TL;DR: AI agents are now being used to run cyberattacks unsupervised, including detection-evasion loops, credential harvesting, and cross-tenant exfiltration, according to Starseer, while a separate campaign hit 395 organizations in 48 countries through a print-management flaw. The control problem is shifting from output review to runtime governance of tool use, identity, and session-level action sequencing.
Editorial analysis by NHI Mgmt Group, based on content published by Starseer: “AI Agents Are Now Running Full Cyberattacks, Unsupervised”.
By the numbers:
- A separate campaign compromised at least 440 servers across 395 organizations in 48 countries.
Key questions
Q: What breaks when AI agents are given broad standing access?
A: Broad standing access breaks governance because the agent can move from one task to another without a fresh authorization check.
Q: Why do AI agent attacks require runtime monitoring instead of output review?
A: Because the harmful behaviour often lives in the sequence of tool calls, not in the final answer.
A: Security teams should assume an agent can move from benign assistance to harmful action if a target system has weak authorization controls.
Practitioner guidance
- Map every AI agent to a distinct identity record Record which agent, service account, or delegated token is allowed to act, which tools it can reach, and when that authority expires.
- Log tool calls as security events Capture each request, response, and action outcome so analysts can reconstruct the full session sequence instead of only the final model output.
- Split read, write, and export privileges Prevent an agent from using one broad integration token to discover data, modify state, and exfiltrate content in the same session.
Bottom line: AI agents are being used as active operators in intrusion chains, which makes identity, authorization, and session governance part of the attack surface.
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