AVID-2023-V011

Vulnerability from avid – Published: 2023-03-31 – Updated: 2023-03-31 ATLAS Case Study
Summary
The Azure Red Team performed a red team exercise on a new Microsoft product designed for running AI workloads at the edge. This exercise was meant to use a automated system to continuously manipulate a target image to cause the ML model to produce misclassifications.
Risk domain
Security
SEP view
S0301: Information Leak, S0403: Adversarial Example
Lifecycle
L06: Deployment
Organisations
Affected artifacts
Artifact Type
New Microsoft AI Product System
References
URL Label
https://atlas.mitre.org/studies/AML.CS0011 Microsoft Edge AI Evasion

{
  "affects": {
    "artifacts": [
      {
        "name": "New Microsoft AI Product",
        "type": "System"
      }
    ],
    "deployer": [
      "New Microsoft AI Product"
    ],
    "developer": []
  },
  "credit": null,
  "data_type": "AVID",
  "data_version": "0.2",
  "description": {
    "lang": "eng",
    "value": "The Azure Red Team performed a red team exercise on a new Microsoft product designed for running AI workloads at the edge. This exercise was meant to use a automated system to continuously manipulate a target image to cause the ML model to produce misclassifications.\n"
  },
  "impact": {
    "avid": {
      "lifecycle_view": [
        "L06: Deployment"
      ],
      "risk_domain": [
        "Security"
      ],
      "sep_view": [
        "S0301: Information Leak",
        "S0403: Adversarial Example"
      ],
      "taxonomy_version": "0.2"
    }
  },
  "last_modified_date": "2023-03-31",
  "metadata": {
    "vuln_id": "AVID-2023-V011"
  },
  "problemtype": {
    "classof": "ATLAS Case Study",
    "description": {
      "lang": "eng",
      "value": "Microsoft Edge AI Evasion"
    },
    "type": "Advisory"
  },
  "published_date": "2023-03-31",
  "references": [
    {
      "label": "Microsoft Edge AI Evasion",
      "type": "source",
      "url": "https://atlas.mitre.org/studies/AML.CS0011"
    }
  ],
  "reports": null
}


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Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.

Sightings

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Nomenclature

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