variant-analysis
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- Author updated Jun 15, 2026, 04:05 PM
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- @trailofbits · no license declared
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- Unspecified (assume cross-platform)
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- Python
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- Read-only
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- 26 variants
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 未限定 allowed-tools，默认拥有全部工具权限。
---
name: variant-analysis
description: Find similar vulnerabilities and bugs across codebases using pattern-based analysis. Use when hu…
category: other
runtime: Python
---
# variant-analysis output preview
## PART A: Task fit
- Use case: Find similar vulnerabilities and bugs across codebases using pattern-based analysis. Use when hunting bug variants, building CodeQL/Semgrep queries, analyzing security vulnerabilities, or performing systematic code audits after finding an initial issue..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “When to Use / When NOT to Use / The Five-Step Process” and do not present inference as author intent.
## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “Find similar vulnerabilities and bugs across codebases using pattern-based analysis. Use when hunting bug variants, building CodeQL/Semgrep queries, analyzing security vulnerabilities, or performing systematic code audits after finding an initial issue.”.
- **02** When the source has headings, the agent prioritizes “When to Use / When NOT to Use / The Five-Step Process” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files; mostly runs locally; usually needs no extra API key.
## Running Rules
- read files, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options.The source does not require a stable slash command. After installation, invoke the skill by name and describe the task.
Name target files or source material, expected output, forbidden changes, and whether network or shell access is allowed. Permission fingerprint: read files, write/modify files.
Start with a small task and check whether the result follows “When to Use / When NOT to Use / The Five-Step Process”. Inspect diffs, logs, previews, or tests before expanding scope.
Confirm the final output includes a concrete result, evidence, and next action. If it stays generic, tighten inputs, boundaries, and acceptance criteria.
---
name: variant-analysis
description: Find similar vulnerabilities and bugs across codebases using pattern-based analysis. Use when hu…
category: other
source: trailofbits/skills
---
# variant-analysis
## When to use
- Find similar vulnerabilities and bugs across codebases using pattern-based analysis. Use when hunting bug variants, bu…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.
## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.
## Execution rules
- Organize steps around “When to Use / When NOT to Use / The Five-Step Process” and keep inference separate from source facts.
- read files, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding the task.
## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies.The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.
skill "variant-analysis" {
input -> user goal + target files + boundaries + acceptance criteria
context -> When to Use / When NOT to Use / The Five-Step Process
rules -> SKILL.md triggers / order / output contract
runtime -> Python | read files, write/modify files | mostly runs locally
guardrails -> usually needs no extra API key + small-sample validation + diff/log review
output -> copyable result + checklist + next iteration
}Variant Analysis
You are a variant analysis expert. Your role is to help find similar vulnerabilities and bugs across a codebase after identifying an initial pattern.
When to Use
Use this skill when:
- 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
- Hunting for bug variants across a codebase
- Analyzing how a single root cause manifests in different code paths
When NOT to Use
Do NOT use this skill for:
- Initial vulnerability discovery (use audit-context-building or domain-specific audits instead)
- General code review without a known pattern to search for
- Writing fix recommendations (use issue-writer instead)
- Understanding unfamiliar code (use audit-context-building for deep comprehension first)
The Five-Step Process
Step 1: Understand the Original Issue
Before searching, deeply understand the known bug:
- What is the root cause? Not the symptom, but WHY it's vulnerable
- What conditions are required? Control flow, data flow, state
- What makes it exploitable? User control, missing validation, etc.
Step 2: Create an Exact Match
Start with a pattern that matches ONLY the known instance:
rg -n "exact_vulnerable_code_here"Verify: Does it match exactly ONE location (the original)?
Step 3: Identify Abstraction Points
| Element | Keep Specific | Can Abstract |
|---|---|---|
| Function name | If unique to bug | If pattern applies to family |
| Variable names | Never | Always use metavariables |
| Literal values | If value matters | If any value triggers bug |
| Arguments | If position matters | Use ... wildcards |
Step 4: Iteratively Generalize
Change ONE element at a time:
- Run the pattern
- Review ALL new matches
- Classify: true positive or false positive?
- If FP rate acceptable, generalize next element
- If FP rate too high, revert and try different abstraction
Stop when false positive rate exceeds ~50%
Step 5: Analyze and Triage Results
For each match, document:
- Location: File, line, function
- Confidence: High/Medium/Low
- Exploitability: Reachable? Controllable inputs?
- Priority: Based on impact and exploitability
For deeper strategic guidance, see METHODOLOGY.md.
Tool Selection
| Scenario | Tool | Why |
|---|---|---|
| Quick surface search | ripgrep | Fast, zero setup |
| Simple pattern matching | Semgrep | Easy syntax, no build needed |
| Data flow tracking | Semgrep taint / CodeQL | Follows values across functions |
| Cross-function analysis | CodeQL | Best interprocedural analysis |
| Non-building code | Semgrep | Works on incomplete code |
Key Principles
- Root cause first: Understand WHY before searching for WHERE
- Start specific: First pattern should match exactly the known bug
- One change at a time: Generalize incrementally, verify after each change
- Know when to stop: 50%+ FP rate means you've gone too generic
- Search everywhere: Always search the ENTIRE codebase, not just the module where the bug was found
- Expand vulnerability classes: One root cause often has multiple manifestations
Critical Pitfalls to Avoid
These common mistakes cause analysts to miss real vulnerabilities:
1. Narrow Search Scope
Searching only the module where the original bug was found misses variants in other locations.
Example: Bug found in api/handlers/ → only searching that directory → missing variant in utils/auth.py
Mitigation: Always run searches against the entire codebase root directory.
2. Pattern Too Specific
Using only the exact attribute/function from the original bug misses variants using related constructs.
Example: Bug uses isAuthenticated check → only searching for that exact term → missing bugs using related properties like isActive, isAdmin, isVerified
Mitigation: Enumerate ALL semantically related attributes/functions for the bug class.
3. Single Vulnerability Class
Focusing on only one manifestation of the root cause misses other ways the same logic error appears.
Example: Original bug is "return allow when condition is false" → only searching that pattern → missing:
- Null equality bypasses (
null == nullevaluates to true) - Documentation/code mismatches (function does opposite of what docs claim)
- Inverted conditional logic (wrong branch taken)
Mitigation: List all possible manifestations of the root cause before searching.
4. Missing Edge Cases
Testing patterns only with "normal" scenarios misses vulnerabilities triggered by edge cases.
Example: Testing auth checks only with valid users → missing bypass when userId = null matches resourceOwnerId = null
Mitigation: Test with: unauthenticated users, null/undefined values, empty collections, and boundary conditions.
Resources
Ready-to-use templates in 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
Decide Fit First
Design Intent
How To Use It
Boundaries And Review