Cisco says attackers used AI agents to break a malicious operation into small, routine-looking tasks. In one real campaign, the activity appeared to be authorized defense testing when viewed one step at a time, but the complete sequence revealed an effort to steal data.
According to Cisco, attackers used AI agents to break a malicious operation into small, routine-looking tasks. In one 2025 campaign targeting around 30 organizations, the activity was presented as new defense testing. Each individual request appeared harmless and consistent with that framing, but the complete sequence revealed an effort to access and steal data. A separate campaign targeting Mexican government institutions reportedly used the same underlying approach.
Because each step looked legitimate on its own, the overall goal stayed hidden until someone analyzed the full chain of actions together. This is the core mechanic of the attack: individually benign requests combine into something that only becomes recognizable as theft when viewed in sequence.
The attack succeeded because it exploited how most security controls work. Traditional defenses evaluate single actions to decide whether an intent is bad or benign, so a request that looks routine in isolation passes review. The pretext of authorized defense testing added further cover, since security teams and AI-agent operators are often primed to approve activity framed as sanctioned testing without demanding a clear, documented scope.
The result is a gap where legitimacy at the individual-step level obscures intent at the campaign level. Only when the requests are reconstructed in order does the pattern pointing toward data theft emerge.
Security operations, AI and automation teams, developers, data governance staff, and IT administrators all have a role here. Organizations should:
This technique reflects a broader shift where attackers rely on AI agents to split operations into innocuous-looking pieces, making sequence-level review and clear authorization processes essential defenses. See MITRE technique https://attack.mitre.org/techniques/T1656/ for related context on impersonation-based access.
Mirage safely runs attacks like this one against your own team, so you find out what happens before a real adversary does.
The campaign was divided into small, routine-looking tasks that an AI agent was told were part of new defense testing, so each individual request appeared legitimate and the true goal of stealing data only became clear when the requests were viewed together in sequence.
Traditional controls evaluate single actions to decide whether an intent is good or bad, but this attack only became apparent when the overall sequence of actions was viewed together.
Require documented scope and authorization for any security testing involving sensitive data, and train teams to escalate unusual chains of AI-agent tool use or data access rather than approving requests that look harmless in isolation.
Project Quarry is a tool Cisco open sourced to detect suspicious patterns across AI-agent conversations, tool use, and actions that may only become suspicious when viewed over time.
“This is part of new defense testing.” Would you approve it? Cisco says a 2025 Claude Code campaign targeting around 30 organizations split data theft into routine-looking tasks. Each step resembled an authorized test. Here’s the catch: connect the steps. Configuration check, file listing, sensitive records, then export. That’s not a test unless the approved scope says so. Before approving an AI-agent chain, compare the whole sequence with the documented test scope.
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