Genotoxic

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From the author

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.

— the description by Trail of Bits

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

Genotoxic streamlines the triage of mutation testing results by integrating code graph data from Trailmark with mutation testing frameworks and Necessist. It transforms raw lists of survived mutants into actionable categories—false positives, missing unit tests, and high-priority fuzzing targets—by analyzing code complexity, reachability, and blast radius. This approach reduces noise in mutation testing and ensures that test improvements are focused on the most critical and vulnerable parts of the codebase.

What it does

Parses codebases to build a structural graph of functions and entrypoints.
Executes mutation testing frameworks to identify code logic that lacks sufficient test coverage.
Runs Necessist to detect weak test assertions and redundant test statements.
Maps survived mutants and test removals to specific production code nodes.
Classifies findings into false positives, missing tests, or fuzzing targets based on graph context.
Generates a structured triage report for prioritized remediation.

When to use it

After running mutation testing and receiving a large, unmanageable list of survived mutants.
When you need to prioritize which parts of your codebase require new unit tests.
When identifying complex, entrypoint-reachable functions that are better suited for fuzzing.
When you want to filter out harmless or equivalent mutants from your test results.
When evaluating the effectiveness of existing test assertions using Necessist.

Advantages

Reduces manual triage effort by using automated graph analysis to filter noise.
Provides data-driven justification for prioritizing specific test improvements.
Identifies high-value fuzzing targets that unit tests might miss.
Corroborates findings across multiple testing tools for higher confidence.
Integrates seamlessly with existing mutation testing and analysis toolchains.

Usage examples

“I have a list of 50 survived mutants from my Python project. How do I triage them?”: The agent will guide you to build a Trailmark graph, run the mutation analysis, and use the Phase 3 triage workflow to categorize the mutants into false positives, missing tests, or fuzzing targets.
“How can I tell if a survived mutant is actually a high-priority security risk?”: The agent will use the graph data to check if the mutated function is reachable from an untrusted entrypoint and calculate its blast radius, flagging it as a fuzzing target if it meets the criteria.

Install

Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/trailofbits/genotoxic/download
Unzip it into the cross-client skills folder of your project:
```
mkdir -p .agents/skills && unzip genotoxic.zip -d .agents/skills
```

Documentation by Trail of Bits

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:
```
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.

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

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

QueryEngine.from_directory("{targetDir}", language="auto")
Call engine.preanalysis() — mandatory before triage
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:

Field	Description
File path	Source file containing the mutant
Line number	Line where mutation was applied
Mutation type	What was changed (operator, value, etc.)
Status	survived, 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.

# 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)

Signal	Bucket	Reasoning
No callers in graph	False Positive	Dead code, mutant is unreachable
Only test callers	False Positive	Test infrastructure, not production
Logging/display string	False Positive	Cosmetic, no behavioral impact
Equivalent mutant	False Positive	Behavior unchanged despite mutation
Simple function, low CC, no entrypoint path	Missing Tests	Unit test is straightforward
Error handling path	Missing Tests	Should have negative test cases
Boundary condition (off-by-one)	Missing Tests	Property-based test candidate
Pure function, deterministic	Missing Tests	Easy to test, high value
High CC (>10), entrypoint reachable	Fuzzing Target	Complex + exposed = fuzz it
Parser/validator/deserializer	Fuzzing Target	Structured input handling
Many callers (>10) + moderate CC	Fuzzing Target	High blast radius
Binary/wire protocol handling	Fuzzing Target	Fuzzers excel at format testing

Quick Classification (Necessist)

Signal	Bucket	Reasoning
Redundant setup or debug call	False Positive	Statement genuinely unnecessary
Cannot map to production function	False Positive	No graph context for triage
Call removed, no assertion checks its effect	Missing Tests	Test has weak assertions
Assertion removed, test still passes	Missing Tests	Redundant or insufficient coverage
Maps to high-CC entrypoint-reachable function	Fuzzing Target	Complex + 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:

# 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

references/mutation-frameworks.md - Language-specific framework setup, output parsing, and necessist configuration
references/triage-methodology.md - Detailed triage criteria, edge cases, and worked examples for both mutation testing and necessist
references/graph-analysis.md - Graph query patterns, test-to-production mapping, and result merging

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.

Files

ATTRIBUTION.mdAdded by AutoGineer921 B
LICENSELicence file added by AutoGineer19.7 KiB
SKILL.md12.7 KiB
agents/openai.yaml229 B
assets/trail-of-bits-mark.svg3.0 KiB
references/graph-analysis.md12.8 KiB
references/mutation-frameworks.md28.1 KiB
references/triage-methodology.md11.8 KiB

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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, Needs Node.js

Security

No issues found by our static scan· No issues found

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Published by

Trail of Bits

Publisher

Trail of Bits (Official)

Source

trailofbits/skills · plugins/trailmark/skills/genotoxic · commit e4dd0bb

Licence

Creative Commons Attribution-ShareAlike 4.0 International (redistribution allowed)

LICENSE (added by AutoGineer from LICENSE)
ATTRIBUTION.md (written by AutoGineer)

Synced

2026-11-08

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 genotoxic.zip

From the author

AutoGineer summary

What it does

When to use it

Advantages

Usage examples

Install

Documentation by Trail of Bits

Genotoxic

When to Use

When NOT to Use

Prerequisites

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

Workflow Overview

Decision Tree

Phase 1: Build Code Graph and Run Pre-Analysis

Phase 2: Run Mutation Testing

Phase 2b: Run Necessist (Optional)

Phase 3: Triage Findings

Quick Classification (Mutation Testing)

Quick Classification (Necessist)

Graph Queries for Triage

Output Format

Quality Checklist

Integration

Supporting Documentation

Files

LICENSE

Requirements and compatibility

Security

Attribution and licence

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Download ZIP