agent-safety-review

To assess autonomous agent safety risks, you need a structured review process evaluating private data, untrusted inputs, and outbound actions. This identifies lethal-trifecta risks and provides specific mitigation strategies based on your architecture documentation and code.

The lethal-trifecta risk in autonomous agent architecture involves the simultaneous exposure to private data, untrusted inputs, and outbound actions. Assessing these fields individually determines autonomy control coherence and highlights potential safety vulnerabilities in high-risk applications.

To conduct an architectural risk assessment for autonomous agents, run the automated review command and follow the prompted instructions. The process requires access to your agent architecture documentation and code to evaluate safety risks and generate mitigation recommendations.

Yes, you need architecture documentation and code to perform an agent safety review. The evaluation analyzes field-by-field risks involving private data, untrusted inputs, and outbound actions, requiring direct access to your implementation details to generate accurate mitigation strategies.

The best ways to mitigate risks in autonomous agents handling untrusted input involve field-by-field evaluations of private data and outbound actions. The safety review classifies these lethal-trifecta risks and offers specific architectural recommendations to control autonomy coherence.

Yes, you can automate architectural risk assessments for high-risk autonomous agent applications. By evaluating fields like private data, untrusted inputs, and outbound actions, the automated review identifies lethal-trifecta risks and generates mitigation strategies without manual analysis.