{
  "node_id": "mitre-atlas-invert-ai-model",
  "title": "MITRE ATLAS Invert AI Model (AML.T0024.001) - Adversarial Invert AI Model threat to AI systems",
  "domain": "AI Governance & Law",
  "version": "1.0.1",
  "last_updated": "2026-07-22",
  "bluf": "This node addresses MITRE ATLAS technique AML.T0024.001 (Invert AI Model). AI models' training data could be reconstructed by exploiting the confidence scores that are available via an inference API. By querying the inference API strategically, adversaries can back out potentially private information embedded within the training data. This could lead to privacy violations if the attacker can reconstruct the data of sensitive features used in the algorithm. Defending against this technique is required under EU AI Act, NIST AI RMF, and ISO/IEC 42001 obligations; this node operationalises the documented ATLAS mitigations and cross-instrument controls into a deterministic verification workflow. Sub-technique of ATLAS AML.T0024. ATLAS-mapped mitigations: AML.M0002 Passive AI Output Obfuscation, AML.M0004 Restrict Number of AI Model Queries, AML.M0024 AI Telemetry Logging.",
  "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": [
    "nist-ai-rmf-1-0",
    "eu-ai-act-2024",
    "iso-iec-42001-ai-management-system-2023",
    "mitre-atlas-mitigation-passive-ai-output-obfuscation",
    "mitre-atlas-mitigation-restrict-number-of-ai-model-queries",
    "mitre-atlas-mitigation-ai-telemetry-logging"
  ],
  "primary_citations_count": 8
}