stemedb/docs/demo/vulnbank

VulnBank - Security Scanner Comparison Demo

VulnBank is an intentionally vulnerable multi-language application designed to demonstrate the precision difference between Aphoria's knowledge-graph approach and traditional pattern-matching security scanners.

DO NOT USE IN PRODUCTION

This codebase contains real security vulnerabilities for testing purposes. Never deploy this code.

Quick Start

# Build Aphoria
cd /path/to/stemedb
cargo build --release -p aphoria

# Run the benchmark
cd docs/demo/vulnbank
./benchmark.sh

What's Inside

Language	Files	Vulnerability Types
Rust	5	JWT, CORS, TLS, Crypto, Secrets
Python	3	TLS, SQL Injection, Command Injection
Go	3	JWT, CORS, TLS, Crypto
Node.js	3	TLS, JWT, SQL Injection, Command Injection
Config	2	Secrets, Misconfigurations

Expected Results

Aphoria Findings (~40)

Extractor	Count	Examples
jwt_config	6	validate_aud = false, Algorithm::None
tls_verify	6	danger_accept_invalid_certs, verify=False
weak_crypto	6	Md5::new(), sha1.Sum(), rc4.NewCipher()
hardcoded_secrets	5	API keys, passwords in source
cors_config	5	Access-Control-Allow-Origin: *
sql_injection	4	f"SELECT * FROM users WHERE id = {id}"
command_injection	4	shell=True, os.system()
rate_limit	3	rate_limit_enabled: false

Precision: 100% - Every finding is a real vulnerability backed by RFC/OWASP specifications.

Semgrep Findings (~100-150)

Semgrep finds many more "issues" because it uses pattern matching:

• Flags every unsafe block in Rust
• Flags every .args() call
• Flags benign code patterns that "look dangerous"

Precision: ~20-30% - Most findings are false positives or low-severity noise.

Why the Difference?

Semgrep Approach

Pattern: "md5" → ALERT!
Pattern: "shell=True" → ALERT!
Pattern: "*.args()" → ALERT!

No context. No understanding. Just pattern matching.

Aphoria Approach

Assertion: "MD5 is cryptographically broken" (RFC 6151)
Code: `Md5::new()` for password hashing
Conflict: Code contradicts RFC 6151 → BLOCK

Every finding is backed by an authoritative source.

Files Overview

vulnbank/
├── rust/
│   ├── src/
│   │   ├── auth.rs      # JWT vulnerabilities
│   │   ├── cors.rs      # CORS misconfigurations
│   │   ├── tls.rs       # TLS verification disabled
│   │   ├── crypto.rs    # Weak cryptography
│   │   └── config.rs    # Hardcoded secrets
│   └── Cargo.toml
├── python/
│   ├── app.py           # TLS, secrets, rate limiting
│   ├── db.py            # SQL injection
│   └── runner.py        # Command injection
├── go/
│   ├── main.go
│   ├── handler.go       # JWT, CORS, TLS
│   └── crypto.go        # Weak cryptography
├── node/
│   ├── server.js        # TLS, CORS, JWT
│   ├── db.js            # SQL injection
│   └── exec.js          # Command injection
├── config/
│   ├── production.yaml  # Config vulnerabilities
│   └── .env.example     # Hardcoded secrets
├── benchmark.sh         # Aphoria vs Semgrep comparison
└── README.md            # This file

Running Individual Scans

Aphoria Only

aphoria scan . --format table

Semgrep Only

semgrep --config=auto .

JSON Output

aphoria scan . --format json > aphoria-results.json
semgrep --config=auto --json . > semgrep-results.json

Understanding the Vulnerabilities

JWT Misconfigurations

• validate_aud = false - Tokens can be replayed across services
• Algorithm::None - Attackers can forge unsigned tokens
• Missing algorithm validation - Algorithm confusion attacks

TLS Issues

• verify=False / InsecureSkipVerify - Man-in-the-middle attacks
• TLS 1.0/1.1 allowed - Known protocol vulnerabilities

Weak Cryptography

• MD5 - Collision attacks practical since 2004
• SHA1 - SHAttered attack demonstrated in 2017
• DES/RC4 - Brute-forceable / multiple known attacks

Injection Vulnerabilities

• SQL Injection - f-strings, format(), concatenation
• Command Injection - shell=True, os.system(), exec()

Secrets Management

• Hardcoded API keys in source code
• Passwords in configuration files
• Credentials in .env.example files

Learn More

• Aphoria Documentation
• Episteme Knowledge Graph
• RFC 7519 - JWT
• OWASP Top 10