4 papers
Manifold of Failure: Behavioral Attraction Basins in Language Models
Sarthak Munshi, Manish Bhatt, Vineeth Sai Narajala +4
While prior work has focused on projecting adversarial examples back onto the manifold of natural data to restore safety, we argue that a comprehensive understanding of AI safety r…
The Defense Trilemma: Why Prompt Injection Defense Wrappers Fail?
Manish Bhatt, Sarthak Munshi, Vineeth Sai Narajala +6
We prove that no continuous, utility-preserving wrapper defense-a function that preprocesses inputs before the model sees them-can make all outputs strictly safe for a…
ACSE-Eval: Can LLMs threat model real-world cloud infrastructure?
Sarthak Munshi, Swapnil Pathak, Sonam Ghatode +3
While Large Language Models have shown promise in cybersecurity applications, their effectiveness in identifying security threats within cloud deployments remains unexplored. This…
Representation Engineering for Large-Language Models: Survey and Research Challenges
Lukasz Bartoszcze, Sarthak Munshi, Bryan Sukidi +6
Large-language models are capable of completing a variety of tasks, but remain unpredictable and intractable. Representation engineering seeks to resolve this problem through a new…