MITRE ATLAS 2026.09 / technique reference
AML.T0116
Autonomous Reconnaissance
MITRE source definition
Adversaries may use autonomous AI agents to conduct Reconnaissance activities. Given an objective, target, or partial lead, an agent may autonomously determine what information to obtain and how to investigate it. It may interpret observations, identify gaps in its understanding of the externally observable attack surface, and select subsequent reconnaissance actions without a human specifying each investigative step.
The agent may formulate investigative questions or hypotheses, select sources and approaches for addressing them, and update its understanding as new information is obtained. Findings may generate additional reconnaissance objectives or change the scope, depth, or direction of the investigation. This creates a recursive action-observation process in which reconnaissance results influence what the agent investigates next rather than merely supplying output from a predefined procedure.
The agent may correlate information across public sources and externally accessible services, prioritize promising systems, investigate suspected vulnerabilities, abandon unsuccessful approaches, or select alternative methods. It may also expand or substitute targets based on discovered names, infrastructure, or contextual relationships and independently reassess whether a system remains relevant or in scope. Incorrect assumptions may cause unrelated or unauthorized systems to be pursued, while successful scope recognition may cause the agent to stop or redirect its activity.
Autonomous AI agents can sustain reconnaissance across long-running operations, reason over multiple information sources, and test many alternative paths at a speed and volume difficult for human operators to maintain.
Source modified 2026-08-31. Reproduced from the pinned ATLAS release; inline technique links resolve to local reference pages.
Parent, sub-techniques and ATT&CK references
No explicit relationship in this pinned source.
Source-backed defensive context
MITRE mitigations
MITRE case studies
- AML.CS0068 Autonomous OpenAI Evaluation Agents Compromise Hugging Face Infrastructure · Incident
- AML.CS0069 GTG-1002 Claude Code Espionage Campaign · Incident
- AML.CS0070 Threat Actor Uses a DeepSeek-Powered Hermes Agent in Langflow and n8n Exploitation Attempts · Incident
- AML.CS0071 Multi-Agent Framework Compromises Taiwanese Government Systems · Incident
These are explicit source relationships, not independently reproduced incidents or validated detection coverage.
Simulation and telemetry boundary
This is a technique reference page, not a runnable simulation. No ATLAS-specific telemetry mapping, local attack execution or detector validation is asserted. MITRE maturity describes its source evidence, not a 1200km lab result.
For broader context—not technique-specific control mappings—see AI Security, AI Security Course, and detection-validation methodology.
Provenance and attribution
Immutable MITRE ATLAS source · Import provenance · Attribution and transformation notice · Apache License 2.0
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