Unique Challenges in Securing Gen AI Applications

Securing Generative AI applications presents unique challenges compared to traditional web or API testing. The non-deterministic nature of AI means that penetration testing requires multiple attempts across different message segments, as context length can vary significantly. Additionally, continuous updates from LLM vendors complicate the process since major version changes are often unannounced, necessitating ongoing testing instead of the periodic assessments common in traditional applications. The embedded logic within AI models presents another challenge, as sensitive business data is integrated within the model itself, making it difficult to implement role-based access controls or isolate confidential information effectively.