The proliferation of AI assistants with tool-use capabilities introduces a new class of security challenges: these systems must enforce authorization policies while remaining connected to untrusted messaging channels and powerful execution backends. We present a comprehensive formal verification effort targeting OpenClaw, an open-source personal AI assistant gateway that connects frontier language models to messaging platforms and device controls. Using TLA+ and the TLC model checker, we specify and verify 91 security-critical properties spanning gateway authentication, direct message pairing protocols, session isolation, tool authorization hierarchies, and remote execution approval workflows. Our methodology employs a green/red testing paradigm where each security property is accompanied by an intentionally-buggy variant designed to produce counterexample traces, ensuring non-vacuity of specifications. We integrate model checking into continuous integration pipelines, treating formal specifications as executable security regression tests. Our work demonstrates that lightweight formal methods can provide meaningful security assurance for AI infrastructure systems without requiring full program verification.
Vignesh Natarajan (Mon,) studied this question.