Catching panics in dependencies

Ryan James Spencer

March 27 2020, 11:55AM

Having crates panic on you feels random because the specific conditions that trigger the panic may not seem clear. Having external crates bring down your program is a pain, but there is currently no static analysis tool to help us easily find panics in external crates. You can get pretty close with fuzzing, though!

The format for fuzzing is generally:

  1. Get some random bytes
  2. Shape them into the right shape needed for our interface
  3. Run the interface with the random data and see if it blows up

Some fuzzing libraries take the input that leads to a crash and continually mutates it to find other cases where it might crash as well. I'm going to use cargo fuzz to reproduce finding a panic in an external dependency. Here's a case taken from the rust-fuzz organisations trophy case. I'll use num v0.1.31 which panics when parsing BigInts as per the linked issue. I'll add it to the Cargo.toml of our project:

[dependencies]
num = "=0.1.31"

Then, I'll install cargo fuzz.

cargo install cargo-fuzz

then in our project, we can initialize cargo fuzz.

cargo fuzz init

Which gives me a single fuzz target which I can rename if I want. I'll rename it to parse.rs so the name is parse when listed but you can call it anything that fits. To do this I will change the fuzz subdirectories Cargo.toml. A [[bin]] key is in there that designates what targets are available. Since we're moving fuzz_target_1 to parse, we have to do this in the TOML file since the cargo fuzz subcommand doesn't have this ability, but we can use the cargo fuzz add subcommand to add extra targets with custom names in the future.

The new key should look like this

[[bin]]
name = "parse"
path = "fuzz_targets/parse.rs"

with the rest of the fuzz/Cargo.toml left as-is.

Then we can write a simple case for our function. This can be a little tricky because the fuzzer will hand us raw bytes and it's up to us to shape them into the right format, whether that be a struct, i64, f32, and so on. For this case I'll make a string from the random bytes and feed it into our project's parse function:

#![no_main]
use our_project::parse;
use libfuzzer_sys::fuzz_target;

fuzz_target!(|data: &[u8]| {
    if let Ok(s) = std::str::from_utf8(data) {
        let _ = parse(&s);
    }
});

the parse function might look something like this (lifted from the issue):

use num::Num;

pub fn parse(str: &str) {
    num::BigUint::from_str_radix(str, 10);
}

and then I'll run the fuzzer for this target:

cargo fuzz run parse

This finds offending strings similar to the trophy case example quite quickly:

<snip>
────────────────────────────────────────────────────────────────────────────────

Failing input:

        fuzz/artifacts/parse/crash-00a78c613a00b21ea723de12e16f32a0385d9bdc

Output of `std::fmt::Debug`:

        [48, 43, 49]

Reproduce with:

        cargo fuzz run parse fuzz/artifacts/parse/crash-00a78c613a00b21ea723de12e16f32a0385d9bdc

Minimize test case with:

        cargo fuzz tmin parse fuzz/artifacts/parse/crash-00a78c613a00b21ea723de12e16f32a0385d9bdc

────────────────────────────────────────────────────────────────────────────────

Error: Fuzz target exited with exit code: 77

Hang on, that debug output doesn't look like the offending case mentioned in the issue we linked above from the trophy case, does it? Again, this is because it's the raw bytes. A handy trick I use when running regressions is to utilize the stored failing input. In this case it's stored at fuzz/artifacts/parse/crash-00a78c613a00b21ea723de12e16f32a0385d9bdc per the output above. We can write a regression that uses this directly with the macro include_bytes!:

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn fuzz_regression_01() {
        let data = include_bytes!(
            "../fuzz/artifacts/parse/crash-00a78c613a00b21ea723de12e16f32a0385d9bdc"
        );
        let s = std::str::from_utf8(data).expect("should be able to make test input");
        dbg!(&s);
        parse(&s);
    }
}

You can run the tests the usual way with cargo test which should panic. I've lobbed a dbg! in there of the transformed raw bytes into the string. When the test panics we see:

running 1 test
test tests::fuzz_regression_01 ... FAILED

failures:

- tests::fuzz_regression_01 stdout -
[src/lib.rs:17] &s = "0+1"
thread 'tests::fuzz_regression_01' panicked at 'called `Result::unwrap_err()` on an `Ok` value: 1', /home/rjs/.cargo/registry/src/github.com-1ecc6299db9ec823/num-0.1.31/src/bigint.rs:388:25
note: run with `RUST_BACKTRACE=1` environment variable to display a backtrace

failures:
    tests::fuzz_regression_01

test result: FAILED. 0 passed; 1 failed; 0 ignored; 0 measured; 0 filtered out

error: test failed, to rerun pass '--lib'

And there is our offending input, "0+1"! Beautiful. I can use these specific cases in issues for upstream projects instead of wasting time trying to find exact cases on my own. Switching to num v0.1.41 avoids the panic and we can run cargo fuzz again. We can also change the fuzzing library used, such as libfuzz or afl, which cargo fuzz supports. You can also use honggfuzz via the honggfuzz.rs library over at honggfuzz-rs. Different fuzzers have different features and guarantees but most are relatively easy to write targets for and get fuzzing so it can pay to try a few alternatives to see if other cases are lurking around.

Before I go, I want to talk about a related concept known as "property based testing" where we define how random data should be generated. We'll dig more into that another day but for now, it suffices to say that both approaches help to drive out test cases you might not have imagined! I am in the habit of making my own regression suites from cases I find from either method, but you don't have to do this as some fuzzers and property-based testing libraries will keep a "corpus" of data that has failed that it can try again on future runs, but I find it helpful to have the regressions as unit tests so there is a fast way to verify earlier failures aren't still happening.


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