Differential Review

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)

Quick Reference

Codebase Size Strategy

Risk Level Triggers

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)
│
├─ 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

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 findings without evidence
• Claim full analysis when time-limited
• Forget to check test coverage
• Miss high blast radius changes
• Output report only to chat (file required)

Supporting Documentation

• methodology.md - Detailed phase-by-phase workflow (Phases 0-4)
• adversarial.md - Attacker modeling and exploit scenarios (Phase 5)
• reporting.md - Report structure and formatting (Phase 6)
• patterns.md - Common vulnerability patterns reference

For first-time users: Start with methodology.md to understand the complete workflow.

For experienced users: Use this page's Quick Reference and Decision Tree to navigate directly to needed content.

AGI Framework Integration

Adapted for @techwavedev/agi-agent-kit Original source: antigravity-awesome-skills

Memory-First Protocol

Retrieve prior decisions and patterns to avoid re-discovering solutions. Cache results for instant retrieval in future sessions.

# Check for prior development context before starting
python3 execution/memory_manager.py auto --query "prior work and patterns related to Differential Review"

Storing Results

After completing work, store development decisions for future sessions:

python3 execution/memory_manager.py store \
  --content "Completed task with key insights documented for future reference" \
  --type decision --project <project> \
  --tags differential-review default

Multi-Agent Collaboration

Share outcomes with other agents so the team stays aligned and avoids duplicate work.

python3 execution/cross_agent_context.py store \
  --agent "<your-agent>" \
  --action "Task completed — results documented and shared with team" \
  --project <project>