Sign in

v43

latestOpenAPI 3.1.0raw.githubusercontent.com2026-07-0953227392.1 KB
Model Scanner SaaS
Model Scanner Hybrid

Get scan results

get/scan/v3/results/{scan_id}

Response

Successful response

has_genealogyboolean

if there is model geneaology info available

versionstring required

scanner version

$schema_versionstring

version of the scan report schema format

scan_idstring required

unique identifier for the scan

start_timestring date-time required

time the scan started

end_timestring date-time

time the scan ended

status'pending' | 'running' | 'done' | 'failed' | 'canceled' required

status of the scan

file_countinteger required

number of files scanned; use .summary.file_count instead

files_with_detections_countinteger required

number of files with detections found; use .summary.files_with_detections_count instead

detection_countinteger required

number of detections found; use .summary.detection_count instead

detection_categoriesstring[]

list of detection categories found; use .summary.detection_categories instead

severity'critical' | 'high' | 'medium' | 'low' | 'unknown' | 'safe'

The highest severity of any detections on the scan, including "safe". Use .summary.highest_severity instead.

Example response

{
  "inventory": {
    "model_name": "keras-tf-2025-05-27",
    "model_version": "1.0.0",
    "model_source": "adhoc",
    "requested_scan_location": "/files-to-scan",
    "file_location": "https://huggingface.co/meta-llama/Llama-3.1-8B",
    "provider_details": {
      "provider": "AWS_BEDROCK",
      "provider_model_id": "anthropic.claude-3-5-sonnet-20241022-v2:0"
    },
    "asset_id": "a1b2c3d4-5e6f-4a7b-8c9d-0e1f2a3b4c5d",
    "origin": "Hugging Face",
    "model_id": "00000000-0000-0000-0000-000000000000",
    "model_version_id": "00000000-0000-0000-0000-000000000000"
  },
  "intelligence": {
    "geographic_footprint": [
      "US",
      "GB"
    ],
    "country_of_origin": "US",
    "contributor_trust_level": "high",
    "licenses": [
      {
        "name": "Apache-2.0",
        "sha256": "abc123..."
      }
    ],
    "usage_policies": [
      {
        "name": "Commercial Use Allowed",
        "sha256": "def456..."
      }
    ]
  },
  "file_results": [
    {
      "start_time": "2024-10-16T23:38:32.278Z",
      "end_time": "2024-10-16T23:38:32.354Z",
      "details": {
        "md5": "ce114e4501d2f4e2dcea3e17b546f339",
        "sha256": "a54d88e06612d820bc3be72877c74f257b561b19",
        "tlsh": "T1C50757F93C74D00C05B70C0793A1D5A9DF3F6D3A2F7AD940F3BFBF07B3BDF5A1D293",
        "file_size": "9 GB",
        "file_size_bytes": 9663676416,
        "file_type": "safetensors",
        "file_type_details": {
          "keras_version": "2.11.0,2.11.0"
        }
      },
      "seen": "2024-10-22T17:59:12.431Z",
      "detections": [
        {
          "detection_id": "00000000-0000-0000-0000-000000000000",
          "rule_id": "PICKLE_0055_202408",
          "category": "Arbitrary Code Execution",
          "description": "Found lambda embedded in keras model allowing custom layers that support  arbitrary expression execution",
          "likelihood": "medium",
          "impact": "critical",
          "mitre_atlas": [
            {
              "technique": "AML.T0003.45",
              "tactic": "AML.TA0001"
            }
          ]
        }
      ],
      "advisories": [
        {
          "advisory_id": "00000000-0000-0000-0000-000000000000",
          "rule_id": "SAFETENSORS_0001_202512",
          "category": "TokenBreak",
          "description": "Models using the BPE and WordPiece tokenization strategies are vulnerable to TokenBreak"
        }
      ],
      "file_error": [
        "File not found"
      ]
    }
  ]
}