{
  "node_id": "mitre-atlas-llm-data-leakage",
  "title": "MITRE ATLAS LLM Data Leakage Techniques (AML.T0057) - Exfiltration of Training Data, System Prompts, and Confidential Information via Language Model Outputs Under GDPR and AI Act Obligations",
  "domain": "AI Governance & Law",
  "version": "1.0.1",
  "last_updated": "2026-07-22",
  "bluf": "This node addresses MITRE ATLAS technique AML.T0057 (LLM Data Leakage), focusing on adversarial exfiltration of training data, system prompts, and confidential information through language model outputs. Compliance with EU AI Act (Article 15, Robustness) and GDPR (Article 5, Data Minimization) mandates organizations to implement defenses against such risks.",
  "paywall": {
    "status": "LOCKED",
    "unlock_cost_usd": "0.01",
    "skyfire_id": "41779894-ece2-4163-9761-b3b1b76e19b0"
  },
  "crosswalks": {
    "_available_keys": [
      "nist_framework",
      "iso_standard",
      "industry_mapping",
      "ai_overlay_2026"
    ],
    "_note": "Full crosswalk values included in vault response"
  },
  "dependencies": [
    "eu-ai-act-2024",
    "nist-ai-rmf-1-0",
    "iso-iec-42001-ai-management-system-2023"
  ],
  "primary_citations_count": 6
}