AI Pulse · Under the Radar

A small open-source project called reverify is climbing quickly on GitHub, with 576 stars in its first three days and 209 stars added in the latest daily count. The idea is simple but important. Instead of asking an AI model to inspect a binary and trusting whatever explanation it produces, reverify pairs the model with deterministic binary-analysis tools. The model can propose what it thinks is happening. The tools then check that claim against the actual binary.

That matters because reverse engineering is a domain where confident-sounding errors are expensive. A model might identify a function, describe a protocol, or suggest a vulnerability, but none of that is useful if it cannot be verified. reverify uses MCP to connect the LLM to the analysis tools, creating a workflow where the AI helps direct the work while the underlying software provides the proof.

The broader lesson reaches well beyond binary analysis. AI is strongest when it does not act as the final authority. Give it a clear task, let it generate hypotheses or next steps, then require a system, database, calculation, or rule set to verify the result. That is the same proof-of-done approach we use in operational AI work. This is the kind of thing we build into an AI command centre, where an AI can coordinate work but completion is confirmed by real business systems, not a chat response.