Framework
MITRE ATLAS (Adversarial Threat Landscape for AI Systems)
Una base de conocimiento reconocida mundialmente sobre tácticas, técnicas y casos de estudio de adversarios contra sistemas de IA, mantenida por MITRE Corporation.
Lectura práctica
Una base de conocimiento reconocida mundialmente sobre tácticas, técnicas y casos de estudio de adversarios contra sistemas de IA, mantenida por MITRE Corporation.
MITRE ATLAS applies the proven ATT&CK methodology to AI systems. It documents real-world attack patterns against machine learning models, pipelines, and applications through an open, community-contributed knowledge base of tactics, techniques, and procedures (TTPs).
Tactical categories
| Tactic | Description |
|---|---|
| Reconnaissance | Gather information about the target AI system, its training data, model architecture, APIs, and guardrails |
| Resource Development | Acquire or build infrastructure, datasets, or tools to support the attack |
| Initial Access | Gain an initial foothold into the AI system, its training pipeline, or its deployment environment |
| ML Model Access | Obtain access to the model itself — its weights, inference endpoints, or training process |
| Execution | Run adversary-controlled code or commands within the AI environment |
| Persistence | Maintain access across restarts, updates, or credential rotations |
| Defence Evasion | Avoid detection by security controls, logging, or monitoring |
| Discovery | Learn about the AI environment: model type, API structure, data schemas, connected systems |
| Collection | Gather information from the AI system: prompts, outputs, embeddings, or training data |
| ML Attack Staging | Prepare the model or its inputs for exploitation — crafting adversarial examples, poisoning data, or tampering with the supply chain |
| Exfiltration | Transfer data, model artefacts, or intellectual property out of the target environment |
| Impact | Manipulate, disrupt, or destroy AI system outputs, availability, or integrity |
ATLAS connection
MITRE ATLAS directly informs the ATLAS Risk Catalogue and Controls Catalogue. The Prompt Injection, Sensitive Data Disclosure, and Agentic Supply Chain Compromise entries are structured around attack paths documented in ATLAS case studies. The Input and Output Validation for AI Agents control is a direct translation of MITRE ATLAS mitigation AML.M0033. Together they provide the “what could happen” and “what to do about it” parts of the operational risk analysis.