| name | critical-interval-security-checker |
| description | Analyzes code to identify security-critical time intervals and timing vulnerabilities in authentication, authorization, and time-sensitive security operations. Use this skill when reviewing code for proper timeout enforcement, token expiration, session management, rate limiting, password reset validity, or any time-sensitive security mechanism. Detects missing expiration checks, excessive timeout values, lack of rate limiting, client-side only validation, hardcoded timeouts, and timing attack vulnerabilities. Triggers when users ask to check security timeouts, verify token expiration handling, audit session timeout implementation, review rate limiting, or analyze time-based security controls. |
Critical Interval Security Checker
Analyze code to identify security-critical time intervals and timing vulnerabilities that could compromise security.
Workflow
1. Identify Security-Critical Operations
Look for code that handles:
- Authentication: Login, logout, token generation
- Session management: Session creation, validation, expiration
- Password operations: Reset tokens, change requests
- Rate limiting: Login attempts, API calls, password resets
- Token operations: JWT, OAuth tokens, API keys
- MFA: OTP codes, push notifications, backup codes
2. Check for Common Vulnerabilities
See vulnerability_patterns.md for detailed patterns.
Critical checks:
- Missing expiration validation
- Excessive timeout values
- No rate limiting on sensitive endpoints
- Client-side only expiration checks
- Race conditions in expiration logic
- Hardcoded timeout values
- Inconsistent timeout enforcement
- Timezone handling issues
- Timing attack vulnerabilities
3. Use Automated Checker
Run the automated checker script:
python scripts/check_intervals.py path/to/file.py
python scripts/check_intervals.py src/
python scripts/check_intervals.py src/ --language python
The script detects:
- 🔴 Critical: JWT decode without verification, timing attacks
- 🟠 High: Missing expiration checks, no rate limiting
- 🟡 Medium: Excessive timeouts, inconsistent enforcement
- 🔵 Low: Hardcoded timeouts, magic numbers
4. Manual Code Review
For each security-critical operation, verify:
Expiration is set:
token_expiry = datetime.utcnow() + timedelta(hours=1)
Expiration is checked:
if datetime.utcnow() > token_expiry:
raise TokenExpiredError()
Timeout is reasonable:
RESET_TOKEN_EXPIRY = timedelta(hours=1)
RESET_TOKEN_EXPIRY = timedelta(days=7)
Rate limiting exists:
@limiter.limit("5 per 15 minutes")
def login():
pass
Server-side enforcement:
decoded = jwt.decode(token, SECRET_KEY)
decoded = jwt.decode(token, options={"verify_signature": False})
5. Verify Against Standards
Consult time_intervals.md for recommended values:
Common intervals:
- JWT access token: 5-15 minutes
- JWT refresh token: 7-30 days
- Session timeout: 15-30 minutes (idle), 8-12 hours (absolute)
- Password reset token: 15-60 minutes
- Login rate limit: 5 attempts per 15 minutes
- TOTP code: 30 seconds
- SMS/Email OTP: 5-10 minutes
Check if intervals match use case:
- High-security apps need shorter timeouts
- User-facing apps balance security and UX
- API tokens can be shorter-lived with refresh tokens
6. Document Findings
For each issue found, document:
Issue: Missing expiration check on password reset token
Location: auth/reset_password.py:45
Severity: High
Current: Token created with expiry but never validated
Recommendation: Add expiration check before using token
Code fix:
if datetime.utcnow() > token.expires_at:
raise TokenExpiredError("Reset token expired")
7. Propose Fixes
Fix missing expiration checks:
def validate_token(token):
decoded = jwt.decode(token, SECRET_KEY, options={"verify_signature": False})
return decoded['user_id']
def validate_token(token):
try:
decoded = jwt.decode(token, SECRET_KEY)
return decoded['user_id']
except jwt.ExpiredSignatureError:
raise AuthenticationError("Token expired")
Fix excessive timeouts:
RESET_TOKEN_EXPIRY = timedelta(days=7)
RESET_TOKEN_EXPIRY = timedelta(hours=1)
Add rate limiting:
@app.route('/login', methods=['POST'])
def login():
pass
@app.route('/login', methods=['POST'])
@limiter.limit("5 per 15 minutes")
def login():
pass
Fix hardcoded timeouts:
expiry = datetime.utcnow() + timedelta(seconds=3600)
SESSION_TIMEOUT = timedelta(hours=1)
expiry = datetime.utcnow() + SESSION_TIMEOUT
Quick Reference
Critical Vulnerabilities
Missing expiration check:
- Token/session has expiry field but it's never validated
- High risk: Expired tokens still work
No rate limiting:
- Authentication endpoints without throttling
- High risk: Brute force attacks
Client-side only validation:
- Expiration checked in frontend but not backend
- Critical risk: Easily bypassed
Excessive timeouts:
- Reset tokens valid for days
- Sessions never expire
- Medium risk: Extended attack window
Detection Patterns
Python:
jwt.decode(..., verify=False)
timedelta(days=7)
@limiter.limit
datetime.now() vs datetime.utcnow()
JavaScript:
jwt.decode(...)
Date.now() < exp
rateLimit(...)
setTimeout(..., 86400000)
Java:
Jwts.parser()
Duration.ofDays(30)
@RateLimit
Helper Script
The check_intervals.py script automates detection:
python scripts/check_intervals.py src/ --language python
python scripts/check_intervals.py src/ --language javascript
python scripts/check_intervals.py src/
Output provides:
- Categorized issues by severity
- File and line number
- Issue description
- Fix recommendation
Best Practices
Always:
- Set expiration times for all security tokens
- Validate expiration server-side
- Use reasonable timeout values
- Implement rate limiting on auth endpoints
- Use UTC for all timestamps
- Use named constants for timeouts
- Document timeout decisions
Never:
- Skip expiration validation
- Use client-side only checks
- Set excessive timeout values
- Use magic number timeouts
- Mix timezone-aware and naive datetimes
- Use non-constant-time comparisons for secrets