Business Logic Flaws Scanner
AI-powered detection of application-specific business logic vulnerabilities.
What is Business Logic Flaws?
Business logic flaws are vulnerabilities in application workflows and rules rather than technical issues. Examples include bypassing payment by manipulating workflow order, applying coupons multiple times, or exploiting race conditions in inventory management. These are specific to each application's logic.
Why is This Important?
Business logic flaws can have severe financial impact—bypassing payments, getting refunds on kept items, or obtaining services for free. They're often missed by automated scanners because they require understanding of how the application should work.
How It Works
1. Web Crawling
Intelligent crawling discovers all endpoints, forms, parameters, and dynamic content across your web application.
2. Payload Injection
AI-powered payloads test each input vector for web vulnerabilities with context-aware attack patterns.
3. Response Analysis
Advanced analysis detects vulnerability signatures in responses, confirming exploitability with proof-of-concept.
Key Capabilities
Industry-leading web security testing powered by AI, trusted by security teams worldwide for accurate vulnerability detection.
- Deep web crawling with JavaScript rendering support
- Context-aware payload generation for each parameter
- False positive elimination through response analysis
- OWASP Top 10 and CWE compliance mapping
- Seamless CI/CD and DevSecOps integration
Frequently Asked Questions
Why can't scanners find logic flaws automatically?
Logic flaws depend on understanding intended business rules. A scanner doesn't know that negative quantities shouldn't give refunds or that coupons should only apply once.
What are common business logic vulnerabilities?
Price manipulation, coupon abuse, workflow bypass, inventory manipulation, privilege escalation through parameter tampering, and race conditions in financial transactions.
How do you test for logic flaws?
Manual testing with understanding of business rules, attempting each step out of order, using negative values, testing limits and boundaries, and thinking like a malicious user.
How does AI help detect logic flaws?
AI can learn normal application patterns and flag anomalies, identify parameter manipulation opportunities, and test workflow sequences that humans might miss.
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