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variant-analysis

Find other occurrences of a known bug across a codebase by tracing its root cause. Gradually broaden search patterns, assess matching candidates, assign severity, and document findings with rules to help prevent recurrence.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

Hunts for the other instances of a bug already found — the variants of one root cause across a codebase. Use immediately after a vulnerability, logic bug, or bad pattern turns up in a specific file and the question becomes where else it occurs, including the bare conversational form ("are there others like this?", "is this the same bug?"). Also for generalizing one known instance into a CodeQL or Semgrep query for its whole pattern family, and for triaging a set of look-alike candidates against a known root cause. Not for initial discovery with no bug in hand.

설치 방법 보기

이럴 때 유용합니다

  • Finding similar issues after discovering a vulnerability
  • Building CodeQL or Semgrep queries from a known bug
  • Checking whether similar code shares the same root cause
  • Documenting findings and adding CI rules

포함된 파일(18)

  • SKILL.md3.8 KB
  • agents/openai.yaml247 B
  • assets/trail-of-bits-mark.svg3.0 KB
  • references/reporting.md1.5 KB
  • references/root-cause.md4.1 KB
  • references/searching.md4.5 KB
  • references/triage.md3.5 KB
  • resources/codeql/cpp.ql3.4 KB
  • resources/codeql/go.ql2.0 KB
  • resources/codeql/java.ql2.3 KB
  • resources/codeql/javascript.ql1.7 KB
  • resources/codeql/python.ql2.4 KB
  • resources/semgrep/cpp.yaml2.7 KB
  • resources/semgrep/go.yaml1.8 KB
  • resources/semgrep/java.yaml2.0 KB
  • resources/semgrep/javascript.yaml1.7 KB
  • resources/semgrep/python.yaml2.0 KB
  • resources/variant-report-template.md1.3 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Variant Analysis

Find the other instances of a bug you have already found. One root cause usually has several manifestations, and they are rarely in the module where you found the first one.

When to Use

  • A vulnerability has been found and you need to search for similar instances
  • Building or refining CodeQL/Semgrep queries for security patterns
  • Performing systematic code audits after an initial issue discovery
  • Analyzing how a single root cause manifests in different code paths

When NOT to Use

  • Initial vulnerability discovery — use audit-context-building or a domain-specific audit
  • General code review with no known pattern to search for
  • Writing fix recommendations — use issue-writer
  • Understanding unfamiliar code — use audit-context-building first

The Five Steps

Read the reference for a step when you reach it.

1. Understand the original issue. Extract the root cause — why the code is wrong, not what it does — and enumerate the directions a variant could hide in: related identifiers, other manifestations of the same mistake, data-type edge cases. → references/root-cause.md

2. Create an exact match. Write a pattern matching ONLY the known instance and confirm it hits. A pattern that matches nothing means you have misunderstood the bug, and every search built on it is calibrated against the wrong code.

3–4. Generalize one element at a time. Climb from the exact match toward the pattern family, running and reading all matches after each single change. Stop when more than half the matches are noise. → references/searching.md — abstraction ladder, tool selection, false-positive filters

5. Triage. Decide which candidates are real, and say so with a severity attached. → references/triage.md

Then write it up, including the patterns that failed and a CI rule to prevent regression. → references/reporting.md

Running it as a Workflow

This plugin ships /variant-analysis:variants, which runs the five steps across parallel subagents — one per expansion axis, looping until the sweep stops finding anything new. Each stage reads the reference above that matches its job.

Use the workflow when the codebase is large or the root cause has many manifestations. Work the steps directly when the search is narrow or you want a say in each generalization.

What Makes Hunts Fail

  1. Narrow scope — searching only the module the original bug was in
  2. Pattern too specific — searching one attribute and missing the family around it
  3. One vulnerability class — chasing a single manifestation of the root cause
  4. Happy-path testing — never trying the null, empty, and boundary cases
  5. Generalizing too fast — abstracting several elements at once, so noise cannot be attributed to any one of them

The first three are covered in root-cause.md and searching.md, the fourth in triage.md.

Resources

CodeQL (resources/codeql/): python.ql, javascript.ql, java.ql, go.ql, cpp.ql

Semgrep (resources/semgrep/): python.yaml, javascript.yaml, java.yaml, go.yaml, cpp.yaml

Report: resources/variant-report-template.md

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같은 저장소의 스킬

Build and test code with AddressSanitizer, a tool that detects invalid memory access during execution. Configure checks for C/C++ and unsafe Rust, investigate crash reports, and adjust settings for fuzzing, or testing with generated inputs.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

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trailofbits/skills7.6천2026년 10월 16일 업데이트

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한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

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한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

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한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

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무료

Set up Atheris to test Python code and C extensions with automatically varied inputs. It guides test harness creation, coverage tracking to explore more code, and AddressSanitizer setup for finding memory errors.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Fuzzing a Python package or parser
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trailofbits/skills7.6천2026년 10월 16일 업데이트

Connect static analysis results and human audit notes to a Trailmark code graph. Group findings by severity and compare them with input flow, impact, and privilege boundaries to prioritize investigation and understand findings in their code context.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

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  • Combining human audit notes with automated findings
  • Prioritizing findings using input flow and impact
trailofbits/skills7.6천2026년 10월 16일 업데이트

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