Chai: Agentic Discovery of Cryptographic Misuse Vulnerabilities
AI-assisted vulnerability discovery has proven effective for bug classes like memory safety, where instrumentation confirms memory violations and efficiently filters false positives. Many dangerous vulnerability classes, such as cryptographic misuse, however, lack any comparable instrumentation. In this work, we present Chai, an AI-based system that discovers and validates cryptographic misuse vulnerabilities through naturally occurring signals. To achieve this, Chai rethinks the classical technique of differential testing by leveraging AI to 1) improve precision for detecting real security issues in libraries, and 2) repurpose commonly overlooked discrepancies as leads for tangible vulne...
| Authors | Corban Villa, Sohee Kim, Austin Chu et al. |
|---|---|
| Primary category | cs.CR |
| Published | 25 June 2026 |
| Last updated at source | 25 June 2026 |
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