Understanding Vulnerability Patterns and Classifications

Security vulnerabilities follow predictable patterns that tools can identify through code analysis. Injection vulnerabilities occur when applications accept untrusted input without proper validation or sanitization. Detection tools trace data flow from input sources through application logic to dangerous sinks like database queries or system commands. By understanding these patterns, tools can identify potential SQL injection, command injection, or cross-site scripting vulnerabilities even in complex codebases.

Authentication and authorization flaws represent another major vulnerability category requiring sophisticated detection. Tools analyze code paths to ensure proper authentication checks before sensitive operations. They identify missing authorization validations, privilege escalation opportunities, and session management weaknesses. Modern detection engines understand framework-specific authentication patterns, reducing false positives while catching framework misuse that creates vulnerabilities.

Business logic vulnerabilities challenge traditional detection approaches because they depend on application-specific requirements rather than generic patterns. Race conditions, time-of-check-time-of-use issues, and improper state management require understanding intended application behavior. Advanced detection tools use symbolic execution and model checking to identify these subtle vulnerabilities. Machine learning models trained on labeled vulnerability data increasingly supplement rule-based detection for complex vulnerability types.