Vector Forge
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Written by AutoGineer from the skill’s own files, not by the author
Vector Forge provides a systematic methodology to improve cryptographic test suites by using mutation testing to identify coverage gaps. It guides users through discovering implementations, establishing a baseline, performing graph-informed escape analysis, and generating targeted test vectors. By comparing mutation kill rates before and after, it provides concrete evidence of test suite effectiveness, ensuring that both valid and invalid inputs are rigorously handled.
What it does
- Identifies code paths missed by existing test suites using mutation testing.
- Uses call-graph analysis to prioritize escaped mutants by security impact.
- Generates targeted test vectors to close coverage gaps and kill surviving mutants.
- Validates test vector effectiveness through before-and-after mutation kill rate comparisons.
- Supports cross-implementation verification to ensure consistency across different codebases.
- Provides a structured reporting template for documenting test suite improvements.
When to use it
- When generating or improving test vectors for cryptographic algorithms.
- When evaluating the concrete coverage of an existing test suite.
- When identifying implementation code paths that lack test coverage.
- When creating cross-implementation test suites for cryptographic primitives.
Advantages
- Systematically uncovers blind spots in cryptographic test suites.
- Prioritizes security-critical code paths for testing.
- Provides measurable proof of test suite improvement.
- Reduces reliance on manual analysis for identifying missing test cases.
- Ensures both positive and negative test assertions are implemented.
Usage examples
- “How can I improve the test coverage for my BLS12-381 implementation?”
- The agent will guide you through running a baseline mutation test, using the call graph to identify escaped mutants, and generating specific test vectors to target those uncovered paths.
- “My cryptographic library has high line coverage but still misses bugs. What should I do?”
- The agent will recommend using Vector Forge to perform mutation testing, which reveals logic gaps that standard line coverage metrics fail to detect.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/trailofbits/vector-forge/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip vector-forge.zip -d .agents/skills
Documentation by Trail of Bits
Vector Forge
Uses mutation testing to systematically identify gaps in test vector coverage, then generates new test vectors that close those gaps. Measures effectiveness by comparing mutation kill rates before and after.
When to Use
Generating test vectors for cryptographic algorithms or protocols
Evaluating how well existing test vectors cover an implementation
Finding implementation code paths that no test vector exercises
Creating Wycheproof-style cross-implementation test vectors
Measuring the concrete coverage value of a test vector suite
When NOT to Use
No implementations exist yet (need code to mutate)
Single trivial implementation with no edge cases
Testing application logic rather than algorithm implementations
The algorithm has no public test vectors to compare against
Prerequisites
trailmark installed — if
uv run trailmarkfails, run:uv tool install trailmark
Python snippets: uv run --with trailmark python - (a tool env is not importable)
- At least one implementation of the target algorithm in a
language with mutation testing support
- A test harness that consumes test vectors and exercises
the implementation
- A mutation testing framework for the target language
---
## Rationalizations to Reject
| Rationalization | Why It's Wrong | Required Action |
|-----------------|----------------|-----------------|
| "We have enough test vectors" | Mutation testing proves otherwise | Run the baseline first |
| "The implementation's own tests are sufficient" | Own tests often share blind spots with the impl | Cross-impl vectors catch different bugs |
| "FFI crates can be mutation tested at the binding layer" | Mutations to wrappers don't affect the underlying impl | Mutate the actual implementation language |
| "Timeouts mean the mutation was caught" | Timeouts are ambiguous — could be killed or alive | Resolve timeouts before drawing conclusions |
| "All mutants are equivalent" | Most aren't — verify by reading the mutation | Classify each escaped mutant individually |
| "Checking valid vectors is enough" | Permissive mutations survive without negative assertions | Assert rejection for every invalid vector |
| "Manual analysis is fine" | Manual analysis misses what tooling catches | Install and run the tools |
---
## Workflow Overview
Phase 1: Discovery → Find implementations to test ↓ Phase 2: Harness → Write/adapt test vector harness for each impl ↓ Phase 3: Baseline → Run mutation testing with existing vectors ↓ Phase 4: Escape Analysis → Classify escaped mutants by code path ↓ Phase 5: Vector Gen → Create test vectors targeting escapes ↓ Phase 6: Validation → Re-run mutation testing, compare before/after ↓ Output: Coverage Report + New Test Vectors
---
## Phase 1: Discovery
Find implementations of the target algorithm. Look for:
1. **Pure implementations** in high-level languages (Go, Rust, Python)
— these are the best mutation testing targets
2. **FFI wrapper crates** — identify these early so you don't waste
time mutating wrapper glue code
3. **Reference implementations** — useful for cross-verification but
may not be the best mutation targets
For each implementation, note:
- Language and mutation testing framework
- Whether it's pure code or FFI wrappers
- Existing test suite size and coverage
- Which API surface the test vectors will exercise
### Implementation Type Classification
| Type | Mutation Value | Example |
|------|---------------|---------|
| Pure implementation | High | zkcrypto/bls12_381 (Rust), gnark-crypto (Go) |
| FFI bindings to C/asm | Low at binding layer | blst Rust crate |
| C/C++ implementation | High (use Mull) | blst C library |
| Generated code | Medium (mutations may be equivalent) | gnark-crypto generated field arithmetic |
**Key insight:** If an implementation delegates to another language
via FFI, you must mutate the *underlying* implementation, not the
bindings. For C/C++ underneath Rust/Go/Python, use Mull or similar.
---
## Phase 2: Harness
For each implementation, create a test harness that:
1. Reads test vectors from JSON files (Wycheproof format recommended)
2. Exercises the implementation's API for each vector
3. Asserts **both acceptance and rejection**:
- Valid vectors: deserialization succeeds, output matches expected
- Invalid vectors: deserialization fails or verification rejects
4. Adds **roundtrip assertions** for valid deserialization vectors:
`serialize(deserialize(bytes)) == bytes`
5. Reports pass/fail per vector with test IDs
**Critical:** A harness that only checks valid vectors will miss all
permissive mutations (e.g., `&` → `|` in validation). See
[references/lessons-learned.md](references/lessons-learned.md) §7.
The harness must be runnable by the mutation testing framework.
For most frameworks this means:
- **Go:** A `_test.go` file in the same package as the implementation
- **Rust:** An integration test in `tests/` or inline `#[test]` functions
- **Python:** A pytest test file
- **C/C++:** A test binary linked against the implementation
### Harness Placement
The harness must live *inside the implementation's package* so the
mutation framework can see it. This usually means:
```bash
# Go: add test file to the package being mutated
cp wycheproof_test.go /path/to/impl/package/
# Rust: add integration test
cp wycheproof.rs /path/to/crate/tests/
# Python: add test to the test directory
cp test_wycheproof.py /path/to/package/tests/Handling Existing Vectors
If the implementation already has test vectors:
Run mutation testing with ONLY the existing vectors (baseline)
Run mutation testing with ONLY your new vectors
Run mutation testing with BOTH combined
The delta between (1) and (3) shows the new vectors' value
Phase 3: Baseline
Run mutation testing with existing test vectors only.
Framework Selection
See references/mutation-frameworks.md for language-specific setup.
| Language | Framework | Command |
|---|---|---|
| Go | gremlins | gremlins unleash ./path/to/package |
| Rust | cargo-mutants | cargo mutants -j N --timeout T |
| Python | mutmut | mutmut run --paths-to-mutate src/ |
| C/C++ | Mull | mull-runner -test-framework=GoogleTest binary |
Parallelism
Always use parallel execution for large codebases:
cargo mutants -j 8(Rust, 8 parallel workers)gremlins unleash --timeout-coefficient 3(Go, increase timeouts)mutmut run --runner "pytest -x -q"(Python, fail-fast)
Recording Baseline Results
Capture these metrics per implementation:
| Metric | Description |
|---|---|
| Total mutants | Number of mutations generated |
| Killed | Mutants caught by tests |
| Survived/Lived | Mutants NOT caught (these are the targets) |
| Not covered | Code paths no test reaches at all |
| Timed out | Ambiguous — resolve before comparing |
| Efficacy % | Killed / (Killed + Survived) |
| Coverage % | (Total - Not covered) / Total |
Save the full mutation log for Phase 4 analysis.
Phase 4: Escape Analysis (Graph-Informed Triage)
Classify each escaped (survived + not covered) mutant using the Trailmark call graph for reachability and blast radius analysis.
This phase MUST use the genotoxic skill's triage methodology. The call graph transforms mutation results from a flat list of survived mutants into an actionable, prioritized set of vector targets.
Step 1: Build the Call Graph
Build a Trailmark code graph for each implementation before triaging mutations:
# Go
uv run trailmark analyze --language go --summary {targetDir}
# Rust
uv run trailmark analyze --language rust --summary {targetDir}The graph provides:
Caller chains — trace from public API entry points to mutated functions to determine reachability
Cyclomatic complexity — prioritize high-CC functions
Blast radius — functions with many callers have wider impact if their mutations survive
Step 2: Filter to Relevant Code
Mutation frameworks test the entire package. Filter results to only the files/functions that test vectors should exercise:
# Go (gremlins)
grep -E "(LIVED|NOT COVERED)" baseline.log \
| grep -E " at (relevant|files)" \
| sort
# Rust (cargo-mutants)
cat mutants.out/missed.txt | grep "src/relevant"Step 3: Graph-Informed Classification
For each escaped mutant, map it to its containing function in the call graph and apply the genotoxic triage criteria:
| Graph Signal | Classification | Action |
|---|---|---|
| No callers in graph | False Positive | Dead code, skip |
| Only test callers | False Positive | Test infrastructure |
| Logging/display/formatting | False Positive | Cosmetic |
| Cross-package callers but NOT COVERED | Cross-Package Gap | See below |
| Reachable from public API, low CC | Missing Vector | Design targeted vector |
| Reachable from public API, high CC (>10) | Fuzzing Target | Both vector + fuzz harness |
| Validation/error-handling path | Negative Vector | Craft invalid input that triggers path |
| Optimization path (GLV, SIMD, batch) | Edge-Case Vector | Input that triggers optimization threshold |
|→^ after left shift (e.g. (t<<1) | carry) | Equivalent Mutant | Skip — bit 0 always 0, OR=XOR |
ct_eq &→| on Montgomery limbs | API-Unreachable | Needs library-internal tests, not vectors |
| Equivalent mutation (behavior unchanged) | False Positive | Skip |
Step 4: Identify Cross-Package Test Gaps
Critical pitfall: Mutation frameworks often only run tests within the same package as the mutation. For Go (gremlins) and Rust (cargo-mutants), this means:
A mutation in
hash_to_curve/g2.goonly runs tests in thehash_to_curvepackage, NOT tests in the parentbls12381package that imports itFunctions that are fully exercised by cross-package tests will appear as NOT COVERED — these are false positives
To confirm: check if the mutated function is called from a test in a different package that wouldn't be run
To resolve cross-package gaps:
Add a thin test in the sub-package that calls through the same code path as the cross-package test
Or run gremlins with
--test-pkg ./...(if supported)Or document as a framework limitation in the report
Step 5: Prioritize by Security Impact
Using the call graph, rank surviving mutants by impact:
| Priority | Criteria | Example |
|---|---|---|
| P0 — Critical | Mutant weakens validation/equality/authentication | ct_eq: & → | makes equality permissive |
| P1 — High | Mutant in deserialization flag parsing | from_compressed: & → | accepts invalid flags |
| P2 — Medium | Mutant in field arithmetic internals | Fp::square: | → ^ corrupts computation |
| P3 — Low | Mutant in optimization path | phi endomorphism: only affects performance path |
| Skip | Formatting, display, equivalent mutation | Debug::fmt return value replacement |
Step 6: Group by Vector Strategy
Group escaped mutants by the code path they represent and the type of test vector needed:
Deserialization flag validation (P1):
- g1.rs:339,363-365,384 — from_compressed_unchecked flags
→ Need: valid-point-wrong-flag vectors
Field arithmetic (P2):
- fp.rs:371-376,406,635-643 — subtract_p, neg, square
→ Need: field arithmetic KATs with edge-case values
Optimization thresholds (P3):
- g1.go:68, g2.go:75 — GLV vs windowed multiplication
→ Need: scalar multiplication with large scalars
Cross-package (framework limitation):
- hash_to_curve/g2.go:242-278 — isogeny, sgn0
→ Document as false positive or add sub-package testEach group becomes a target for new test vectors in Phase 5.
Phase 5: Vector Generation
For each escaped code path group, design test vectors that force execution through that path.
Vector Design Patterns
| Code Path Type | Vector Strategy |
|---|---|
| Point deserialization | Malformed points: wrong length, invalid field elements, off-curve, wrong subgroup, identity point |
| Signature verification | Valid sig + all single-bit corruptions of sig, pk, msg |
| Hash-to-curve | Known answer tests (KATs) with edge-case inputs: empty, single byte, max length |
| Aggregate operations | 1 signer, many signers, duplicate signers, mixed valid/invalid |
| Error handling | Every error path should have a vector that triggers it |
| Arithmetic edge cases | Zero, one, field modulus - 1, points at infinity |
| Serialization flags | Every valid flag combination + every invalid flag combination |
| Roundtrip integrity | For every valid deser vector, assert serialize(deserialize(b)) == b |
| Carry/reduction faults | Reimplement at reduced limb widths, inject faults, extract distinguishing inputs |
Single-Fault Negative Vectors
Each negative vector should have exactly one defect with everything else valid — this isolates which validation check is being tested. See references/vector-patterns.md for per-flag construction examples.
Fault Simulation (Limb-Width Reimplementation)
When mutation testing only applies local operator swaps, deeper architectural bugs (carry propagation, reduction overflow) go untested. To close this gap, reimplement the target algorithm at reduced limb widths (8, 16, 25, 32 bits) and deliberately inject faults — then generate vectors that catch them.
See references/fault-simulation.md for the full methodology: limb-width selection, fault injection catalog, vector extraction, and validation workflow.
Cross-Implementation Verification
Every new test vector MUST be verified against at least two independent implementations before being added to the suite:
Generate the vector using implementation A
Verify with implementation B (different codebase, ideally different language)
If B disagrees, investigate — one implementation has a bug
Vector Format
Use Wycheproof JSON format (algorithm, testGroups[].tests[]
with tcId, comment, result, flags). See
references/vector-patterns.md
for the full schema.
Wycheproof contributions: Use Wycheproof's vectorgen tool rather
than formatting vector files directly. Supply the generated changes as an
envelope. The vectorgen tool can add, update, or replace vectors while
handling tcId assignment, test counts, canonical formatting, and schema
validation. Go-based generators can avoid the vectorgen CLI tool and instead
call the programmatic github.com/c2sp/wycheproof/vectorgen API.
See references/lessons-learned.md §14 and the upstream vectorgen guide for the current workflow and commands.
Phase 6: Validation
Re-run mutation testing with the new test vectors included.
Tip: Use per-file mutation testing for fast iteration during vector development (see references/lessons-learned.md §12). Only run full-crate tests for the final comparison.
Before/After Comparison
| Metric | Baseline | With New Vectors | Delta |
|---|---|---|---|
| Killed | X | Y | Y - X |
| Survived | A | B | A - B (should decrease) |
| Not Covered | C | D | C - D (should decrease) |
| Efficacy % | E% | F% | F - E |
Success Criteria
Vectors have both retroactive value (killing mutants in existing code) and proactive value (catching bugs in future implementations). Generate both kinds — boundary-condition vectors may not improve kill rates in mature libraries but will catch bugs in new implementations. See references/lessons-learned.md §13.
Retroactive (measurable): previously survived/uncovered mutants become killed, no regressions.
If kill rates don't change: the implementation's own tests likely already cover those paths. The vectors still add cross-implementation verification value. Document which case applies.
Output Format
Write VECTOR_FORGE_REPORT.md covering: target algorithm,
implementations tested, baseline results, escape analysis,
new vectors generated, after results, before/after delta, and
conclusions. See
references/report-template.md
for the full template.
Quality Checklist
Before delivering:
[ ] At least one pure implementation mutation-tested (not just FFI wrappers)
[ ] Baseline run completed with existing vectors
[ ] Trailmark call graph built for each implementation
[ ] All escaped mutants triaged using graph-informed classification
[ ] Cross-package false positives identified and documented
[ ] Security-critical mutations (ct_eq, validation, auth) prioritized as P0/P1
[ ] Fault simulation and mutation-derived vectors cross-verified against 2+ implementations
[ ] After run completed with new vectors included
[ ] Before/after delta computed and explained
[ ] Report written to
VECTOR_FORGE_REPORT.md[ ] New test vectors saved in standard format (Wycheproof JSON)
Integration
| Skill | Relationship |
|---|---|
| genotoxic (required for Phase 4) | Provides graph-informed triage — call graph cuts actionable mutants by 30-50% |
| mutation-testing (mewt/muton) | Use for Solidity; Vector Forge is language-agnostic |
| property-based-testing | Better than hand-crafted vectors for bitwise mutations in field arithmetic |
| testing-handbook-skills (fuzzing) | Functions with CC > 10 and surviving mutants need both vectors and fuzz harnesses |
Supporting Documentation
references/mutation-frameworks.md - Language-specific mutation testing framework setup
references/vector-patterns.md - Common test vector patterns for cryptographic primitives
references/fault-simulation.md - Limb-width reimplementation for carry, reduction, and overflow faults
references/report-template.md - Full markdown template for the Vector Forge report
references/lessons-learned.md - BLS12-381 case study: FFI kill rates, timeout masking, cross-package false positives, bitwise mutation gaps, and security-critical priorities
Files
- ATTRIBUTION.mdAdded by AutoGineer927 B
- LICENSELicence file added by AutoGineer19.7 KiB
- SKILL.md18.9 KiB
- agents/openai.yaml241 B
- assets/trail-of-bits-mark.svg3.0 KiB
- references/fault-simulation.md5.7 KiB
- references/lessons-learned.md7.6 KiB
- references/mutation-frameworks.md19.8 KiB
- references/report-template.md912 B
- references/vector-patterns.md9.6 KiB
references/mutation-frameworks.md
Mutation Testing Frameworks
Language-specific setup, execution, and output parsing for mutation testing.
Contents
Language detection
Framework reference table
Per-language setup and commands
Parsing survived mutants
Necessist (test statement removal)
Installation Policy
Every mutation testing framework listed below MUST be installed before proceeding. If a framework command is not found or fails to install:
Try the primary install method for the platform
Try the alternative install methods listed in the language section
If all methods fail, report the error to the user — do NOT fall back to "manual mutation analysis", "manual verification", or any other substitute that skips running the tool
Manual analysis is not a replacement for mutation testing. Mutation testing tools systematically apply hundreds or thousands of mutations that manual review cannot replicate. Skipping installation and doing manual analysis produces false confidence with minimal actual coverage.
Language Detection
Use file extensions to determine the target language, then select the appropriate mutation framework:
| Extensions | Language | Framework |
|---|---|---|
.py | Python | pytest-gremlins or mutmut |
.js, .jsx, .ts, .tsx | JavaScript/TypeScript | Stryker |
.rs | Rust | cargo-mutants |
.go | Go | gremlins or go-mutesting |
.java | Java | PITest |
.c, .h, .cpp, .hpp, .cc | C/C++ | Mull |
.cs | C# | Stryker.NET |
.rb | Ruby | mutant |
.php | PHP | Infection |
.hs | Haskell | MuCheck or Hedgehog |
Python: pytest-gremlins (preferred) or mutmut
pytest-gremlins
Faster alternative to mutmut. Uses mutation switching (no file I/O or module reloads), coverage-guided test selection, and parallel execution. Requires Python 3.11+.
Install:
uv add --dev pytest-gremlinsRun:
uv run pytest --gremlinsNo configuration needed — it integrates directly with pytest.
Parse survived mutants: pytest-gremlins reports survived gremlins in its test output. Each entry includes the file, line, mutation type, and original/replacement values.
mutmut
Install:
uv add --dev mutmutConfigure in pyproject.toml:
[tool.mutmut]
paths_to_mutate = "src/"
tests_dir = "tests/"
runner = "python -m pytest -x -q"Run:
uv run mutmut run
uv run mutmut resultsParse survived mutants:
# List survived mutant IDs
uv run mutmut results | grep "Survived"
# Show specific mutant
uv run mutmut show <id>
# Export all results as JSON (mutmut 3.x+)
uv run mutmut junitxml > mutmut-results.xmlExtract from results output: Each survived mutant line contains the file path, line number, and mutation description. Parse with:
uv run mutmut results 2>&1 | grep "Survived" | \
sed 's/.*Survived: //'macOS note: If using rustworkx or other Rust extensions, set:
export OBJC_DISABLE_INITIALIZE_FORK_SAFETY=YESJavaScript/TypeScript: Stryker
Install:
pnpm add -D @stryker-mutator/core
pnpm dlx stryker initConfigure stryker.config.json:
{
"mutate": ["src/**/*.ts", "!src/**/*.test.ts"],
"testRunner": "vitest",
"reporters": ["json", "clear-text"],
"jsonReporter": { "fileName": "stryker-report.json" }
}Run:
pnpm dlx stryker runParse survived mutants:
# JSON report at reports/mutation/stryker-report.json
# Filter survived:
cat reports/mutation/stryker-report.json | \
jq '.files | to_entries[] | .value.mutants[] | select(.status == "Survived")'Output fields: mutatorName, replacement, location.start.line,
location.start.column, fileName.
Rust: cargo-mutants
Install:
cargo install cargo-mutantsRun:
cargo mutants --jsonParse survived mutants:
# Results in mutants.out/outcomes.json
cat mutants.out/outcomes.json | \
jq '.[] | select(.outcome == "survived")'Output fields: scenario.function, scenario.file, scenario.line,
scenario.replacement, outcome.
Filtering by module:
cargo mutants --file src/parser.rs --jsonGo: gremlins (preferred) or go-mutesting
gremlins
Actively maintained mutation testing tool for Go. Works best on small-to-medium Go modules (microservices, libraries).
Install:
# macOS
brew tap go-gremlins/tap && brew install gremlins
# Any platform with Go
go install github.com/go-gremlins/gremlins/cmd/gremlins@latestRun:
gremlins unleash .Parse results: gremlins reports survived mutants to stdout with file path, line number, and mutation type.
go-mutesting
Install:
go install github.com/zimmski/go-mutesting/cmd/go-mutesting@latestRun:
go-mutesting ./...Parse results: go-mutesting prints survived mutants to stdout. Each line contains the file, line number, and mutation operator.
Alternative: native fuzzing (Go 1.18+)
go test -fuzz=FuzzTarget -fuzztime=60s ./pkg/...Java: PITest
Configure in pom.xml:
<plugin>
<groupId>org.pitest</groupId>
<artifactId>pitest-maven</artifactId>
<configuration>
<targetClasses>com.example.*</targetClasses>
<outputFormats>XML,CSV</outputFormats>
</configuration>
</plugin>Run:
mvn org.pitest:pitest-maven:mutationCoverageParse survived mutants:
# Results in target/pit-reports/mutations.xml
# Filter SURVIVED status
grep 'status="SURVIVED"' target/pit-reports/*/mutations.xmlOutput fields: mutatedClass, mutatedMethod, lineNumber,
mutator, status.
C/C++: Mull
Mull is an LLVM-based mutation testing tool for C and C++. It works as a compiler plugin — it instruments the compiled test binary with mutations, then selectively activates them during test execution.
Mull requires a specific LLVM version. Check the Mull releases page for the LLVM version supported by the latest release. The project must compile with the matching Clang version.
Install
Mull is distributed as prebuilt binaries on GitHub Releases. Each binary targets a specific LLVM version — you must match the Mull binary's LLVM version to the Clang version installed on the system.
Step 1: Determine your Clang/LLVM version:
clang --version
# Look for the major version number (e.g., 19, 20)If Clang is not installed, install it first. On macOS, use
brew install llvm@<version>. On Ubuntu, use
sudo apt-get install clang-<version>.
Step 2: Download the matching Mull binary.
Go to the Mull releases page and download the asset matching your LLVM version, platform, and architecture. Asset naming convention:
Mull-<LLVM_MAJOR>-<MULL_VERSION>-LLVM-<LLVM_FULL>-<OS>-<ARCH>.<ext>Examples (Mull 0.29.0):
| Platform | LLVM | Asset |
|---|---|---|
| macOS arm64 | 19 | Mull-19-0.29.0-LLVM-19.1.7-macOS-aarch64-*.zip |
| macOS arm64 | 20 | Mull-20-0.29.0-LLVM-20.1.8-macOS-aarch64-*.zip |
| Ubuntu 24.04 amd64 | 19 | Mull-19-0.29.0-LLVM-19.1.1-ubuntu-amd64-24.04.deb |
| Ubuntu 24.04 amd64 | 20 | Mull-20-0.29.0-LLVM-20.1.2-ubuntu-amd64-24.04.deb |
| RHEL 9 amd64 | 20 | Mull-20-0.29.0-LLVM-20.1.8-rhel-amd64-9.6.rpm |
Step 3: Install.
macOS:
# 1. Install the matching LLVM/Clang version via Homebrew
# Check Mull releases for which LLVM versions are available
brew install llvm@18 # or llvm@19, llvm@20
# 2. Download the matching Mull binary
gh release download --repo mull-project/mull \
--pattern 'Mull-18-*-macOS-aarch64-*.zip' # match LLVM version
unzip Mull-18-*.zip
# 3. Install binaries to a known location
sudo mkdir -p /usr/local/bin /usr/local/lib
sudo cp usr/local/bin/mull-runner-* /usr/local/bin/
sudo cp usr/local/bin/mull-reporter-* /usr/local/bin/
sudo cp usr/local/lib/mull-ir-frontend-* /usr/local/lib/
# 4. Verify
mull-runner-18 --version
/opt/homebrew/opt/llvm@18/bin/clang --versionImportant macOS notes:
The Mull binary's LLVM version must exactly match the installed Clang. Using
brew install llvm@18withMull-19-*will not work.Use the Homebrew Clang, not Apple's system Clang (which is a different LLVM version and lacks plugin support).
Set
ulimit -n 1024before runningmull-runner(see Environment Setup section below).
Ubuntu/Debian:
# Option A: Cloudsmith APT repository
curl -1sLf \
'https://dl.cloudsmith.io/public/mull-project/mull-stable/setup.deb.sh' \
| sudo -E bash
sudo apt-get update
sudo apt-get install mull-19 # match your LLVM version
# Option B: Direct .deb from GitHub
gh release download --repo mull-project/mull \
--pattern 'Mull-19-*-ubuntu-amd64-24.04.deb'
sudo dpkg -i Mull-19-*.debRHEL/Fedora:
# Option A: Cloudsmith RPM repository
curl -1sLf \
'https://dl.cloudsmith.io/public/mull-project/mull-stable/setup.rpm.sh' \
| sudo -E bash
sudo dnf install mull-20 # match your LLVM version
# Option B: Direct .rpm from GitHub
gh release download --repo mull-project/mull \
--pattern 'Mull-20-*-rhel-amd64-*.rpm'
sudo rpm -i Mull-20-*.rpmVerify installation:
mull-runner --versionIf mull-runner is not found after installation, check that the
install prefix is on $PATH. DO NOT fall back to "manual mutation
analysis" — fix the installation or report the error.
Configure and Build
Mull requires the project to be compiled with Clang and the Mull compiler plugin. The plugin injects mutations at the LLVM IR level.
Key build requirements:
Use the same Clang version that matches your Mull release
Pass
-fpass-plugin=<path-to-mull-ir-frontend>to the compilerUse
-g -O0(debug info required, no optimization)Disable assembly (
--disable-asm) — Mull can only mutate LLVM IR, not hand-written assemblyDisable hardening flags that interfere:
--disable-ssp --disable-pie
Find the plugin path:
# The plugin is typically installed alongside mull-runner:
# Linux: /usr/lib/mull-ir-frontend-<N> (or mull-ir-frontend.so)
# macOS: <install-prefix>/lib/mull-ir-frontend-<N>
# Use `find` or `locate` if unsure:
find /usr/local /opt/homebrew /tmp -name "mull-ir-frontend*" 2>/dev/nullSimple projects:
MULL_PLUGIN=$(find /usr/local /opt/homebrew -name "mull-ir-frontend*" 2>/dev/null | head -1)
clang -fpass-plugin=$MULL_PLUGIN -g -O0 \
-o test_binary test_main.c src/*.cAutotools projects (configure/make):
MULL_PLUGIN=$(find /usr/local /opt/homebrew -name "mull-ir-frontend*" 2>/dev/null | head -1)
LLVM_BIN=$(dirname $(which clang)) # or /opt/homebrew/opt/llvm@18/bin
CC=$LLVM_BIN/clang \
CFLAGS="-fpass-plugin=$MULL_PLUGIN -g -grecord-command-line -O0" \
./configure --disable-shared --enable-static --disable-asm \
--disable-ssp --disable-pie
make clean && make -j$(nproc)CMake projects:
set(CMAKE_C_COMPILER clang)
set(CMAKE_CXX_COMPILER clang++)
set(MULL_PLUGIN_PATH "" CACHE STRING "Path to Mull plugin")
if(MULL_PLUGIN_PATH)
add_compile_options(-fpass-plugin=${MULL_PLUGIN_PATH} -g -O0)
endif()MULL_PLUGIN=$(find /usr/local /opt/homebrew -name "mull-ir-frontend*" 2>/dev/null | head -1)
cmake -B build -DMULL_PLUGIN_PATH=$MULL_PLUGIN
cmake --build buildRun
# Set FD limit (required on macOS, see Environment Setup)
ulimit -n 1024
# Run with GoogleTest binary
mull-runner --allow-surviving --no-output --timeout=5000 \
--reporters=Elements --report-dir=mull-report ./build/tests
# Run with custom test command
mull-runner --test-program=ctest ./build/tests
# Generate report
mull-runner --report-dir=mull-report ./build/testsRecommended flags:
--allow-surviving— don't treat survived mutants as errors--no-output— suppress stdout/stderr from mutant runs--timeout=5000— 5 second timeout per mutant (adjust based on baseline test runtime; use 1000ms for tests completing in <100ms)--reporters=Elements— JSON output in Mutation Testing Elements format (machine-parseable for triage)--report-dir=DIR— write JSON reports to this directory--report-name=NAME— control output filename (useful when running multiple test binaries)--workers=N— parallelism for mutant execution (defaults to CPU count)
Parse survived mutants
Mull outputs results to stdout and optionally to report files. Each survived mutant includes the file path, line number, and mutation type.
# JSON report (if --report-dir used)
cat mull-report/mutation-testing-report.json | \
jq '.files | to_entries[] | .value.mutants[] |
select(.status == "Survived")'Environment Setup (Required)
Before running mull-runner, always set a bounded file descriptor
limit. On macOS (especially Tahoe / macOS 26+), the default
ulimit -n is unlimited, which causes Mull's subprocess library
(reproc) to fail with EINVAL when it tries to close inherited file
descriptors in the forked child process. The fix:
# REQUIRED before any mull-runner invocation
ulimit -n 1024Add this to your Mull runner scripts or shell session. Without it, you will see:
[error] Cannot run executable: Invalid argumentRoot cause: reproc calls getrlimit(RLIMIT_NOFILE) to determine
the max FD to close. When the soft limit is RLIM_INFINITY, reproc
computes max_fd = INT_MAX, which exceeds its internal
MAX_FD_LIMIT (1048576) safety check, causing the child to exit
with EMFILE.
Troubleshooting
| Problem | Solution |
|---|---|
mull-runner: command not found | Install Mull using the instructions above |
Cannot run executable: Invalid argument | Run ulimit -n 1024 before mull-runner (see Environment Setup above) |
| LLVM version mismatch | Install the LLVM version matching your Mull release |
| Plugin load error | Recompile with matching Clang version |
| No mutants generated | Ensure -g -O0 flags and Mull plugin are active |
| Tests fail without mutations | Fix test suite first — Mull needs a green baseline |
| Original test failed (timeout) | Increase --timeout or skip tests with long baseline runtimes |
C#: Stryker.NET
Install:
dotnet tool install -g dotnet-strykerRun:
dotnet stryker --reporter jsonParse survived mutants:
cat StrykerOutput/*/reports/mutation-report.json | \
jq '.files | to_entries[] | .value.mutants[] | select(.status == "Survived")'Ruby: mutant
Install:
gem install mutantRun:
bundle exec mutant run --include lib --require mylib 'MyLib*'Parse results: mutant outputs surviving mutations to stdout with file paths, line numbers, and mutation descriptions.
PHP: Infection
Install:
composer require --dev infection/infectionRun:
vendor/bin/infection --show-mutations --min-msi=0Parse survived mutants:
# JSON log at infection-log.json
cat infection-log.json | jq '.survived[]'Haskell: MuCheck or Hedgehog
MuCheck is the primary mutation testing tool for Haskell. For projects without MuCheck support, property-based testing with Hedgehog or QuickCheck serves as a mutation-resistant alternative.
MuCheck
Install:
cabal install MuCheckRun:
mucheck -t "cabal test" src/MyModule.hsMuCheck applies standard mutation operators (negate guards, swap operators, replace patterns) to the target module and runs the test suite against each mutant.
Parse survived mutants: MuCheck prints results to stdout. Each survived mutant includes the file path, line number, and mutation description (e.g., "Negated guard on line 42").
Limitations: MuCheck requires the project to build with cabal and
has limited support for large multi-module projects. For Stack-based
projects, wrap the test command: mucheck -t "stack test" src/Module.hs.
Alternative: property-based testing as mutation proxy
For projects where MuCheck is impractical, strong property-based tests provide equivalent mutation resistance. Properties that assert invariants over all inputs catch most mutations that MuCheck would surface.
Hedgehog (preferred):
cabal install hedgehogWrite properties in test/ that cover arithmetic, branching, and
boundary behavior. A comprehensive property suite catches the same
classes of defects as mutation testing.
QuickCheck:
cabal install QuickCheckQuickCheck properties work similarly. Use forAll with custom generators
to target the input domain of each function under test.
Universal Mutant Record Format
Regardless of framework, normalize each survived mutant to this schema before feeding into Phase 3 triage:
{
"file_path": "src/parser.py",
"line": 42,
"mutation_type": "arithmetic_operator",
"original": "+",
"replacement": "-",
"function_name": "parse_header",
"status": "survived"
}Map the containing function name by matching file_path:line against
trailmark graph nodes using their location.start_line and
location.end_line ranges.
Necessist: Test Statement Removal
Necessist complements mutation testing by removing statements and method calls from test code and re-running the tests. If a test still passes after a statement is removed, that statement may be unnecessary — indicating weak assertions or missing coverage.
Mutation testing mutates production code to check if tests detect changes. Necessist mutates test code to check if each test statement is actually needed. Run both when the language supports it.
Supported Frameworks
| Framework | Language | Auto-detected |
|---|---|---|
| Anchor | Rust (Solana) | Yes |
| Foundry | Solidity | Yes |
| Go | Go | Yes |
| Hardhat (TypeScript) | TypeScript | Yes |
| Rust | Rust | Yes |
| Vitest | JavaScript/TypeScript | Yes |
Necessist auto-detects the framework from project files. Use --framework
to override when auto-detection fails.
Install
cargo install necessistRun
# Auto-detect framework, run on all test files
necessist
# Explicit framework selection
necessist --framework foundry
# Target specific test files
necessist tests/test_parser.rs tests/test_validator.rs
# Set timeout per test (default 60s, 0 = no timeout)
necessist --timeout 120
# Resume a previous run (results stored in SQLite)
necessist --resumeParse Results
Necessist stores results in a SQLite database by default. Use --dump
to export:
necessist --dumpEach result line contains the test file, line number, the removed statement, and whether the test passed or failed after removal. Filter to passed after removal entries — these are the findings to triage.
Configuration
Create necessist.toml in the project root (necessist --default-config
generates a template):
ignored_functions = ["println", "eprintln", "dbg"]
ignored_methods = ["clone", "to_string", "unwrap"]
ignored_macros = ["debug_assert", "trace"]ignored_functions— Skip removals of these function callsignored_methods— Skip removals of these method callsignored_macros— Skip removals of these macro invocations
For Foundry projects, consider ignoring common cheatcodes that are
setup-only (e.g., vm.label, vm.deal for labeling/funding).
Normalized Necessist Record Format
Normalize each finding before feeding into Phase 3 triage:
{
"test_file_path": "tests/test_parser.rs",
"test_line": 42,
"removed_statement": "parser.validate(&input)",
"test_function": "test_parse_header",
"status": "passed_after_removal",
"source": "necessist"
}The source field distinguishes necessist findings from mutation testing
results during triage and reporting. Map the removed statement to a
production function using the graph analysis algorithm described in the
genotoxic skill.
Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Needs Python
Security
No issues found by our static scan· No issues found
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Attribution and licence
- Published by
- Trail of Bits
- Publisher
- Trail of Bits (Official)
- Source
- trailofbits/skills · plugins/trailmark/skills/vector-forge · commit e4dd0bb
- Licence
- Creative Commons Attribution-ShareAlike 4.0 International (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by Trail of Bits.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download vector-forge.zip