| name | review-crate |
| description | Deep audit of a Rust crate for vulnerabilities, bugs, unfinished work, inconsistencies, duplicate code, and oversights. Works on the current crate or a specified path. |
| disable-model-invocation | true |
| allowed-tools | Bash(cargo *), Bash(git diff *), Bash(git log *), Bash(git show *), Bash(wc *), Read, Grep, Glob, Task |
| argument-hint | [path/to/crate] |
Rust Crate Audit
You are performing a thorough audit of a Rust crate. Your goal is to find every vulnerability, bug, unfinished piece of work, inconsistency, and oversight before it ships. Leave no stone unturned.
Step 1: Locate the crate
Parse $ARGUMENTS:
- If a path is provided, use it as the crate root.
- If empty, use the current working directory.
Verify it's a valid Rust crate by checking for Cargo.toml. If not found, stop and ask the user.
Step 2: Understand the crate
Read Cargo.toml to understand:
- Crate name, version, edition
- Dependencies (look for outdated, unmaintained, or suspicious crates)
- Feature flags and their implications
- Build scripts (
build.rs) if any
Read CLAUDE.md, README.md, or top-level documentation if present to understand intent and architecture.
Read src/lib.rs or src/main.rs to get the module tree. Then read each module's mod.rs or top-level file to build a mental map of the crate's structure before diving into details.
Read the all rust files (src/*.rs) to make sure everything is in the context when you are reasoning.
Step 3: Run the compiler's checks
Run these commands and capture output. Do NOT fix anything, just collect findings:
cargo fmt --check 2>&1
cargo clippy --all --benches --tests --examples --all-features -- -W clippy::all -W clippy::pedantic -W clippy::nursery 2>&1
cargo test --all-features 2>&1
If any of these fail, record the failures as findings. If cargo test has ignored tests, note which ones and why.
Step 4: Scan for unfinished work
Search the entire src/ tree for:
todo!
unimplemented!
fixme
FIXME
TODO
HACK
XXX
SAFETY:
stub
placeholder
temporary
For each match:
- Is it in production code or test code?
- Is it a genuine incomplete feature or a deliberate placeholder?
- Is there a tracking issue referenced?
- Could this panic at runtime?
Any todo!() or unimplemented!() in non-test code is High severity (runtime panic).
Step 5: Audit for vulnerabilities and unsafe code
5a. Unsafe code
Search for all unsafe blocks. For each one:
- Is the safety invariant documented with a
// SAFETY: comment?
- Is the invariant actually upheld by the surrounding code?
- Could the unsafe block be replaced with a safe alternative?
- Are there any pointer dereferences, transmutes, or FFI calls?
5b. Unwrap and panic paths
Search for .unwrap(), .expect(, panic!, unreachable! in non-test code. For each:
- Can this actually panic in production?
- Is there a code path that reaches this with None/Err?
- Should it be replaced with proper error handling (
?, .ok(), .unwrap_or_default())?
5c. SQL and injection vectors
Search for string formatting used in SQL queries, shell commands, or HTML:
format! used near .execute(, .query(, Command::new(
- String interpolation in query construction vs parameterized queries
- User input flowing into file paths (
Path::new, std::fs::)
5d. Cryptographic issues
If the crate uses crypto:
- Are comparisons constant-time? (look for
== on secrets/hashes vs subtle::ConstantTimeEq)
- Is randomness from
OsRng / thread_rng and not a fixed seed?
- Are keys/secrets zeroized after use? (
secrecy, zeroize crates)
- Are deprecated algorithms used? (MD5, SHA1 for security, RC4, DES)
5e. Resource exhaustion
- Are there unbounded allocations? (
Vec growing from user input without limits)
- Are there unbounded loops? (retry loops without max attempts)
- Are file reads bounded? (
std::fs::read_to_string on user-provided paths)
- Are timeouts set on all network operations?
- Are there connection/resource leaks? (opened but never closed, missing
Drop)
5f. Error handling
- Are errors swallowed silently? (
let _ = ..., .ok() discarding errors that matter)
- Do error types carry enough context to debug in production?
- Are there error type mismatches? (returning generic
anyhow::Error where a typed error would prevent confusion)
- Is
thiserror or the crate's error pattern used consistently?
Step 6: Check for inconsistencies
6a. Naming conventions
- Are types, functions, modules named consistently? (e.g., mixing
get_ and fetch_, create_ and new_)
- Do similar operations follow the same patterns?
- Are module-level re-exports (
pub use) consistent?
6b. Duplicate or near-duplicate code
Look for:
- Functions that do nearly the same thing with minor variations (candidates for generics or shared helpers)
- Repeated error mapping patterns that should be extracted
- Copy-pasted SQL queries or string templates with slight differences
- Identical struct definitions or conversion logic in different modules
6c. API consistency
- Do similar functions take arguments in the same order?
- Are return types consistent? (e.g., some functions return
Option<T>, similar ones return Result<T, E>)
- Are visibility modifiers consistent? (
pub where it should be pub(crate), or vice versa)
- Do builder patterns follow the same conventions throughout?
6d. Dead code and unused items
- Are there functions, structs, or modules that nothing references?
- Are there
#[allow(dead_code)] annotations that should be investigated?
- Are there imports that are unused (beyond what clippy catches)?
- Are there feature-gated items where the feature is never enabled?
Step 7: Inspect for change oversights
7a. Partial refactors
- Are there old patterns coexisting with new patterns? (e.g., some files use the old approach, some the new)
- Are there renamed types/functions where some call sites still use the old name via a compatibility alias?
- Are there comments referencing behavior that no longer exists?
7b. Trait implementation gaps
- If a trait is defined, do all intended types implement it?
- Are there
impl blocks that look incomplete (some methods implemented, others missing)?
- Are
Default implementations sensible?
- Are
Display, Debug, Clone, PartialEq derived where they should be?
7c. Test coverage gaps
- Are there public functions without any test?
- Are there error paths without tests?
- Are there recently-changed functions where the tests still assert old behavior?
- Are there
#[cfg(test)] modules that have been emptied or commented out?
7d. Documentation drift
- Do doc comments match actual function behavior?
- Are examples in doc comments still valid and compilable?
- Are module-level docs up to date with the current module structure?
Step 8: Dependency audit
Review Cargo.toml and Cargo.lock:
- Are there duplicate versions of the same crate in the lock file? (potential version conflicts)
- Are there dependencies with known security advisories? Run
cargo audit if available.
- Are there heavy dependencies used for trivial functionality? (e.g., pulling in
tokio full features when only a timer is needed)
- Are dependency features minimal? (avoiding pulling in unused sub-crates)
Step 9: Present findings
Compile all findings into a structured report. Group by severity, then by category.
Format
For each finding:
### [Severity] Category: One-line summary
**Location:** `file_path:line_number`
**Category:** Vulnerability | Bug | Unfinished | Inconsistency | Duplicate | Oversight | Style
**Description:**
Detailed explanation of the issue, why it matters, and how it could manifest.
**Suggested fix:**
Concrete suggestion with code if applicable.
Severity levels
- Critical: Security vulnerability, data loss, or crash in production
- High: Bug that causes incorrect behavior,
todo!()/unimplemented!() in prod code, or missing validation on trust boundaries
- Medium: Inconsistency, duplicate code, incomplete error handling, missing tests for important paths
- Low: Naming inconsistency, unnecessary complexity, documentation drift, minor dead code
- Nit: Style preference, optional improvement
Summary table
End with a summary table:
| # | Severity | Category | File:Line | Finding |
|---|
And a final tally: X Critical, Y High, Z Medium, W Low, V Nit.
Rules
- Read every file before reporting on it. Never guess about code you haven't seen.
- Be specific. "This might have issues" is worthless. "Line 42 calls
.unwrap() on a Result that returns Err when the DB connection is dropped" is useful.
- Distinguish certainty levels: "this IS a bug" vs "this COULD be a bug if X".
- Don't invent problems to look thorough. If the code is solid, say so.
- Focus on substance over style. Don't flag formatting unless it causes real confusion.
- Respect existing project conventions (check CLAUDE.md). Don't flag patterns the project explicitly endorses.
- When in doubt about severity, round up.
- For large crates (>50 files), prioritize: core logic > public API > internal utilities > tests > examples.
- Use the Task tool to parallelize file reading across modules when the crate is large.
- Do NOT fix anything. This is a read-only audit. Report findings for the user to action.