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
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 == null evaluates 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