Business Logic Vulnerabilities
Business logic vulnerabilities exploit flaws in the design and implementation of application workflows. These vulnerabilities are often unique to each application and require intelligent testing.What are Business Logic Flaws?
Unlike technical vulnerabilities (SQL injection, XSS), business logic flaws abuse legitimate functionality in unintended ways. They typically:- Cannot be detected by automated scanners (but AIPTx’s AI can!)
- Require understanding of application context
- Exploit assumptions in application design
- Have high business impact
Common Categories
Price Manipulation
Negative Quantities
Submitting negative item quantities for refunds
Price Override
Modifying prices in client-side requests
Currency Confusion
Exploiting currency conversion logic
Discount Abuse
Stacking or manipulating discounts
Example: Price Manipulation
Race Conditions
Types Detected
| Type | Description | Example |
|---|---|---|
| TOCTOU | Time-of-check to time-of-use | Balance check vs debit |
| Double Spending | Same resource used twice | Coupon reuse |
| Concurrent Updates | Parallel modifications | Simultaneous withdrawals |
Testing Methodology
AIPTx tests race conditions by:- Identifying vulnerable operations (balance transfers, inventory updates)
- Sending concurrent requests with precise timing
- Analyzing state inconsistencies
- Validating exploitation
Example: Double Spending
Workflow Bypass
Authentication Workflow
| Step | Bypass Test |
|---|---|
| 1. Login | Skip to step 2 |
| 2. MFA | Skip to step 3 |
| 3. Dashboard | Access directly |
Example: MFA Bypass
Multi-Step Process Bypass
Testing e-commerce checkout:Limit Bypass
Types
- Rate limit bypass
- Quantity limit bypass
- Time-based restriction bypass
- Geographic restriction bypass
Example: Rate Limit Bypass
Inventory Manipulation
Testing Scenarios
Feature Abuse
Common Abuse Patterns
| Feature | Abuse | Impact |
|---|---|---|
| Referral program | Self-referral | Financial loss |
| Free trial | Unlimited trials | Revenue loss |
| Promo codes | Code enumeration | Unauthorized discounts |
| File upload | Storage abuse | Resource exhaustion |
Example: Referral Abuse
Data Validation Flaws
Insufficient Validation
AI-Powered Detection
AIPTx uses AI to detect business logic flaws by:- Understanding Context - Analyzing application purpose and workflows
- Identifying Assumptions - Finding implicit business rules
- Generating Test Cases - Creating context-aware tests
- Validating Results - Confirming exploitability
AI Detection Examples
Remediation Guidelines
Server-Side Validation
Server-Side Validation
Race Condition Prevention
Race Condition Prevention
Workflow Enforcement
Workflow Enforcement