OpenAPPA intercepts agent tool calls and checks their data flows against declarative policies, blocking exfiltration from prompt injection or hallucination.
Yes, OpenAPPA is open source under the MIT license.
OpenAPPA is free to use.
Yes, OpenAPPA can be self-hosted (the source is available under the MIT license).
OpenAPPA is a deterministic guardrail layer that intercepts agent tool calls and verifies data flows against declarative policies, blocking data exfiltration from prompt injection or hallucination without breaking agent function. Open source: yes (MIT); self-hostable; pricing free. It runs in-process, has 26 stars, and is active (668 commits).
OpenAPPA sits between an agent and its tools and reasons about data movement rather than message text. When the agent tries to call a tool, OpenAPPA checks the data flow that call would create against declarative policies — what data is leaving, and to where — and deterministically blocks flows that would exfiltrate sensitive data, whether the trigger was a prompt injection or a plain hallucination. The stated design goal is to do this without breaking the agent's legitimate function: block the leak, keep the task working. It runs in-process alongside the agent (no separate service). Open source: yes (MIT); self-hostable; pricing free.
A GTM agent with CRM, inbox, and enrichment access holds exactly the data an exfiltration attack wants — and the dangerous failure is not a wrong answer but a correct-looking tool call that ships that data somewhere it should not go. OpenAPPA targets that class deterministically: it gates on the data flow the call produces, not on spotting the injecting text, and aims to keep legitimate work flowing. Open source: yes (MIT); self-hostable; pricing free. The honest read: the vendor's headline (0% attacks, 89% task completion, beating Claude auto-mode and FIDES) is its own benchmark and the project is young at 26 stars — the mechanism is well-aimed, but pilot it on your own sensitive tools and write real policies before trusting it in front of live data.