The Next Big Thing in AppSec: LLM Discovery and Security Testing

As technology advances, the evolution from Dynamic Application Security Testing (DAST) to API security, and now to Large Language Model (LLM) security testing, reflects the increasing complexity of digital interfaces. The GenAI Application Security Report by Pynt highlights the rapid integration of AI into organizational systems, with 98% of respondents already adopting AI, making LLMs a fundamental aspect rather than a competitive advantage. This shift necessitates a new category in security visibility: LLM Discovery, which involves mapping the use of models, data interactions, and access controls. LLM security testing focuses on understanding contextual behavior, with vulnerabilities arising from reasoning flaws rather than traditional code injections. The report underscores the importance of securing the entire interaction chain from input to output, advocating for a context-aware approach that unifies API and model testing. As organizations prioritize API security, understanding and securing LLMs becomes crucial, as they encapsulate but do not replace existing risks, emphasizing the need for adaptive and comprehensive security practices.