Recording Agent and Model Activity, Tool Invocation, and Prompt Chains and Analyzing for Dual-Use Patterns

According to generative AI orchestration platform ZBrain, AI agent monitoring is “the practice of systematically tracking and analyzing an agent’s behavior, outputs, and impact to ensure it operates reliably, fairly, and efficiently.”⁠1 Effective monitoring enables the detection of misuse patterns or near misses and supports compliance with dual-use governance requirements.

This process involves addressing several challenges unique to AI implementation, including

  • ensuring resilience against AI failure modes, such as prompt variation
  • detecting subtle degradation over time due to model drift
  • linking agent output to business-specific key performance indicators, such as cost savings, resolution time, lead conversion, or customer satisfaction
  • evaluating the effectiveness of human-AI collaboration.

Commercial Off-the-Shelf Solutions and Simple Recommendations

Follow through with practices recommended by NIST:

  • Managing Misuse Risk for Dual-Use Foundation Models,⁠2
  • Secure Software Development Practices for Generative AI and Dual-Use Foundation Models.⁠3

See also

  • Langfuse⁠4
  • Arize⁠5
  • Datadog⁠6
  • New Relic⁠7
  • Dynatrace⁠8
  • Amazon Bedrock and Amazon CloudWatch integration⁠9
  • Microsoft Azure⁠10 and AI Foundry⁠11
  • IBM Observability solutions⁠12
  • Google Cloud Vertex AI Model Monitoring⁠13
  • Dialzara⁠14
  • Databricks Lakehouse Monitoring⁠15
  • Microsoft Defender Endpoint⁠16
  • WorkOS Radar⁠17
  • Microsoft Purview Insider Risk Management⁠18

How Does This Relate to the Rest of the Guide or Other Threats That the User Cares About?

  • Monitoring: A.CSM-1, CC.ISM-1, CC.NSI-1, CC.PSC-1, CC.CSM-1, COP.ISM-1, COP.CSM-1, D.CSM-1, D.DIVM-1, D.DTS-2, D.RDTP-1, E.CSM-1, E.ISCM-1, HT.TDM-1, IE.IRSO-2, IE.NSAP-1, IE.RMRL-2, IE.SML-1, IE.TD-1, II.AD-2, II.IRSO-1, II.RMRL-2, II.SML-1, MT.ISM-1, MT.TPMV-1

Other Sources of Information About This Topic

  • “Monitoring ZBrain AI Agents” (ZBrain)⁠19
  • “AI Monitoring” (InfluxData)⁠20
  • “ML Monitoring” (Acceldata)⁠21
  • “Demystifying AI Agents” (UptimeRobot)⁠22
  • “AI Model Monitoring” (Lyzr)⁠23
  • “The Ultimate Guide to Middleware Monitoring” (Avada Software)⁠24
  • “Can Large Language Models Democratize Access to Dual‑Use Biotechnology?” (arXiv)⁠25
  • “Dual Use Concerns of Generative AI and Large Language Models” (Journal of Responsible Innovation)⁠26
  • “The GPT Dilemma” (arXiv)⁠27
  • “Generative AI” (Artificial Intelligence Review)⁠28

Notes

  1. Takyar, “Monitoring ZBrain AI Agents.” Return to content ⤴
  2. U.S. AI Safety Institute, Managing Misuse Risk for Dual‑Use Foundation Models. Return to content ⤴
  3. Booth et al., Secure Software Development Practices for Generative AI and Dual‑Use Foundation Models. Return to content ⤴
  4. Langfuse, “Homepage.” Return to content ⤴
  5. Arize, “Homepage.” Return to content ⤴
  6. Datadog, “Homepage.” Return to content ⤴
  7. New Relic, “Homepage.” Return to content ⤴
  8. Beer, “Enhanced AI Model Observability with Dynatrace and Traceloop OpenLLMetry.” Return to content ⤴
  9. Eppel, Batalov, and Patel, “Monitoring Generative AI Applications Using Amazon Bedrock and Amazon CloudWatch Integration.” Return to content ⤴
  10. Microsoft, “Detect and Mitigate Potential Issues Using AIOps and Machine Learning in Azure Monitor.” Return to content ⤴
  11. Microsoft, “Monitor Your Generative AI Applications (Preview).” Return to content ⤴
  12. IBM, “IBM Observability.” Return to content ⤴
  13. Google Cloud, “Introduction to Vertex AI Model Monitoring.” Return to content ⤴
  14. Dialzara, “AI Model Monitoring vs Maintenance — Key Differences.” Return to content ⤴
  15. Databricks, “Lakehouse Monitoring”; SepidehEb, “MLOps Gym — Beginners Guide to Monitoring.” Return to content ⤴
  16. Microsoft, “What Is Endpoint Detection and Response (EDR)?.” Return to content ⤴
  17. WorkOS, “Radar.” Return to content ⤴
  18. Microsoft, “Learn About Insider Risk Management.” Return to content ⤴
  19. Takyar, “Monitoring ZBrain AI Agents.” Return to content ⤴
  20. InfluxData, “AI Monitoring.” Return to content ⤴
  21. Suma, “ML Monitoring — Challenges and Best Practices for Production Environments.” Return to content ⤴
  22. Goel, “Demystifying AI Agents — How They Work.” Return to content ⤴
  23. Lyzr, “AI Model Monitoring.” Return to content ⤴
  24. Avada Software, “The Ultimate Guide to Middleware Monitoring.” Return to content ⤴
  25. Soice et al., “Can Large Language Models Democratize Access to Dual‑Use Biotechnology?.” Return to content ⤴
  26. Grinbaum and Adomaitis, “Dual Use Concerns of Generative AI and Large Language Models.” Return to content ⤴
  27. Hickey, “The GPT Dilemma.” Return to content ⤴
  28. Ibrar et al., “Generative AI.” Return to content ⤴