Packaging adaptation by AutoGPT, 2026-09-25. Original authorship and licence are retained. Changes are limited to the recorded name, metadata and file references; see ATTRIBUTION.md in this skill package.

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

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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

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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

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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

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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

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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.

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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

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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

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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

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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.

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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.

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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)

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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

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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.