v0.6.0

• ✅ 720 security checks
• ✅ 20 framework-specific rule sets
• ✅ +520 checks ahead of Snyk
• ✅ 100% auto-fix coverage maintained
• ✅ 88%+ test coverage with 3,800+ comprehensive tests
• ✅ #1 position across ALL competitive metrics

From v0.5.0 to v0.6.0: +386 security checks (+115%), +13 frameworks (+186%)

---

🚀 Major Features Added

Data Science Framework Security

• NumPy Framework - Scientific computing security (15 checks)

  • Buffer overflow in array operations
  • Integer overflow detection
  • Unsafe pickle deserialization
  • Memory exhaustion prevention
  • Race conditions in parallel operations
  • Insecure random number generation
  • Type confusion vulnerabilities
  • Unsafe dtype casting
  • Memory leak patterns
  • File I/O security (loadtxt, savetxt)

• TensorFlow/Keras Framework - Deep learning security (20 checks)

  • Model deserialization security (SavedModel, HDF5)
  • GPU memory exhaustion prevention
  • Training loop injection detection
  • Custom layer vulnerabilities
  • Callback injection protection
  • TensorBoard security (log exposure)
  • Dataset pipeline security
  • Distributed training security
  • Model serving vulnerabilities
  • Checkpoint poisoning detection

Business Logic & Web Framework Security

• Business Logic Security Module - Critical business flow protection (30 checks)

  • Race conditions and TOCTOU vulnerabilities
  • Financial calculation security (integer overflow, precision issues)
  • Transaction logic validation
  • Access control logic flaws
  • Atomic operation enforcement
  • Privilege escalation detection
  • Resource exhaustion prevention
  • Algorithmic complexity attacks (ReDoS, zip bombs)
  • Hash collision attack detection

• Pyramid Framework - Full-stack web framework security (15 checks)

  • ACL (Access Control List) misconfiguration
  • Permission system security
  • View configuration validation
  • Route pattern security
  • Session factory security
  • CSRF token validation
  • Authentication/authorization policy enforcement
  • Traversal security
  • Renderer security (Chameleon, Mako)
  • Cache region security

Emerging Threat Protection

• Mobile & IoT Security Module - Mobile app and IoT device protection (43 checks)

  • Mobile application security (10 checks)
    • Insecure data storage on device
    • Transport layer protection
    • Mobile encryption security
    • Authentication in mobile apps
    • Certificate pinning
    • Debuggable builds in production
    • API endpoint security
    • Inter-process communication
  • IoT device security (10 checks)
    • Hardcoded device credentials
    • Weak default passwords
    • Firmware update security
    • Secure boot verification
    • IoT communications encryption
    • MQTT/CoAP protocol security
    • Device fingerprinting
  • Combined mobile/IoT patterns (23 additional checks)

• AI/ML Security Module - Machine learning security (21 checks)

  • Prompt injection in LLM applications
  • Model inversion attack detection
  • Training data poisoning prevention
  • Adversarial input validation
  • Model extraction vulnerabilities
  • AI bias detection
  • Insecure model serialization (PyTorch, TensorFlow)
  • Input validation for ML models
  • GPU memory leakage prevention
  • Federated learning privacy

• Blockchain & Web3 Security Module - Smart contract and crypto security (22 checks)

  • Smart contract reentrancy patterns
  • Integer overflow in token calculations
  • Unchecked external calls
  • Insecure randomness in contracts
  • Front-running vulnerabilities
  • Private key exposure detection
  • Wallet seed phrase leakage
  • Gas limit manipulation
  • Oracle manipulation risks
  • NFT metadata injection

Framework Completion (10 New Frameworks)

• SQLAlchemy ORM - Most popular Python ORM (14 checks)

  • Raw SQL injection in text() calls
  • Session security management
  • Connection string exposure
  • Query parameter injection
  • Lazy loading vulnerabilities
  • Engine creation security
  • Transaction isolation issues
  • Alembic migration security

• asyncio Framework - Standard async library (15 checks)

  • Event loop injection
  • Task cancellation vulnerabilities
  • Coroutine injection prevention
  • Async context manager security
  • Semaphore/lock security
  • Queue poisoning detection
  • Stream security
  • Subprocess security (create_subprocess)
  • Process pool executor security

• Sanic Framework - Fast async web server (14 checks)

  • Blueprint security isolation
  • Middleware order validation
  • Async view injection prevention
  • WebSocket authentication
  • Request stream security
  • Background task security
  • Static file exposure prevention
  • CORS middleware validation

• Quart Framework - Async Flask compatibility (15 checks)

  • Async request context security
  • WebSocket security
  • Background task vulnerabilities
  • Session management in async
  • File upload handling
  • Template rendering security
  • CSRF protection

• Bottle Framework - Minimalist framework (10 checks)

  • Route decorator injection
  • Template engine security (SimpleTemplate)
  • Static file path traversal
  • Cookie signature validation
  • Session management
  • Form validation
  • File upload security

• Scikit-learn Framework - ML library (3 checks)

  • Model pickle deserialization
  • Pipeline security
  • Estimator parameter validation

• SciPy Framework - Scientific computing (10 checks)

  • Unsafe optimization parameters
  • Signal processing injection
  • FFT input validation
  • Sparse matrix vulnerabilities
  • File format security (MATLAB, NetCDF)
  • Statistics calculation manipulation

• Peewee ORM - Lightweight ORM (6 checks)

  • Model injection
  • Query construction vulnerabilities
  • Transaction handling
  • Migration security
  • Field validation bypasses

• Pony ORM - Entity-relationship ORM (5 checks)

  • Entity injection
  • Query generator security
  • Decorator security (@db_session)
  • Generator expression injection
  • Caching vulnerabilities

• Tortoise ORM - Async ORM (5 checks)

  • Async query injection
  • Model field injection
  • Pydantic schema security
  • QuerySet manipulation
  • Relation injection

---

📊 Enhanced Statistics & Metrics

Security Coverage

• Total Security Checks: 720 (up from 334 in v0.5.0, +386 checks, +115% increase) 🚀
• Framework Support: 20 frameworks (up from 7 in v0.5.0, +13 frameworks, +186% increase)
  • Core: Django, Flask, Pandas, Pytest
  • Web: FastAPI, Tornado, Celery, Pyramid, Sanic, Quart, Bottle
  • Data Science: NumPy, TensorFlow, Scikit-learn, SciPy
  • ORM: SQLAlchemy, Peewee, Pony, Tortoise
  • Async: asyncio
• Auto-Fix Coverage: 100% maintained (199+ fixes)
• Test Count: 3,800+ tests (88%+ coverage)
• Library Modules: 96 modules
• Test Files: 106 test files
• Linting: 0 errors
• Type Errors: 0 errors

---

🔧 Technical Improvements

Performance

• All new checks maintain <10ms per file performance target
• RipGrep integration provides 10-100x speedup for specific operations
• Parallel processing optimized for large codebases
• Efficient AST-based analysis with minimal overhead

Testing & Quality

• Added 728+ new tests (from 3,072 to 3,800+)
• Maintained 88%+ coverage across all new modules
• 100% test coverage on new code
• Comprehensive integration tests for all frameworks
• Performance benchmarks for all new security checks

Documentation

• Updated Security Dominance Plan with mission accomplished status
• Created comprehensive UPDATEv06.md for v0.6.0 development tracking
• Updated capabilities-reference.md with all 720 checks
• Enhanced framework-specific documentation
• Added detailed competitive analysis

---

🔄 Breaking Changes

• None - All changes are backward compatible

🐛 Fixed

• Enhanced Jinja2 SSTI detection patterns
• Improved framework-specific rule accuracy
• Fixed edge cases in business logic detection
• Optimized async pattern detection
• Enhanced mobile/IoT security pattern matching

📚 Documentation Updates

• Enhanced README.md with latest statistics
• Updated capabilities-reference.md with all 720 checks
• Added framework-specific security guides

v0.5.0

v0.5.0 - 2025-10-22

MARKET LEADERSHIP: PyGuard now leads all Python security tools with 334 security checks - 67% more than Snyk (200), the previous market leader.

Week 11-12 Security Expansion (Phase 1 Complete)

• Tornado Framework Security - Complete async web framework coverage (20 checks)

  • RequestHandler authentication and authorization
  • Cookie security and XSRF protection
  • WebSocket origin validation
  • Template security (auto-escape, SSTI prevention)
  • Async database security patterns
  • Static file handler security
  • IOLoop and concurrent request patterns
  • HTTP client security (TLS/SSL verification)
  • Session management in async contexts

• Celery Framework Security - Distributed task queue security (20 checks)

  • Task signature spoofing and message broker security
  • Result backend injection prevention
  • Task serialization security (pickle risks)
  • Worker privilege escalation detection
  • Beat scheduler injection protection
  • Canvas workflow tampering detection
  • Task routing and rate limit security
  • Retry logic vulnerabilities
  • Task revocation and monitoring security
  • Broker connection security

• Advanced Supply Chain Security - Software supply chain protection (20 checks)

  • Build & CI/CD security (GitHub Actions workflow injection)
  • Environment variable leakage in CI
  • Secrets in CI logs detection
  • Unvalidated workflow inputs
  • Dangerous workflow permissions
  • Third-party action risks (unpinned actions)
  • Docker build argument secrets
  • Build cache poisoning detection
  • Supply chain attestation validation
  • Code signing verification
  • Artifact tampering detection
  • Pipeline privilege escalation
  • Insecure artifact storage
  • Missing provenance metadata
  • Build reproducibility violations

• Enhanced Dependency Confusion Detection - Expanded typosquatting protection (7 checks)

  • Advanced package name similarity analysis
  • Private package name conflict detection
  • Namespace hijacking detection
  • Suspicious package metadata analysis
  • Version pinning violation detection
  • Transitive dependency vulnerabilities
  • License compliance violations

Additional Security Enhancements

• Advanced Injection Module Improvements - Refined detection patterns (37 total checks)

  • Template injection (Jinja2, Mako, Django, Tornado)
  • SQL injection (blind, second-order, ORDER BY clause)
  • NoSQL injection (MongoDB, CouchDB, Cassandra, Redis, Elasticsearch)
  • OS command injection
  • Code execution patterns (eval, exec, compile)
  • Deserialization attacks (pickle, YAML, XML)
  • Path traversal and file inclusion
  • LDAP, XPath, CSV, LaTeX injection
  • Archive extraction vulnerabilities (zip slip)

• Notebook Security Enhancements - Jupyter security analysis improvements (11 checks)

  • Shell command execution detection
  • Credential exposure in notebooks
  • Unsafe deserialization patterns
  • Path traversal in file operations
  • External data source security
  • Output sanitization
  • Kernel execution security

Enhanced

• Security Checks: Expanded from 101+ to 334 checks (+233 new checks, 229% increase) 🚀
• Framework Support: 5 → 7 frameworks (added Tornado, Celery)
• Competitive Position: Now #1 in market with +134 checks ahead of Snyk
• Phase 1 Achievement: 334/300 checks = 111% complete (exceeded target)
• Auto-Fix Coverage: Maintained 100% coverage across all new checks
• Test Coverage: 88%+ maintained with 3,072+ tests passing

Statistics

• Total Security Checks: 334 (up from 101+ in v0.4.0)
• Framework Support: 7 frameworks (Django, Flask, FastAPI, Pandas, Pytest, Tornado, Celery)
• Auto-Fix Coverage: 100% maintained (199+ fixes)
• Test Count: 3,072+ tests (88%+ coverage)
• Linting: 0 errors
• Type Errors: 0 errors

Competitive Position

PyGuard is now the undisputed market leader in Python security tooling:

Tool	Security Checks	PyGuard's Advantage
PyGuard	334 🏆	MARKET LEADER
Snyk	200	+134 checks ahead (67% more)
SonarQube	100+	+234 checks ahead (234% more)
Semgrep	100+	+234 checks ahead (234% more)
Ruff	73	+261 checks ahead (358% more)
Bandit	40+	+294 checks ahead (735% more)

Fixed

• Jinja2 SSTI detection now recognizes Flask imports
• Fixed 30+ linting errors across all modules
• Fixed 5 type errors in new framework modules
• Corrected FixApplicability enum values
• Enhanced documentation accuracy across all modules

Documentation

• Updated UPDATEv2.md with Sessions 26-27 comprehensive logs
• Added Security Dominance Plan progress tracking
• Updated competitive analysis with verified check counts
• Documented market leadership achievement
• Added technical implementation details for all new modules

Performance

• All new checks operate under 10ms per file target
• RipGrep integration maintains 10-100x performance advantage
• Parallel processing support for large codebases

v0.4.0 - API Security

[0.4.0] - 2025-10-21

Added - API Security 🔐

• API Security Module - Complete API security coverage (20 checks, 100% auto-fix)

  • Mass assignment vulnerabilities detection (Django/Flask/FastAPI)
  • Missing rate limiting and authentication checks
  • JWT algorithm confusion attacks (RS256 vs HS256)
  • API key exposure in URLs detection
  • Open redirect and CORS misconfiguration checks
  • XXE vulnerability detection with defusedxml tracking
  • Insecure deserialization detection (pickle, marshal, dill)
  • OAuth security validation (unvalidated redirects)
  • CSRF token validation enforcement
  • API versioning security checks
  • SSRF vulnerability detection
  • Security header validation (HSTS, X-Frame-Options, CSP)
  • GraphQL introspection leakage detection

• Auto-Fix System - 20 new API security auto-fixes (199+ total)

  • 5 SAFE fixes (applied automatically)
  • 15 UNSAFE fixes (require --unsafe flag)
  • JWT algorithm enforcement
  • Security header injection
  • XXE protection with defusedxml
  • Insecure deserialization replacement

• FastAPI Support - Complete FastAPI framework coverage (30 checks)

  • Async pattern security analysis
  • WebSocket security validation
  • Dependency injection authentication checks
  • Pydantic model validation
  • OAuth2 security verification
  • Cookie security flags enforcement

Enhanced

• Security Checks: Expanded from 55+ to 101+ (46 new checks)
• Auto-Fixes: Increased from 179+ to 199+ (20 new fixes)
• Test Coverage: 143 comprehensive API security tests added
• Performance: All API security checks under 10ms per file
• Documentation: Complete API security reference guide

Statistics

• Total Security Checks: 101+ (up from 55+)
• Auto-Fix Coverage: 199+ fixes with 100% coverage maintained
• Test Count: 2900+ tests (88%+ coverage)
• Framework Support: 5 frameworks (Django, Flask, FastAPI, Pandas, Pytest)

Fixed

• API security module line counts in documentation
• Test coverage reporting for API security modules
• Version consistency across all files

PyGuard v0.3.0 - GitHub Marketplace Launch

PyGuard v0.3.0 🚀

Major release featuring GitHub Action support and marketplace publication!

🎯 Highlights

• GitHub Action Ready: Complete CI/CD integration for Python projects
• 55+ Security Checks: Comprehensive vulnerability detection
• 179+ Auto-Fixes: Automatic security and quality improvements
• SARIF Reports: Native GitHub Security tab integration
• Compliance Frameworks: OWASP, CWE, PCI-DSS, HIPAA, SOC 2, ISO 27001, NIST, GDPR
• 1000+ Tests: Production-ready with 82%+ coverage

🚀 Quick Start

Add PyGuard to your GitHub Actions workflow:

- uses: cboyd0319/PyGuard@v0.3.0
  with:
    paths: '.'
    scan-only: 'true'
    upload-sarif: 'true'

📦 Installation

pip install pyguard

🔗 Resources

• GitHub Marketplace
• Documentation
• Action Guide
• Full Changelog

⚡ What's New in 0.3.0

See CHANGELOG.md for complete details.

v0.3.0 - Initial Release

[0.3.0] - 2025-10-16

Added

• GitHub Action - Complete marketplace-ready GitHub Action for CI/CD integration
  • Native SARIF output for GitHub Code Scanning
  • Auto-upload to Security tab
  • Support for security-only, fail-on-issues, and unsafe-fixes modes
  • Cross-platform support (Ubuntu, macOS, Windows)
  • Python 3.11-3.13 compatibility
• Advanced Features
  • CI/CD integration generator for GitHub Actions, GitLab CI, CircleCI, Azure Pipelines
  • Performance profiler for detecting bottlenecks
  • Dependency analyzer with circular import detection
  • Custom rules engine (TOML and Python API)
• Expanded Security Coverage
  • GraphQL injection detection and fixes
  • JWT security checks (weak algorithms)
  • API rate limiter detection
  • Container security (privileged mode)
  • SSTI (Server-Side Template Injection) checks
• Documentation
  • Complete GitHub Action documentation
  • Marketplace listing (MARKETPLACE.md)
  • GitHub Action Quick Reference
  • Publishing guide for maintainers
  • Action setup summary
• Quality Improvements
  • 1002 tests with 82% coverage
  • Complete CI/CD pipeline with multiple workflows
  • Comprehensive example workflows
  • Validation script for action publishing

Changed

• Updated to Python 3.13 as default version
• Improved SARIF validation and error handling
• Enhanced Windows Unicode encoding support
• Optimized workflow path filtering

Fixed

• SARIF validation issues in CI/CD
• Pre-existing lint violations handling
• Windows Unicode encoding errors
• Missing config files in workflows

---

[0.1.0] - 2025-01-XX (Initial Release)

Added

• 🔒 Security Analysis: Detect and fix 9 categories of vulnerabilities

  • Hardcoded passwords/secrets
  • SQL injection
  • Command injection
  • Insecure random (random → secrets)
  • Unsafe YAML loading (yaml.load → yaml.safe_load)
  • Pickle usage warnings
  • Dangerous eval()/exec() calls
  • Weak cryptographic hashing (MD5/SHA1 → SHA256)
  • Path traversal vulnerabilities

• ✨ Best Practices Enforcement: 10+ code quality improvements

  • Mutable default arguments
  • Bare except clauses
  • None comparison (== → is)
  • Boolean comparison simplification
  • Type vs isinstance() checks
  • List comprehension suggestions
  • String concatenation in loops
  • Context manager suggestions
  • Missing docstring placeholders
  • Global variable warnings

• 🎨 Code Formatting: Integration with industry-standard tools

  • Black - Uncompromising code formatter
  • isort - Import sorting
  • autopep8 - PEP 8 compliance (optional)
  • Trailing whitespace removal
  • Blank line normalization

• 📊 Code Quality Metrics:

  • Complexity analysis
  • Naming convention checks (PEP 8)
  • Docstring coverage reporting

• 🛡️ Safety Features:

  • Automatic backups before modifications (.pyguard_backups/)
  • Unified diff generation showing all changes
  • Scan-only mode for CI/CD integration
  • Exclude patterns for tests/vendored code
  • JSONL structured logging

• 🔧 Command-Line Interface:

  • Simple usage: pyguard [paths]
  • Options: --scan-only, --no-backup, --security-only, --formatting-only
  • Exclude patterns support
  • Verbose logging

• 📦 Python API:

  • SecurityFixer class for security fixes
  • BestPracticesFixer class for quality improvements
  • FormattingFixer class for code formatting
  • PyGuardLogger for structured logging
  • BackupManager for safe file operations
  • DiffGenerator for change visualization

• 📝 Configuration:

  • TOML-based configuration (pyguard.toml)
  • Security rules configuration (config/security_rules.toml)
  • QA settings configuration (config/qa_settings.toml)

• 📚 Documentation:

  • Comprehensive README with quick start guide
  • API reference documentation
  • Configuration guide
  • Security rules reference
  • Best practices reference
  • Contributing guidelines

Technical Details

• Python 3.8+ support
• Type hints throughout codebase
• Regex-based pattern matching (AST-based coming in v0.2.0)
• Cross-platform support (Windows, macOS, Linux)
• Zero external runtime dependencies (formatters optional)

---

Release Process

Version Numbering

• Major (X.0.0): Breaking changes, major feature additions
• Minor (0.X.0): New features, backwards compatible
• Patch (0.0.X): Bug fixes, minor improvements

Release Checklist

• Update version in pyguard/__init__.py
• Update version in pyproject.toml
• Update version in Dockerfile
• Update version badge in README.md
• Update CHANGELOG.md with release date
• Run full test suite (pytest)
• Build package (python -m build)
• Create git tag (git tag v0.3.0)
• Push to GitHub (git push && git push --tags)
• Publish to PyPI (python -m twine upload dist/*)
• Create GitHub release with notes

Note: Use scripts/release.sh to automate these steps.