Efficient and Sound Probabilistic Verification for AI Agents
Securing AI agents that operate in complex digital environments has become a critical need, and runtime monitoring approaches that formulate and enforce policies expressed in a formal language like Datalog offer a promising solution. However, existing approaches are restricted to deterministic policies. In many practical applications of AI agents, there is a need to enforce security policies in the face of ambiguity, leading to probabilistic predicates or state transitions (for example, a declassifier or Personally Identifiable Information (PII) detector that has some failure probability on each invocation). Furthermore, in many such applications, one cannot easily make the independence a...
| Authors | Alaia Solko-Breslin, Pramod Kaushik Mudrakarta, Mihai Christodorescu et al. |
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| Primary category | cs.CR |
| Published | 18 June 2026 |
| Last updated at source | 18 June 2026 |
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