Security Testing¶

Section: 5-security-architecture
Document: Security Testing & Vulnerability Management
Status: Security Testing Strategy
Audience: Security teams, QA engineers, DevOps

🎯 Overview¶

MachineAvatars implements a multi-layered security testing strategy to identify and remediate vulnerabilities before they can be exploited.

Testing Types:

Penetration Testing (Annual)
Vulnerability Scanning (Automated)
SAST - Static Application Security Testing
DAST - Dynamic Application Security Testing
Dependency Scanning
Container Security Scanning

🔍 Penetration Testing¶

Frequency: Annual (minimum)
Provider: Third-party security firm
Status: ⏳ Scheduled for Q1 2025

Scope¶

In-Scope:

Web application (frontend + backend APIs)
Authentication & authorization mechanisms
Data storage & encryption
Network infrastructure
Third-party integrations

Out-of-Scope:

Social engineering
Physical security
DoS attacks on production

Methodology¶

Framework: OWASP Testing Guide + PTES

Phases:

Pre-Engagement (1 week)
Scope definition
Rules of engagement
Emergency contact procedures
Intelligence Gathering (1 week)
Passive reconnaissance
Public information gathering
Technology stack identification
Threat Modeling (3 days)
Attack surface analysis
Threat actor profiling
Risk prioritization
Vulnerability Analysis (1 week)
Automated scanning
Manual testing
Configuration review
Exploitation (1 week)
Proof-of-concept development
Privilege escalation attempts
Data exfiltration simulation
Post-Exploitation (3 days)
Lateral movement testing
Persistence mechanisms
Impact assessment
Reporting (1 week)
Executive summary
Technical findings
Remediation recommendations
Risk ratings (CVSS)

Expected Findings¶

Based on current security posture:

CRITICAL (Expected):

❌ Hardcoded API keys (already documented)
❌ Plain text passwords (no bcrypt)
❌ CORS allows all origins

HIGH (Potential):

⚠️ No rate limiting on some endpoints
⚠️ JWT secret weak default
⚠️ Insufficient input validation

MEDIUM:

⚠️ Missing security headers
⚠️ No CSRF tokens(for state-changing operations)
⚠️ Session management issues

Action Plan: All findings must be remediated within:

CRITICAL: 7 days
HIGH: 30 days
MED IUM: 90 days
LOW: Best effort

🤖 Automated Vulnerability Scanning¶

Tool: Azure Security Center + third-party scanners
Frequency: Weekly (automated)
Status: ✅ Enabled

Scanned Components¶

Web Application
XSS vulnerabilities
SQL/NoSQL injection
Authentication bypasses
Broken access control
APIs
Insecure endpoints
Missing authentication
Excessive data exposure
Rate limiting missing
Infrastructure
Unpatched systems
Misconfigured services
Open ports
Weak SSL/TLS configurations

OWASP Top 10 Compliance¶

OWASP Risk	Status	Mitigation
A01 - Broken Access Control	⚠️ Partial	RBAC implemented, needs testing
A02 - Cryptographic Failures	🔴 CRITICAL	Plain text passwords!
A03 - Injection	✅ Good	Pydantic validation, parameterized queries
A04 - Insecure Design	🟡 Medium	Security requirements in design
A05 - Security Misconfiguration	🔴 CRITICAL	Hardcoded secrets, CORS=*
A06 - Vulnerable Components	🟡 Medium	Dependency scanning needed
A07 - ID & Auth Failures	⚠️ Partial	JWT implemented, MFA missing
A08 - Software & Data Integrity	✅ Good	Code review process
A09 - Security Logging Failures	🟡 Medium	Basic logging, needs enhancement
A10 - SSRF	✅ Good	Input validation on URLs

Priority Fixes:

Implement bcrypt for passwords (A02)
Remove hardcoded secrets (A05)
Fix CORS configuration (A05)
Add MFA (A07)
Enhanced logging (A09)

🔬 Static Application Security Testing (SAST)¶

Tool: SonarQube / CodeQL (planned)
Integration: GitHub Actions (CI/CD)
Status: ⏳ Planned for Q2 2025

Implementation¶

GitHub Actions Workflow:

name: SAST Security Scan

on:
  pull_request:
    branches: [main, develop]
  push:
    branches: [main]

jobs:
  sast:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3

      - name: Run CodeQL Analysis
        uses: github/codeql-action/analyze@v2
        with:
          languages: javascript, python

      - name: Run SonarQube Scan
        uses: sonarsource/sonarqube-scan-action@master
        env:
          SONAR_TOKEN: ${{ secrets.SONAR_TOKEN }}

      - name: Quality Gate Check
        run: |
          if [ "${{ steps.sonar.outputs.quality-gate-status }}" != "PASSED" ]; then
            echo "Quality gate failed"
            exit 1
          fi

Security Rules:

SQL/NoSQL injection detection
XSS vulnerabilities
Hardcoded secrets detection
Insecure random number generation
Weak cryptography usage

🌐 Dynamic Application Security Testing (DAST)¶

Tool: OWASP ZAP / Burp Suite
Frequency: Before each release
Status: ⏳ Planned for Q2 2025

DAST Workflow¶

graph LR
    A[Deploy to Staging] --> B[OWASP ZAP Scan]
    B --> C{Vulnerabilities Found?}
    C -->|Yes - HIGH/CRITICAL| D[Block Deployment]
    C -->|Yes - LOW/MEDIUM| E[Create Tickets]
    C -->|No| F[Proceed to Production]

    style D fill:#FFCDD2
    style F fill:#C8E6C9

Scanner Configuration:

# ZAP API automation
from zapv2 import ZAPv2

zap = ZAPv2(apikey='your-api-key')

# Start spider scan
zap.spider.scan('https://staging.machineavatars.com')

# Wait for spider to complete
while int(zap.spider.status()) < 100:
    time.sleep(2)

# Start active scan
zap.ascan.scan('https://staging.machineavatars.com')

# Generate report
zap.core.htmlreport()

📦 Dependency Scanning¶

Tool: npm audit, pip-audit, Dependabot
Frequency: Daily (automated)
Status: ✅ Enabled

Frontend (npm audit)¶

# Run in CI/CD
npm audit --production

# Auto-fix non-breaking vulnerabilities
npm audit fix

# View detailed report
npm audit --json > audit-report.json

GitHub Dependabot:

# .github/dependabot.yml
version: 2
updates:
  - package-ecosystem: "npm"
    directory: "/"
    schedule:
      interval: "weekly"
    open-pull-requests-limit: 10

  - package-ecosystem: "pip"
    directory: "/backend"
    schedule:
      interval: "weekly"

Backend (pip-audit)¶

# Scan Python dependencies
pip-audit

# Generate JSON report
pip-audit --format json > pip-audit-report.json

Known Vulnerabilities:

{
  "vulnerabilities": [
    {
      "name": "requests",
      "version": "2.25.0",
      "id": "PYSEC-2023-123",
      "fix_versions": ["2.31.0"],
      "description": "Requests vulnerable to SSRF"
    }
  ]
}

Action: Upgrade to latest secure versions

🐳 Container Security Scanning¶

Tool: Trivy / Azure Container Registry scanning
Frequency: On every image build
Status: ⏳ Planned for Q1 2025

Docker Image Scanning¶

# GitHub Actions
- name: Run Trivy vulnerability scanner
  uses: aquasecurity/trivy-action@master
  with:
    image-ref: "machineavatars/response-3d-chatbot:latest"
    format: "sarif"
    output: "trivy-results.sarif"
    severity: "CRITICAL,HIGH"

- name: Upload to GitHub Security
  uses: github/codeql-action/upload-sarif@v2
  with:
    sarif_file: "trivy-results.sarif"

Scan Results:

Base image vulnerabilities
Application dependencies
Exposed secrets in layers
Misconfigurations

🎯 Bug Bounty Program (Planned)¶

Status: ⏳ Planned for Q3 2025
Platform: HackerOne / Bugcrowd

Program Scope¶

In-Scope:

*.machineavatars.com domains
API endpoints
Authentication mechanisms
Data storage

Out-of-Scope:

Third-party services (Azure, Razorpay)
Social engineering
Physical attacks
DoS/DDoS

Reward Structure¶

Severity	Bounty Range	Examples
CRITICAL	$500 - $2,000	RCE, SQL injection, auth bypass
HIGH	$200 - $500	XSS, CSRF, privilege escalation
MEDIUM	$50 - $200	Information disclosure, IDOR
LOW	$0 - $50	Security misconfiguration

Safe Harbor:

Good faith security research
No data exfiltration
No service disruption
Responsible disclosure (90 days)