Variant AnalysisBLOCK
Vigolium - High-fidelity vulnerability scanner fusing agentic AI with native speed, modularity, and precision
Overview
Vigolium - High-fidelity vulnerability scanner fusing agentic AI with native speed, modularity, and precision
abfda8d468e1OBSERVED · 2026-10-13Host compatibility
What the documentation claims. We have not run a compatibility test.
| Host | Status | Notes |
|---|---|---|
| cursor | mentioned |
What it tells the agent
The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.
--- name: variant-analysis description: 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. --- # 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: ```bash 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:** 1. Run the pattern 2. Review ALL new matches 3. Classify: true positive or false positive? 4. If FP rate acceptable, generalize next element 5. 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](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 1. **Root cause first**: Understand WHY before searching for WHERE 2. **Start specific**: First pattern should match exactly the known bug 3. **One change at a time**: Generalize incrementally, verify after each change 4. **Know when to stop**: 50%+ FP rate means you've gone too generic 5. **Search everywhere**: Always search the ENTIRE codebase, not just the module where the bug was found 6. **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`
Trust audit
BLOCKgrade D · trust 69/100 Do not install this without reading the findings. The audit found something that could harm you or your machine.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | PASS |
| L1 | Static analysis of the code | NA |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- none-observed
- Shell
- declared (10 observation(s))
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (6)
- pattern: eval($SINK)
- pattern: eval(...)
- pattern-not: Function("...")- pattern: eval($SINK)
- pattern: exec($SINK)
AGENTS.md
Gates applied: no_behavioural_pass.
abfda8d468e1full audit observations/trust-audit/skill/vigolium__variant-analysis.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-13 | abfda8d468e1 | BLOCK | D | 69 | first audit |
Questions
What does the Variant Analysis skill do?
Vigolium - High-fidelity vulnerability scanner fusing agentic AI with native speed, modularity, and precision
Is Variant Analysis safe to install?
No — not without reading the findings first. The audit graded it D (69/100) and found 5 critical or high issues in the source. Each one is listed on this page with the file and line it is on.
What can Variant Analysis access on my machine?
The audit observed that it runs shell commands. Each of those is consistent with what it says it does. Secrets in the source: none found.
Which assistants does Variant Analysis work with?
Its documentation mentions cursor. That is what the text claims, not a compatibility test we ran.
How current is this page?
The grade is for one exact copy of the source (abfda8d468e1), read on 2026-10-13. The repository is watched, and a new audit runs when it changes — this is the first audit.