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Genotoxic

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trailofbits
genotoxic

Graph-informed mutation testing triage. Parses codebases with Trailmark, runs mutation testing and necessist, then uses survived mutants, unnecessary test statements, and call graph data to identify false positives, missing test coverage, and fuzzing targets. Use when triaging survived mutants, analyzing mutation testing results, identifying test gaps, finding fuzzing targets from weak tests, running mutation frameworks (including circomvent and cairo-mutants), or using necessist.

Overview

Publishertrailofbits
Repositoryskills
Skill namegenotoxic
Stars
7.3K
Forks
624
Bundled files
5
LicenseCC-BY-SA-4.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by trailofbits on GitHub. Read the source before you install it.

Installation

Install the Genotoxic AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/trailofbits/skills/tree/main/plugins/trailmark/skills/genotoxic
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/trailofbits/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/plugins/trailmark/skills/genotoxic .claude/skills/genotoxic
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Genotoxic in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Genotoxic on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Genotoxic is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Genotoxic

Combines mutation testing and necessist (test statement removal) with code graph analysis to triage findings into actionable categories: false positives, missing unit tests, and fuzzing targets.

When to Use

  • After mutation testing reveals survived mutants that need triage
  • Identifying where unit tests would have the highest impact
  • Finding functions that need fuzz harnesses instead of unit tests
  • Prioritizing test improvements using data flow context
  • Filtering out harmless mutants from actionable ones
  • Finding unnecessary test statements that indicate weak assertions (necessist)

When NOT to Use

  • Codebase has no existing test suite (write tests first)
  • Pure documentation or configuration changes
  • Single-file scripts with trivial logic

Prerequisites

  • trailmark installed — if uv run trailmark fails, run:
    bash
    uv tool install trailmark

Python snippets: uv run --with trailmark python - (a tool env is not importable)

**DO NOT** fall back to "manual verification" or "manual analysis"
as a substitute for running trailmark. Install it first. If installation
fails, report the error instead of switching to manual analysis.
- A **mutation testing framework** for the target language — if the framework
command fails (not found, not installed), install it using the instructions
in [references/mutation-frameworks.md](references/mutation-frameworks.md).
**DO NOT** fall back to "manual mutation analysis" or skip mutation testing.
Install the framework first. If installation fails, report the error
instead of switching to manual mutation analysis.
- **necessist** (optional, recommended) — if the target language is
supported (Go, Rust, Solidity/Foundry, TypeScript/Hardhat,
TypeScript/Vitest, Rust/Anchor), install with `cargo install necessist`.
See [references/mutation-frameworks.md](references/mutation-frameworks.md)
for details.
- An existing test suite that passes
- **macOS environment**: Run `ulimit -n 1024` before any `mull-runner`
invocation. macOS Tahoe (26+) sets unlimited file descriptors by
default, which crashes Mull's subprocess spawning. See
[references/mutation-frameworks.md](references/mutation-frameworks.md)
for details.

---

## Rationalizations to Reject

| Rationalization | Why It's Wrong | Required Action |
|-----------------|----------------|-----------------|
| "All survived mutants need tests" | Many are harmless or equivalent | Triage before writing tests |
| "Mutation testing is too noisy" | Noise means you're not triaging | Use graph data to filter |
| "Unit tests cover everything" | Complex data flows need fuzzing | Check entrypoint reachability |
| "Dead code mutants don't matter" | Dead code should be removed | Flag for cleanup |
| "Low complexity = low risk" | Boundary bugs hide in simple code | Check mutant location |
| "Tool isn't installed, I'll do it manually" | Manual analysis misses what tooling catches | Install the tool first |
| "Necessist isn't mutation testing, skip it" | Necessist finds what mutation testing misses: weak tests | Run both when the language supports it |

---

## Quick Start

```bash
# 1. Build the code graph
uv run trailmark analyze --language auto --summary {targetDir}

# 2. Run mutation testing (language-dependent)
# Python:
uv run mutmut run --paths-to-mutate {targetDir}/src
uv run mutmut results

# 2b. Run necessist (if language supported)
necessist

# 3. Analyze results with this skill's workflow (Phase 3)

Workflow Overview

Phase 1: Graph Build      → Parse codebase with trailmark
      ↓
Phase 2: Mutation Run     → Execute mutation testing framework
Phase 2b: Necessist Run   → Remove test statements (optional, parallel)
      ↓
Phase 3: Triage           → Classify findings using graph data
      ↓
Output: Categorized Report
  ├── Corroborated         (both tools flag same function — highest value)
  ├── False Positives      (harmless, skip)
  ├── Missing Tests        (write unit tests)
  └── Fuzzing Targets      (set up fuzz harnesses)

Decision Tree

├─ Need to set up mutation testing for a language?
│  └─ Read: references/mutation-frameworks.md
│
├─ Need to set up necessist or find weak test statements?
│  └─ Read: references/mutation-frameworks.md (Necessist section)
│
├─ Need to understand the triage criteria in depth?
│  └─ Read: references/triage-methodology.md
│
├─ Need to understand how graph data informs triage?
│  └─ Read: references/graph-analysis.md
│
└─ Already have results + graph? Use Phase 3 below.

Phase 1: Build Code Graph and Run Pre-Analysis

Parse the target codebase with trailmark and run pre-analysis before mutation testing. Pre-analysis computes blast radius, entry points, privilege boundaries, and taint propagation, which Phase 3 uses for triage.

bash
uv run trailmark analyze --language auto --summary {targetDir}

Use the QueryEngine API to build the graph and run pre-analysis:

  1. QueryEngine.from_directory("{targetDir}", language="auto")
  2. Call engine.preanalysis() — mandatory before triage
  3. Export with engine.to_json() for cross-referencing with mutation results

If auto-detection is wrong for the target, rerun with an explicit language or comma-separated list such as python,rust.

See references/graph-analysis.md for the full API: node mapping, reachability queries, blast radius, and pre-analysis subgraph lookups.


Phase 2: Run Mutation Testing

Select and run the appropriate framework. See references/mutation-frameworks.md for language-specific setup.

Capture survived mutants. Each framework reports differently, but extract these fields per mutant:

FieldDescription
File pathSource file containing the mutant
Line numberLine where mutation was applied
Mutation typeWhat was changed (operator, value, etc.)
Statussurvived, killed, timeout, error

Filter to survived mutants only for Phase 3.


Phase 2b: Run Necessist (Optional)

If the target language is supported (Go, Rust, Solidity/Foundry, TypeScript/Hardhat, TypeScript/Vitest, Rust/Anchor), run necessist to find unnecessary test statements. This runs independently of Phase 2 and can execute in parallel.

bash
# Auto-detect framework
necessist

# Or target specific test files
necessist tests/test_parser.rs

# Export results
necessist --dump

Filter to findings where the test passed after removal. See references/mutation-frameworks.md for framework-specific configuration and the normalized record format.

Map each removal to a production function using the algorithm in references/graph-analysis.md.


Phase 3: Triage Findings

For each survived mutant and each necessist removal, determine its triage bucket using graph data. Necessist removals must first be mapped to a production function (see references/graph-analysis.md).

Quick Classification (Mutation Testing)

SignalBucketReasoning
No callers in graphFalse PositiveDead code, mutant is unreachable
Only test callersFalse PositiveTest infrastructure, not production
Logging/display stringFalse PositiveCosmetic, no behavioral impact
Equivalent mutantFalse PositiveBehavior unchanged despite mutation
Simple function, low CC, no entrypoint pathMissing TestsUnit test is straightforward
Error handling pathMissing TestsShould have negative test cases
Boundary condition (off-by-one)Missing TestsProperty-based test candidate
Pure function, deterministicMissing TestsEasy to test, high value
High CC (>10), entrypoint reachableFuzzing TargetComplex + exposed = fuzz it
Parser/validator/deserializerFuzzing TargetStructured input handling
Many callers (>10) + moderate CCFuzzing TargetHigh blast radius
Binary/wire protocol handlingFuzzing TargetFuzzers excel at format testing

Quick Classification (Necessist)

SignalBucketReasoning
Redundant setup or debug callFalse PositiveStatement genuinely unnecessary
Cannot map to production functionFalse PositiveNo graph context for triage
Call removed, no assertion checks its effectMissing TestsTest has weak assertions
Assertion removed, test still passesMissing TestsRedundant or insufficient coverage
Maps to high-CC entrypoint-reachable functionFuzzing TargetComplex + exposed + weak test

When both mutation testing and necessist flag the same production function, mark as corroborated — highest confidence finding.

For detailed criteria, see references/triage-methodology.md.

Graph Queries for Triage

For each mutant, map it to its containing graph node and use pre-analysis subgraphs (tainted, high_blast_radius, privilege_boundary) from Phase 1 to classify it. The classification logic checks: no callers → false positive, privilege boundary → fuzzing, high CC + tainted → fuzzing, high blast radius → fuzzing, otherwise → missing tests.

See references/graph-analysis.md for the batch_triage implementation and node mapping functions.


Output Format

Generate a markdown report:

markdown
# Genotoxic Triage Report

## Summary
- Total survived mutants: N
- Total necessist removals: N
- Corroborated findings: N
- False positives: N (N%)
- Missing test coverage: N (N%)
- Fuzzing targets: N (N%)

## Corroborated Findings
| File | Line | Function | Mutation Signal | Necessist Signal | Action |
|------|------|----------|----------------|------------------|--------|

## False Positives
| File | Line | Mutation | Reason | Source |
|------|------|----------|--------|--------|

## Missing Test Coverage
| File | Line | Function | CC | Callers | Suggested Test | Source |
|------|------|----------|----|---------|----------------|--------|

## Fuzzing Targets
| File | Line | Function | CC | Entrypoint Path | Blast Radius | Source |
|------|------|----------|----|-----------------|--------------|--------|

The Source column is mutation, necessist, or corroborated.

Write the report to GENOTOXIC_REPORT.md in the working directory.


Quality Checklist

Before delivering:

  • Trailmark graph built for target language
  • Mutation framework ran to completion
  • Necessist ran (if language supported) or noted as not applicable
  • All survived mutants triaged (none unclassified)
  • All necessist removals triaged (if applicable)
  • Corroborated findings identified (if both tools ran)
  • False positives have clear justifications
  • Missing test items include suggested test type
  • Fuzzing targets include entrypoint paths and blast radius
  • Report file written to GENOTOXIC_REPORT.md
  • User notified with summary statistics

Integration

trailmark skill:

  • Phase 1: Build code graph, query complexity and entrypoints
  • Phase 3: Caller analysis, reachability, blast radius

property-based-testing skill:

  • Missing test coverage items involving boundary conditions
  • Roundtrip/idempotence properties for serialization mutants

testing-handbook-skills (fuzzing):

  • Fuzzing target items: use harness-writing, cargo-fuzz, atheris

Supporting Documentation


First-time users: Start with Phase 1 (graph build), then run mutations, then use the Quick Classification table in Phase 3.

Experienced users: Jump to Phase 3 and use the Decision Tree to load specific reference material.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Genotoxic AI skill do?

Graph-informed mutation testing triage. Parses codebases with Trailmark, runs mutation testing and necessist, then uses survived mutants, unnecessary test statements, and call graph data to identify false positives, missing test coverage, and fuzzing targets. Use when triaging survived mutants, analyzing mutation testing results, identifying test gaps, finding fuzzing targets from weak tests, running mutation frameworks (including circomvent and cairo-mutants), or using necessist.

Why use Genotoxic on TypingMind?

Because you install it once and use it with any model. Genotoxic is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Genotoxic in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/trailofbits/skills/tree/main/plugins/trailmark/skills/genotoxic. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Genotoxic?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Genotoxic?

As many as you like. As long as a model supports skills, you can use Genotoxic with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Genotoxic AI skill free?

Yes. It is published on GitHub by trailofbits under the CC-BY-SA-4.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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