultimately is truly insecure or not.

The purpose of cargo-geiger is to provide statistical input to auditing e.g. with:

The use of unsafe is nuanced and necessary in some cases and any motivation to use it is outside the scope of cargo-geiger.

It is important that any reporting is handled with care:

Output example

Example output

Known issues

See the issue tracker.

Libraries

Cargo Geiger exposes three libraries:

cargo-geiger - Unversioned and highly unstable library exposing the internals of the cargo-geiger binary. As such, any function contained within this library may be subject to change.
cargo-geiger-serde - A library containing the serializable report types
geiger - A library containing a few decoupled cargo components used by cargo-geiger

Changelog

See the changelog.

Why the name?

https://en.wikipedia.org/wiki/Geiger_counter

Unsafe code, like ionizing radiation, is unavoidable in some situations and should be safely contained!

I agree about test coverage. I’d say it’s less bad but still doesn’t necessarily mean anything rigorous.

Short of formal verification, which I think is often going to be unreasonable, we generally have a spectrum of “less bad” options.