zz-code-recon

# CodeRecon - Deep Architectural Context Building

Build comprehensive architectural understanding through ultra-granular code analysis. Designed for security auditors, code reviewers, and developers who need to rapidly understand unfamiliar codebases before diving deep.

## Overview

CodeRecon is a systematic approach to codebase reconnaissance that builds layered understanding from high-level architecture down to implementation details. Inspired by Trail of Bits' audit-context-building methodology.

### Why CodeRecon?

Before you can find vulnerabilities, you need to understand:
- How the system is architected
- Where data flows
- What the trust boundaries are
- Where security-critical logic lives

This skill provides a structured methodology for building that context efficiently.

## The Recon Pyramid

```
                    ┌─────────────┐
                    │   DETAILS   │  ← Implementation specifics
                   ─┼─────────────┼─
                  / │  FUNCTIONS  │  ← Key function analysis
                 /  ─┼─────────────┼─
                /   │   MODULES   │  ← Component relationships
               /    ─┼─────────────┼─
              /     │ ARCHITECTURE│  ← System structure
             /      ─┼─────────────┼─
            /       │   OVERVIEW  │  ← High-level understanding
           ─────────┴─────────────┴─────────
```

Start broad, go deep systematically.

## Phase 1: Overview Reconnaissance

### 1.1 Project Identification

Gather basic project information:

```bash
# Check for documentation
ls -la README* ARCHITECTURE* SECURITY* CHANGELOG* docs/

# Identify build system
ls package.json Cargo.toml go.mod pyproject.toml Makefile

# Check for tests
ls -la test* spec* *_test* __tests__/

# Identify CI/CD
ls -la .github/workflows/ .gitlab-ci.yml Jenkinsfile .circleci/
```

### 1.2 Technology Stack Detection

```bash
# Language distribution
find . -type f -name "*.py" | wc -l
find . -type f -name "*.js" -o -name "*.ts" | wc -l
find . -type f -name "*.go" | wc -l
find . -type f -name "*.rs" | wc -l
find . -type f -name "*.sol" | wc -l

# Framework indicators
grep -r "from flask" --include="*.py" | head -1
grep -r "from django" --include="*.py" | head -1
grep -r "express\|fastify" --include="*.js" | head -1
grep -r "anchor_lang" --include="*.rs" | head -1
```

### 1.3 Dependency Analysis

```bash
# Python dependencies
cat requirements.txt pyproject.toml setup.py 2>/dev/null | grep -E "^\s*[a-zA-Z]"

# Node.js dependencies
cat package.json | jq '.dependencies, .devDependencies'

# Rust dependencies
cat Cargo.toml | grep -A 100 "\[dependencies\]"

# Go dependencies
cat go.mod | grep -E "^\s+[a-z]"
```

### 1.4 Create Technology Map

```markdown
## Technology Map: [PROJECT NAME]

### Languages
| Language | Files | Lines | Primary Use |
|----------|-------|-------|-------------|
| Python | 150 | 25K | Backend API |
| TypeScript | 80 | 12K | Frontend |
| Solidity | 12 | 2K | Smart Contracts |

### Key Dependencies
| Package | Version | Purpose | Security Notes |
|---------|---------|---------|----------------|
| fastapi | 0.100.0 | Web framework | Recent CVEs: None |
| web3.py | 6.0.0 | Blockchain client | Check signing |
| pyjwt | 2.8.0 | JWT handling | Verify alg checks |

### Infrastructure
- Database: PostgreSQL 15
- Cache: Redis 7
- Message Queue: RabbitMQ
- Container: Docker + K8s
```

## Phase 2: Architecture Mapping

### 2.1 Directory Structure Analysis

```bash
# Top-level structure
tree -L 2 -d

# Identify entry points
find . -name "main.py" -o -name "app.py" -o -name "index.ts" -o -name "main.go"

# Identify config
find . -name "config*" -o -name "settings*" -o -name ".env*"
```

### 2.2 Component Identification

Look for common patterns:

```
project/
├── api/           # HTTP endpoints
├── auth/          # Authentication
├── core/          # Business logic
├── db/            # Database layer
├── models/        # Data models
├── services/      # External services
├── utils/         # Utilities
├── workers/       # Background jobs
└── tests/         # Test suite
```

### 2.3 Create Architecture Diagram

```
┌─────────────────────────────────────────────────────────────┐
│                        CLIENTS                              │
│              (Web, Mobile, API Consumers)                   │
└─────────────────────────┬───────────────────────────────────┘
                          │ HTTPS
                          ▼
┌─────────────────────────────────────────────────────────────┐
│                      API GATEWAY                            │
│                   (Rate Limiting, Auth)                     │
└─────────────────────────┬───────────────────────────────────┘
                          │
          ┌───────────────┼───────────────┐
          ▼               ▼               ▼
    ┌──────────┐   ┌──────────┐   ┌──────────┐
    │  Auth    │   │  Core    │   │  Admin   │
    │ Service  │   │  API     │   │  API     │
    └────┬─────┘   └────┬─────┘   └────┬─────┘
         │              │              │
         └──────────────┼──────────────┘
                        │
          ┌─────────────┼─────────────┐
          ▼             ▼             ▼
    ┌──────────┐  ┌──────────┐  ┌──────────┐
    │ Database │  │  Cache   │  │ External │
    │ (Postgres)│  │ (Redis)  │  │  APIs    │
    └──────────┘  └──────────┘  └──────────┘
```

### 2.4 Trust Boundary Identification

Map where trust levels change:

```markdown
## Trust Boundaries

### Boundary 1: Internet → API Gateway
- **Type:** Network boundary
- **Controls:** TLS, Rate limiting, WAF
- **Risks:** DDoS, Injection, Auth bypass

### Boundary 2: API Gateway → Services
- **Type:** Authentication boundary
- **Controls:** JWT validation, Role checks
- **Risks:** Token forgery, Privilege escalation

### Boundary 3: Services → Database
- **Type:** Data access boundary
- **Controls:** Query parameterization, Connection pooling
- **Risks:** SQL injection, Data leakage

### Boundary 4: Services → External APIs
- **T