Security Analysis Skills

Purpose: Universal security knowledge framework for threat modeling, vulnerability assessment, risk scoring, and secure coding. Designed to be applied by ALL development agents (security-agent, developer-agent, devops-agent, rust-expert, python-ml-expert) to ensure security-first development practices.

Created: 2025-11-08

When to Use Security Analysis Skills

✅ Use this skill when:

•Conducting threat modeling for new features/systems
•Performing security code review
•Assessing vulnerabilities and scoring risk
•Implementing authentication/authorization
•Handling sensitive data (PII, credentials, payment info)
•Deploying to production (security checklist)
•Investigating security incidents
•Designing secure architectures

❌ NOT required for:

•Pure documentation tasks with no code
•Read-only data analysis with public data
•Internal tools with no network exposure (but still recommended)

Target Audience: Security specialists AND general developers integrating security into daily work

Core Security Frameworks

1. STRIDE Threat Modeling

Purpose: Systematic identification of threats by category

STRIDE Categories:

•
S - Spoofing Identity
- •Definition: Attacker pretends to be someone else
- •Examples: Stolen credentials, session hijacking, JWT forgery
- •Mitigations: MFA, certificate pinning, signed tokens
•
T - Tampering with Data
- •Definition: Unauthorized modification of data
- •Examples: Man-in-the-middle, SQL injection, XSS
- •Mitigations: HTTPS/TLS, input validation, integrity checks (HMAC)
•
R - Repudiation
- •Definition: User denies performing an action
- •Examples: Missing audit logs, unsigned transactions
- •Mitigations: Audit logging, digital signatures, timestamps
•
I - Information Disclosure
- •Definition: Exposure of confidential information
- •Examples: Directory traversal, verbose errors, unencrypted data
- •Mitigations: Encryption at rest/transit, least privilege, sanitized errors
•
D - Denial of Service
- •Definition: Service becomes unavailable
- •Examples: Resource exhaustion, infinite loops, DDoS attacks
- •Mitigations: Rate limiting, resource quotas, circuit breakers
•
E - Elevation of Privilege
- •Definition: Unauthorized permission escalation
- •Examples: Privilege escalation bugs, insecure defaults
- •Mitigations: Principle of least privilege, role-based access control

How to Apply STRIDE:

•For each component/feature, ask: "What STRIDE threats apply?"
•Fill out threat modeling worksheet (see reference section)
•Prioritize threats by impact × likelihood
•Document mitigations for each identified threat

2. OWASP Top 10 (2021 Edition)

Purpose: Most critical web application security risks

A01: Broken Access Control

Description: Users can act outside their intended permissions

Examples:

•Direct object references: /user/1234/profile → change to /user/5678/profile
•Missing function-level access control: Regular user accesses /admin/delete
•IDOR (Insecure Direct Object Reference): Manipulating IDs in URLs/APIs

Secure Patterns:

python

# ❌ VULNERABLE: No ownership check
@app.route('/document/<doc_id>')
def get_document(doc_id):
    doc = Document.query.get(doc_id)
    return render_template('doc.html', doc=doc)

# ✅ SECURE: Verify ownership
@app.route('/document/<doc_id>')
@login_required
def get_document(doc_id):
    doc = Document.query.get(doc_id)
    if not doc or doc.owner_id != current_user.id:
        abort(403)  # Forbidden
    return render_template('doc.html', doc=doc)

Checklist:

• All endpoints verify user permissions
• Object ownership validated before access
• Default deny (whitelist not blacklist)
• Disable directory listing
• Invalidate sessions on logout

A02: Cryptographic Failures

Description: Sensitive data exposed due to weak/missing encryption

Examples:

•Storing passwords in plaintext
•Using weak algorithms (MD5, SHA1 for passwords)
•Transmitting sensitive data over HTTP
•Hardcoded encryption keys

Secure Patterns:

python

# ❌ VULNERABLE: Weak hashing
import hashlib
password_hash = hashlib.md5(password.encode()).hexdigest()

# ✅ SECURE: Proper password hashing
import bcrypt
password_hash = bcrypt.hashpw(password.encode(), bcrypt.gensalt())

# ❌ VULNERABLE: Hardcoded key
AES_KEY = "mysecretkey12345"

# ✅ SECURE: Environment variable
import os
AES_KEY = os.environ['AES_ENCRYPTION_KEY']

Checklist:

• Use TLS 1.2+ for all data in transit
• Hash passwords with bcrypt/Argon2 (not MD5/SHA1)
• Never hardcode secrets (use env vars/vaults)
• Encrypt sensitive data at rest
• Use strong key generation (crypto.randomBytes, secrets module)

A03: Injection

Description: Untrusted data sent to interpreter as command/query

Types: SQL Injection, NoSQL Injection, Command Injection, LDAP Injection, XPath Injection

SQL Injection Example:

python

# ❌ VULNERABLE: String concatenation
username = request.form['username']
query = f"SELECT * FROM users WHERE username = '{username}'"
# Attacker inputs: ' OR '1'='1' --
# Result: SELECT * FROM users WHERE username = '' OR '1'='1' --'

# ✅ SECURE: Parameterized query
username = request.form['username']
query = "SELECT * FROM users WHERE username = ?"
cursor.execute(query, (username,))

Command Injection Example:

python

# ❌ VULNERABLE: Shell injection
filename = request.form['filename']
os.system(f"cat {filename}")  # Attacker: "; rm -rf /"

# ✅ SECURE: Avoid shell, use safe APIs
import subprocess
subprocess.run(['cat', filename], check=True, capture_output=True)

Checklist:

• Use parameterized queries (prepared statements)
• Avoid dynamic query construction with string concat
• Validate input against whitelist (not blacklist)
• Escape special characters for context
• Use ORM frameworks (with parameterization)

A04: Insecure Design

Description: Missing or ineffective security controls in design phase

Examples:

•No rate limiting on login (brute force)
•Password reset without identity verification
•Predictable session IDs
•No transaction verification (CSRF)

Secure Design Patterns:

•Defense in depth (multiple security layers)
•Principle of least privilege
•Fail securely (default deny)
•Separation of duties
•Security by default (opt-in for risky features)

Checklist:

• Threat model created during design
• Rate limiting on authentication/sensitive endpoints
• CSRF tokens for state-changing operations
• Cryptographically secure random IDs (not sequential)
• Security requirements defined before coding

A05: Security Misconfiguration

Description: Insecure default configurations, incomplete setups, exposed admin interfaces

Examples:

•Default admin credentials (admin/admin)
•Verbose error messages revealing stack traces
•Unnecessary features enabled (debug mode in production)
•Missing security headers
•Outdated software versions

Secure Configuration:

python

# ❌ VULNERABLE: Debug mode in production
app = Flask(__name__)
app.config['DEBUG'] = True  # Exposes code, allows RCE

# ✅ SECURE: Environment-based config
import os
app.config['DEBUG'] = os.environ.get('FLASK_ENV') == 'development'

# ✅ SECURE: Security headers
@app.after_request
def set_security_headers(response):
    response.headers['X-Content-Type-Options'] = 'nosniff'
    response.headers['X-Frame-Options'] = 'DENY'
    response.headers['X-XSS-Protection'] = '1; mode=block'
    response.headers['Strict-Transport-Security'] = 'max-age=31536000; includeSubDomains'
    return response

Checklist:

• Change all default credentials
• Disable debug mode in production
• Remove unnecessary features/services
• Configure security headers (CSP, HSTS, X-Frame-Options)
• Regular security updates applied

A06: Vulnerable and Outdated Components

Description: Using libraries/frameworks with known vulnerabilities

Examples:

•Unmaintained dependencies (no security patches)
•Using deprecated crypto libraries
•Outdated frameworks (old Rails, Django, Spring)

Secure Practices:

bash

# Check for vulnerabilities
npm audit          # Node.js
pip-audit          # Python
bundle audit       # Ruby
cargo audit        # Rust

# Update dependencies
npm update
pip install --upgrade -r requirements.txt
cargo update

Checklist:

• Dependency scanning in CI/CD
• Regular updates (monthly for deps, immediate for critical CVEs)
• Remove unused dependencies
• Pin versions (avoid wildcards like *)
• Monitor CVE databases (NVD, GitHub Security Advisories)

A07: Identification and Authentication Failures

Description: Weak authentication allows attackers to compromise accounts

Examples:

•Weak password policy (no complexity requirements)
•Session fixation
•Missing MFA
•Predictable session tokens
•No account lockout on brute force

Secure Authentication:

python

# Password Policy
MIN_LENGTH = 12
REQUIRE_UPPERCASE = True
REQUIRE_DIGIT = True
REQUIRE_SPECIAL = True

# Session Management
from secrets import token_urlsafe
session_id = token_urlsafe(32)  # Cryptographically secure

# Rate Limiting
from flask_limiter import Limiter
limiter = Limiter(app, default_limits=["5 per minute"])

@app.route('/login', methods=['POST'])
@limiter.limit("5 per minute")
def login():
    # Login logic with rate limiting
    pass

Checklist:

• Strong password policy enforced
• MFA available (TOTP, WebAuthn)
• Account lockout after N failed attempts
• Session timeout configured
• Secure session cookie flags (HttpOnly, Secure, SameSite)

A08: Software and Data Integrity Failures

Description: Code/infrastructure relies on untrusted sources without integrity verification

Examples:

•Downloading dependencies without checksum verification
•Auto-update without signature validation
•Insecure CI/CD pipeline
•Deserialization of untrusted data

Secure Practices:

python

# ❌ VULNERABLE: Deserialize untrusted data
import pickle
data = pickle.loads(request.data)  # RCE risk!

# ✅ SECURE: Use safe serialization
import json
data = json.loads(request.data)  # Only deserializes JSON primitives

# Verify package integrity
pip install --require-hashes -r requirements.txt

Checklist:

• Use signed commits (GPG)
• Verify package checksums/signatures
• Secure CI/CD pipeline (no secrets in logs)
• Avoid insecure deserialization (pickle, YAML.unsafe_load)
• Implement software bill of materials (SBOM)

A09: Security Logging and Monitoring Failures

Description: Insufficient logging prevents detection of breaches

Examples:

•No logging of authentication events
•Logs not reviewed/alerted
•Sensitive data in logs (passwords, tokens)
•No integrity protection (logs can be tampered)

Secure Logging:

python

import logging
import hashlib

# ✅ SECURE: Log security events
logger = logging.getLogger('security')

@app.route('/login', methods=['POST'])
def login():
    username = request.form['username']
    password = request.form['password']

    if authenticate(username, password):
        logger.info(f"Successful login: user={username}, ip={request.remote_addr}")
        return "Success"
    else:
        logger.warning(f"Failed login: user={username}, ip={request.remote_addr}")
        return "Invalid credentials", 401

# ❌ VULNERABLE: Log sensitive data
logger.info(f"User {username} logged in with password {password}")  # DON'T!

# ✅ SECURE: Redact sensitive data
logger.info(f"User {username} logged in")

Checklist:

• Log all authentication events (success/failure)
• Log authorization failures
• Log input validation failures
• Never log passwords, tokens, PII
• Centralized logging with alerting
• Tamper-evident logs (write-once storage)

A10: Server-Side Request Forgery (SSRF)

Description: Web app fetches remote resource without validating user-supplied URL

Examples:

•Fetching arbitrary URLs from user input
•Accessing internal services (localhost, 169.254.169.254)
•Port scanning via web app

SSRF Example:

python

# ❌ VULNERABLE: Fetch arbitrary URL
import requests
url = request.args.get('url')
response = requests.get(url)  # Attacker: http://localhost:6379/

# ✅ SECURE: Whitelist domains
ALLOWED_DOMAINS = ['api.example.com', 'cdn.example.com']
from urllib.parse import urlparse

url = request.args.get('url')
parsed = urlparse(url)
if parsed.hostname not in ALLOWED_DOMAINS:
    abort(400, "Invalid domain")
response = requests.get(url)

Checklist:

• Whitelist allowed domains/IPs
• Block private IP ranges (10.0.0.0/8, 192.168.0.0/16, 127.0.0.1)
• Disable URL redirects or validate redirect targets
• Use network segmentation (no internet access from app servers)

3. Risk Scoring (CVSS v3.1)

Purpose: Quantify vulnerability severity for prioritization

CVSS Formula: Base Score (0-10) = f(Impact, Exploitability)

Severity Levels:

•Critical (9.0-10.0): Immediate action required, exploit in the wild
•High (7.0-8.9): High priority, exploitable remotely
•Medium (4.0-6.9): Medium priority, requires user interaction
•Low (0.1-3.9): Low priority, limited impact

Impact Scoring:

•Confidentiality Impact: None / Low / High
•Integrity Impact: None / Low / High
•Availability Impact: None / Low / High

Exploitability Scoring:

•Attack Vector: Network (highest) / Adjacent / Local / Physical (lowest)
•Attack Complexity: Low (easy) / High (difficult)
•Privileges Required: None (highest) / Low / High (lowest)
•User Interaction: None (highest) / Required (lower)

Quick Risk Matrix (Impact × Likelihood):

Impact / Likelihood	Low	Medium	High
High	Med	High	Crit
Medium	Low	Med	High
Low	Low	Low	Med

Example Scoring:

code

Vulnerability: SQL Injection in login endpoint

CVSS Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:N
- Attack Vector: Network (AV:N) - remotely exploitable
- Attack Complexity: Low (AC:L) - easy to exploit
- Privileges Required: None (PR:N) - unauthenticated
- User Interaction: None (UI:N) - no user action needed
- Confidentiality: High (C:H) - all user data exposed
- Integrity: High (I:H) - data can be modified
- Availability: None (A:N) - no DoS

Base Score: 9.1 (CRITICAL)

Checklist:

• Score all identified vulnerabilities using CVSS
• Prioritize remediation: Critical → High → Medium → Low
• Define risk acceptance criteria (e.g., no Critical in production)
• Track vulnerabilities in registry (Jira, GitHub Security)

4. Security Code Review Patterns

Purpose: Identify common vulnerabilities during code review

Input Validation

Rule: Never trust user input

Patterns:

python

# Whitelist validation (preferred)
ALLOWED_EXTENSIONS = {'.jpg', '.png', '.pdf'}
file_ext = os.path.splitext(filename)[1].lower()
if file_ext not in ALLOWED_EXTENSIONS:
    raise ValueError("Invalid file type")

# Regex validation
import re
EMAIL_PATTERN = re.compile(r'^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$')
if not EMAIL_PATTERN.match(email):
    raise ValueError("Invalid email")

# Type validation
from pydantic import BaseModel, validator

class UserInput(BaseModel):
    age: int
    email: str

    @validator('age')
    def age_must_be_positive(cls, v):
        if v < 0 or v > 150:
            raise ValueError('Invalid age')
        return v

Authentication & Authorization

Rule: Verify identity and permissions at every access point

Patterns:

python

# Decorator-based authorization
from functools import wraps

def require_role(role):
    def decorator(f):
        @wraps(f)
        def decorated_function(*args, **kwargs):
            if not current_user.has_role(role):
                abort(403)
            return f(*args, **kwargs)
        return decorated_function
    return decorator

@app.route('/admin/users')
@require_role('admin')
def list_users():
    return render_template('users.html', users=User.query.all())

# Resource ownership check
def check_ownership(resource, user):
    if resource.owner_id != user.id and not user.is_admin():
        abort(403, "Not authorized to access this resource")

Cryptography Best Practices

Rules:

•Don't roll your own crypto
•Use standard libraries (cryptography, libsodium)
•Use authenticated encryption (AES-GCM, ChaCha20-Poly1305)

Patterns:

python

# ✅ SECURE: Modern authenticated encryption
from cryptography.hazmat.primitives.ciphers.aead import AESGCM
import os

key = AESGCM.generate_key(bit_length=256)
aesgcm = AESGCM(key)
nonce = os.urandom(12)  # 96-bit nonce
ciphertext = aesgcm.encrypt(nonce, plaintext, associated_data=None)

# ✅ SECURE: Password hashing
import bcrypt
hashed = bcrypt.hashpw(password.encode(), bcrypt.gensalt(rounds=12))

# ✅ SECURE: Secure random token
import secrets
token = secrets.token_urlsafe(32)

Secrets Management

Rule: Never hardcode secrets

Patterns:

python

# ❌ VULNERABLE
API_KEY = "sk_live_abc123xyz789"

# ✅ SECURE: Environment variables
import os
API_KEY = os.environ['API_KEY']

# ✅ SECURE: Secrets manager (AWS Secrets Manager)
import boto3
client = boto3.client('secretsmanager')
response = client.get_secret_value(SecretId='prod/api-key')
API_KEY = response['SecretString']

# ✅ SECURE: Configuration file (gitignored)
import json
with open('/etc/secrets/config.json') as f:
    config = json.load(f)
    API_KEY = config['api_key']

Checklist:

• No secrets in source code
• No secrets in git history (use git-secrets)
• Secrets in environment variables or vault
• Rotate secrets regularly
• Use different secrets per environment (dev/staging/prod)

STRIDE Threat Modeling Worksheet

Use this template for every new feature/component:

markdown

## Threat Model: [Feature/Component Name]

**Description**: [Brief description of functionality]

**Date**: [YYYY-MM-DD]

**Reviewer**: [Your name]

---

### Components

List all components involved:
1. [Component 1: e.g., Login API endpoint]
2. [Component 2: e.g., User database]
3. [Component 3: e.g., Session store]

---

### Data Flow

Describe how data flows:
1. User submits credentials → Login API
2. Login API queries User DB
3. On success, create session in Session Store
4. Return session token to user

---

### Threats Identified

#### Spoofing
- [ ] **Threat**: Attacker uses stolen credentials
  - **Mitigation**: Implement MFA
  - **Priority**: High

#### Tampering
- [ ] **Threat**: Man-in-the-middle modifies login request
  - **Mitigation**: Enforce HTTPS/TLS 1.3
  - **Priority**: Critical

#### Repudiation
- [ ] **Threat**: User denies login action
  - **Mitigation**: Log all authentication events with timestamp
  - **Priority**: Medium

#### Information Disclosure
- [ ] **Threat**: Verbose error reveals username existence
  - **Mitigation**: Generic error message "Invalid credentials"
  - **Priority**: Medium

#### Denial of Service
- [ ] **Threat**: Brute force attack exhausts server resources
  - **Mitigation**: Rate limiting (5 attempts/minute)
  - **Priority**: High

#### Elevation of Privilege
- [ ] **Threat**: Session fixation allows privilege escalation
  - **Mitigation**: Regenerate session ID on login
  - **Priority**: High

---

### Risk Summary

Total threats identified: [N]
- Critical: [N]
- High: [N]
- Medium: [N]
- Low: [N]

**Overall Risk Level**: [Critical/High/Medium/Low]

Security Checklist (Pre-Deployment)

Use this before deploying any code to production:

Authentication & Authorization

• Strong password policy enforced (12+ chars, complexity)
• MFA available for sensitive accounts
• Session timeout configured (15-30 minutes)
• Secure session cookies (HttpOnly, Secure, SameSite)
• Authorization checks on all endpoints
• Default deny (whitelist approach)

Input Validation

• All user input validated (whitelist preferred)
• Parameterized queries used (no string concatenation)
• File upload restrictions (type, size, content)
• Output encoding for XSS prevention

Cryptography

• TLS 1.2+ enforced for all connections
• Passwords hashed with bcrypt/Argon2
• No hardcoded secrets
• Secrets in environment variables or vault
• Secure random generators used (secrets module)

Error Handling

• Generic error messages (no stack traces)
• Errors logged with context (user, IP, timestamp)
• No sensitive data in logs

Security Headers

• Content-Security-Policy configured
• X-Content-Type-Options: nosniff
• X-Frame-Options: DENY or SAMEORIGIN
• Strict-Transport-Security (HSTS)
• X-XSS-Protection: 1; mode=block

Logging & Monitoring

• Authentication events logged
• Authorization failures logged
• Security alerts configured
• Log retention policy defined

Dependencies

• No known vulnerabilities (npm audit, pip-audit)
• Dependencies up to date
• Unused dependencies removed
• CI/CD includes security scanning

Infrastructure

• Debug mode disabled in production
• Default credentials changed
• Unnecessary services disabled
• Network segmentation implemented
• Rate limiting configured

Reference Materials

Detailed Guides:

•OWASP Top 10: https://owasp.org/www-project-top-ten/
•STRIDE Methodology: https://learn.microsoft.com/en-us/azure/security/develop/threat-modeling-tool-threats
•CVSS Calculator: https://www.first.org/cvss/calculator/3.1
•CWE Database: https://cwe.mitre.org/

Secure Coding Guides:

•OWASP Cheat Sheet Series: https://cheatsheetseries.owasp.org/
•NIST Secure Software Development Framework: https://csrc.nist.gov/projects/ssdf

Tools:

•Static Analysis: Bandit (Python), ESLint (JS), cargo-audit (Rust)
•Dependency Scanning: Snyk, Dependabot, npm audit
•Dynamic Analysis: OWASP ZAP, Burp Suite

Self-Assessment

After applying security analysis, verify:

• STRIDE Coverage: All 6 threat categories considered for this component
• OWASP Awareness: Top 10 vulnerabilities reviewed and mitigated
• Risk Scoring: Vulnerabilities scored and prioritized
• Secure Patterns: Code review patterns applied
• Checklist Completion: Pre-deployment checklist 100% complete
• Documentation: Threat model and mitigations documented
• Testing: Security tests written (auth bypass, injection, etc.)

Confidence Level:

•High (90%+): All frameworks applied, threat model complete, security tests passing
•Medium (70-89%): Main threats addressed, some edge cases remain
•Low (<70%): Significant security gaps identified - continue working

Summary

Security Analysis Skills provide systematic frameworks for integrating security into all development work:

•STRIDE Threat Modeling: Identify threats by category (Spoofing, Tampering, Repudiation, Information Disclosure, DoS, Elevation of Privilege)
•OWASP Top 10: Address most critical web vulnerabilities
•CVSS Risk Scoring: Quantify and prioritize vulnerability remediation
•Secure Coding Patterns: Apply proven security patterns in code review

Remember: Security is not a feature, it's a requirement. Apply these frameworks proactively during design and development, not reactively after incidents.

Target: Zero Critical/High vulnerabilities in production deployments.