A publication model for AI agent findings that explains observed behavior, tool boundaries, and mitigations without sharing jailbreak recipes.
Safe technical detail
The brief can state that a retrieved document, user prompt, or tool response influenced an agent outside its intended policy. The exact prompt chain, tool arguments, and customer data remain in private evidence.
Add source trust labels, tool-use policy checks, confirmation gates for sensitive actions, behavior logging, and regression evaluations for the affected control.
Pentoma AI Red Teaming reports observed behavior, expected control, and mitigation path while keeping reusable prompt attacks out of public pages.
AI agent findings need enough context to be useful, but prompt transcripts can become reusable attack material.
Recommended fixes should focus on policy checks, source trust labels, tool confirmation, logging, and evaluation coverage rather than publishing bypass prompts.
Publication timeline
Public research should show enough process to be credible without exposing raw scan output, prompt traces, proprietary code, or private customer context.
The public record describes the failed boundary rather than the exact prompt chain.
Full prompts, poisoned documents, tool arguments, and customer records stay private.
Claims are reviewed to avoid treating probabilistic model behavior as deterministic exploitability.
References
Links here point only to resources that are safe to share publicly.