differential-review
Differential-review is a Claude Code skill for conducting security-focused code reviews of pull requests, commits, and diffs. It applies risk-first analysis by prioritizing authentication, cryptography, value transfers, and external calls, using git history and quantified blast radius calculations to back findings. Use this skill when reviewing code changes for security vulnerabilities, particularly in critical systems where small changes may introduce significant risks.
git clone --depth 1 https://github.com/trailofbits/skills /tmp/differential-review && cp -r /tmp/differential-review/plugins/differential-review/skills/differential-review ~/.claude/skills/differential-reviewSKILL.md
# Differential Security Review
Security-focused code review for PRs, commits, and diffs.
## Core Principles
1. **Risk-First**: Focus on auth, crypto, value transfer, external calls
2. **Evidence-Based**: Every finding backed by git history, line numbers, attack scenarios
3. **Adaptive**: Scale to codebase size (SMALL/MEDIUM/LARGE)
4. **Honest**: Explicitly state coverage limits and confidence level
5. **Output-Driven**: Always generate comprehensive markdown report file
---
## Rationalizations (Do Not Skip)
| Rationalization | Why It's Wrong | Required Action |
|-----------------|----------------|-----------------|
| "Small PR, quick review" | Heartbleed was 2 lines | Classify by RISK, not size |
| "I know this codebase" | Familiarity breeds blind spots | Build explicit baseline context |
| "Git history takes too long" | History reveals regressions | Never skip Phase 1 |
| "Blast radius is obvious" | You'll miss transitive callers | Calculate quantitatively |
| "No tests = not my problem" | Missing tests = elevated risk rating | Flag in report, elevate severity |
| "Just a refactor, no security impact" | Refactors break invariants | Analyze as HIGH until proven LOW |
| "I'll explain verbally" | No artifact = findings lost | Always write report |
---
## Quick Reference
### Codebase Size Strategy
| Codebase Size | Strategy | Approach |
|---------------|----------|----------|
| SMALL (<20 files) | DEEP | Read all deps, full git blame |
| MEDIUM (20-200) | FOCUSED | 1-hop deps, priority files |
| LARGE (200+) | SURGICAL | Critical paths only |
### Risk Level Triggers
| Risk Level | Triggers |
|------------|----------|
| HIGH | Auth, crypto, external calls, value transfer, validation removal |
| MEDIUM | Business logic, state changes, new public APIs |
| LOW | Comments, tests, UI, logging |
---
## Workflow Overview
```
Pre-Analysis → Phase 0: Triage → Phase 1: Code Analysis → Phase 2: Test Coverage
↓ ↓ ↓ ↓
Phase 3: Blast Radius → Phase 4: Deep Context → Phase 5: Adversarial → Phase 6: Report
```
---
## Decision Tree
**Starting a review?**
```
├─ Need detailed phase-by-phase methodology?
│ └─ Read: methodology.md
│ (Pre-Analysis + Phases 0-4: triage, code analysis, test coverage, blast radius)
│
├─ Analyzing HIGH RISK change?
│ ├─ Read: adversarial.md
│ │ (Phase 5: Attacker modeling, exploit scenarios, exploitability rating)
│ └─ Or delegate to: differential-review:adversarial-modeler agent
│ (Autonomous attacker modeling with concrete exploit scenarios)
│
├─ Writing the final report?
│ └─ Read: reporting.md
│ (Phase 6: Report structure, templates, formatting guidelines)
│
├─ Looking for specific vulnerability patterns?
│ └─ Read: patterns.md
│ (Regressions, reentrancy, access control, overflow, etc.)
│
└─ Quick triage only?
└─ Use Quick Reference above, skip detailed docs
```
---
## Agents
**`differential-review:adversarial-modeler`** — Models attacker perspectives and
builds exploit scenarios for HIGH RISK code changes. Follows the 5-step
adversarial methodology (attacker model, attack vectors, exploitability rating,
exploit scenario, baseline cross-reference) and produces structured vulnerability
reports. Delegate to this agent when Phase 5 analysis is needed on high-risk
changes, passing that full namespaced name as `subagent_type` — a bare
`adversarial-modeler` is unregistered and the dispatch fails at runtime.
---
## Quality Checklist
Before delivering:
- [ ] All changed files analyzed
- [ ] Git blame on removed security code
- [ ] Blast radius calculated for HIGH risk
- [ ] Attack scenarios are concrete (not generic)
- [ ] Findings reference specific line numbers + commits
- [ ] Report file generated
- [ ] User notified with summary
---
## Integration
**audit-context-building skill:**
- Pre-Analysis: Build baseline context
- Phase 4: Deep context on HIGH RISK changes
**issue-writer skill:**
- Transform findings into formal audit reports
- Command: `issue-writer --input DIFFERENTIAL_REVIEW_REPORT.md --format audit-report`
---
## Example Usage
### Quick Triage (Small PR)
```
Input: 5 file PR, 2 HIGH RISK files
Strategy: Use Quick Reference
1. Classify risk level per file (2 HIGH, 3 LOW)
2. Focus on 2 HIGH files only
3. Git blame removed code
4. Generate minimal report
Time: ~30 minutes
```
### Standard Review (Medium Codebase)
```
Input: 80 files, 12 HIGH RISK changes
Strategy: FOCUSED (see methodology.md)
1. Full workflow on HIGH RISK files
2. Surface scan on MEDIUM
3. Skip LOW risk files
4. Complete report with all sections
Time: ~3-4 hours
```
### Deep Audit (Large, Critical Change)
```
Input: 450 files, auth system rewrite
Strategy: SURGICAL + audit-context-building
1. Baseline context with audit-context-building
2. Deep analysis on auth changes only
3. Blast radius analysis
4. Adversarial modeling
5. Comprehensive report
Time: ~6-8 hours
```
---
## When NOT to Use This Skill
- **Greenfield code** (no baseline to compare)
- **Documentation-only changes** (no security impact)
- **Formatting/linting** (cosmetic changes)
- **User explicitly requests quick summary only** (they accept risk)
For these cases, use standard code review instead.
---
## Red Flags (Stop and Investigate)
**Immediate escalation triggers:**
- Removed code from "security", "CVE", or "fix" commits
- Access control modifiers removed (onlyOwner, internal → external)
- Validation removed without replacement
- External calls added without checks
- High blast radius (50+ callers) + HIGH risk change
These patterns require adversarial analysis even in quick triage.
---
## Tips for Best Results
**Do:**
- Start with git blame for removed code
- Calculate blast radius early to prioritize
- Generate concrete attack scenarios
- Reference specific line numbers and commits
- Be honest about coverage limitations
- Always generate the output file
**Don't:**
- Skip git history analysis
- Make generic finAudits GitHub Actions workflows for security vulnerabilities in AI agent integrations including Claude Code Action, Gemini CLI, OpenAI Codex, and GitHub AI Inference. Detects attack vectors where attacker-controlled input reaches AI agents running in CI/CD pipelines, including env var intermediary patterns, direct expression injection, dangerous sandbox configurations, and wildcard user allowlists. Use when reviewing workflow files that invoke AI coding agents, auditing CI/CD pipeline security for prompt injection risks, or evaluating agentic action configurations.
Clarify requirements before implementing. Use when serious doubts arise.
Understand a codebase before looking for bugs in it - what each function assumes, what it guarantees, and what it depends on elsewhere. Use when starting an audit, threat model, or architecture review on unfamiliar code, and before any vulnerability-hunting pass.
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Prepares codebases for security review using Trail of Bits' checklist. Helps set review goals, runs static analysis tools, increases test coverage, removes dead code, ensures accessibility, and generates documentation (flowcharts, user stories, inline comments). Use when preparing your own codebase to be audited by someone else, getting a repository review-ready before an external security review, deciding what to fix before auditors start, or asking what assessors need from a project. For understanding unfamiliar code you are about to audit, use audit-context-building instead.
Scans Cairo/StarkNet smart contracts for 6 critical vulnerabilities including felt252 arithmetic overflow, L1-L2 messaging issues, address conversion problems, and signature replay. Use when auditing StarkNet projects.
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