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DTEND:20260513T204500Z
UID:949dde9885d0320244696e55deed6119
DTSTAMP:1781197973
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DESCRIPTION:As enterprises adopt agentic AI, they face a new class of adversary: autonomous, goal-seeking agents that probe controls, data, and policies at machine speed. Building on ideas like “Digital Darwinism” and adversarial agents competing to optimize infrastructure, this session asks: what happens when attackers weaponize agents—and how do
we respond?
Key Questions: – How will adversarial agents change red-teaming, penetration testing, and threat modeling? – What defensive patterns are emerging for agent endpoint protection, data controls, and PII sensitivity mitigation? – Where do AI guardrails, content moderation, and design best practices fit in the security architecture versus at the application layer? – How do we monitor for agent-vs-agent “arms races” inside the enterprise and prevent unintended escalation?
Takeaways: – A taxonomy of adversarial agent threats relevant to Global 2000 environments. – Concrete examples of guardrail policies and monitoring approaches that actually reduce risk.

URL;VALUE=URI: https://onug.net/events/ai-security-defending-against-adversarial-ai-agents-from-digital-darwinism-to-guardrails/
SUMMARY:Defending Against Adversarial AI Agents – From Digital  Darwinism to Guardrails
DTSTART:20260513T204500Z
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