business-logic-flaws-ai-generated-code

Race conditions occur when multiple concurrent requests access shared resources without proper synchronization, allowing overselling or data corruption. This Skill identifies these flaws in AI-generated code by analyzing concurrent access patterns in flash sales, inventory systems, and financial transactions, then recommends database locking and distributed locking strategies to prevent them.

Business logic vulnerabilities like race conditions, integer overflow, and negative totals often don't trigger during single-threaded testing. This Skill uncovers these hidden flaws that emerge under concurrent load, revealing how 100 simultaneous requests could oversell inventory or corrupt financial calculations that unit tests miss.

Critical vulnerabilities include race conditions during concurrent access, integer overflow in calculations, negative account balances, excessive discounts, and overselling. This Skill analyzes AI-generated code across web services and APIs to detect these patterns and provides actionable remediation using database transactions with locking and distributed locking strategies.

Overselling occurs when concurrent requests bypass inventory checks. This Skill identifies where AI-generated code lacks proper locking mechanisms, then documents secure patterns using database transactions and distributed locking to ensure inventory counts remain accurate under simultaneous purchases.

Yes. This Skill applies to AI-generated code across web services, APIs, and transaction-heavy systems. It detects business logic vulnerabilities specific to concurrent scenarios, validates handling of edge cases, and provides implementation patterns for secure APIs that prevent race conditions and calculation errors.

Race conditions are timing-dependent flaws that emerge only under concurrent load, unlike syntax or obvious logic errors. This Skill specializes in identifying these subtle concurrency vulnerabilities in AI-generated code where functional tests pass but real-world concurrent access causes financial loss or data corruption.