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The Problem with AI Agents

AI Agents are rapidly moving from experimental prototypes into production systems capable of making decisions autonomously. Unlike traditional automation, their behaviour depends on the instructions and context they receive. As Multi-Agent Systems (MAS) become more common, a single user request may pass through multiple autonomous Agents and external applications before reaching its final destination.

This introduces a new set of security concerns:

  • Who created the initial intent of the workflow?
  • Can every step in the workflow be traced back to the original requester?
  • Was an Agent authorized to perform an action according to its policy?
  • Has an Agent's policy been modified since it was deployed?
  • How much an Agent has drifted from the initial intent?

AgentDNA was built to ensure that every autonomous decision can be identified, verified, authorized and audited.