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Release · v2026.06-rc4

FINOS-CCC/CCC.Vector.TH Threat Catalog

FINOS-CCC/CCC.Vector.TH

Threats for Managed Vector Store technologies, as defined by the FINOS Common Cloud Controls project.

Published by FINOS Common Cloud Controls

Install

OCI v1.1
$grcli unpack --repository finos-ccc/ccc.vector.th --tag v2026.06-rc4
Coordinate
oci.grc.store/finos-ccc/ccc.vector.th:v2026.06-rc4
Manifest digest
sha256:f272c589af4059796f1da024fd3962030c5f9cec298b88d3461eb18a0080fcb5

Provenance

1 layer
Digest Media type Size
0820eeacbd1a… application/vnd.gemara.artifact.v1+yaml 5.6 KiB
Bundle config blob 
{
  "bundle-version": "1.0",
  "gemara-version": "v1.2.0",
  "metadata": {
    "provenance": {
      "buildDefinition": {
        "buildType": "https://grc.store/grcli/buildtype/v0",
        "externalParameters": {
          "artifact": {
            "id": "CCC.Vector.TH",
            "type": "ThreatCatalog"
          },
          "target": {
            "registry": "oci.grc.store",
            "repository": "finos-ccc/ccc.vector.th",
            "tag": "v2026.06-rc4"
          }
        },
        "internalParameters": {
          "CI": "true",
          "GITHUB_ACTIONS": "true",
          "GITHUB_ACTOR": "eddie-knight",
          "GITHUB_REF": "refs/heads/main",
          "GITHUB_REPOSITORY": "eddie-knight/common-cloud-controls",
          "GITHUB_RUN_ATTEMPT": "1",
          "GITHUB_RUN_ID": "26770748733",
          "GITHUB_SHA": "2b6dab4c1307a0ac67d90c99829f6c1825154c84",
          "GITHUB_WORKFLOW": "Batch Release All Catalogs",
          "RUNNER_OS": "Linux"
        },
        "resolvedDependencies": [
          {
            "name": "artifacts/database/vector/threats.yaml",
            "uri": "file://artifacts/database/vector/threats.yaml",
            "digest": {
              "sha256": "0820eeacbd1a9be25d8045099d8a86ccafc6f31a6ae922dc586fe0699eb8afcf"
            }
          },
          {
            "name": "source",
            "uri": "git+https://github.com/eddie-knight/common-cloud-controls@2b6dab4c1307a0ac67d90c99829f6c1825154c84",
            "digest": {
              "gitCommit": "2b6dab4c1307a0ac67d90c99829f6c1825154c84"
            }
          }
        ]
      },
      "runDetails": {
        "builder": {
          "id": "https://github.com/eddie-knight/common-cloud-controls/actions/runs/26770748733",
          "version": {
            "go": "go1.25.0",
            "go-arch": "amd64",
            "go-os": "linux",
            "grcli": "v0.2.2"
          }
        },
        "metadata": {
          "invocationId": "26770748733-1",
          "startedOn": "2026-06-01T17:28:40.209636631Z",
          "finishedOn": "2026-06-01T17:28:40.424346235Z"
        },
        "byproducts": [
          {
            "name": "threats.yaml",
            "digest": {
              "sha256": "0820eeacbd1a9be25d8045099d8a86ccafc6f31a6ae922dc586fe0699eb8afcf"
            }
          }
        ]
      }
    }
  },
  "artifacts": [
    {
      "name": "threats.yaml",
      "type": "ThreatCatalog",
      "id": "CCC.Vector.TH",
      "role": "artifact"
    }
  ]
}

CCC Managed Vector Store Threats

Threats for Managed Vector Store technologies, as defined by the FINOS Common Cloud Controls project.

ID
CCC.Vector.TH
Version
v2026.06-rc4
Gemara version
v1.2.0
Author
FINOS Common Cloud Controls

Data Resilience

The Data Resilience group covers entries related to ensuring data availability, integrity, and sovereignty across its lifecycle. This includes replication, backup, recovery, region restrictions, and protection against data loss or corruption.

  1. CCC.Vector.TH01 Embedding Extraction and Model Inversion

    Attackers may infer or reconstruct original data by probing vector similarity APIs, especially with unrestricted access. This enables model inversion attacks, membership inference, and unauthorized data leakage from stored embeddings.

    Capabilities
    • CCC.Vector.Capabilities
      • CCC.Vector.CP01
      • CCC.Vector.CP03
      • CCC.Vector.CP06

  2. CCC.Vector.TH03 Cross-modal or Metadata Leakage

    Attackers may infer sensitive information through metadata filters or by correlating embeddings across modalities (e.g., voice and face), bypassing surface-level access controls.

    Capabilities
    • CCC.Vector.Capabilities
      • CCC.Vector.CP04
      • CCC.Vector.CP10

  3. CCC.Vector.TH04 Index Corruption or Downgrade

    Attackers with unauthorized access or excessive permissions may tamper with or roll back index versions, potentially restoring poisoned data or breaking downstream integrations.

    Capabilities
    • CCC.Vector.Capabilities
      • CCC.Vector.CP07
      • CCC.Vector.CP11

  4. CCC.Vector.TH06 Search Result Manipulation via ANN Bias

    Approximate nearest neighbor (ANN) algorithms may yield non-deterministic or biased results. Adversaries may exploit these differences to evade detection or bias AI responses.

    Capabilities
    • CCC.Vector.Capabilities
      • CCC.Vector.CP12

Ingestion

The Ingestion group covers entries related to how a service receives or retrieves data, inputs, or commands for processing. This includes both active (pull-based) and passive (push-based) ingestion patterns.

  1. CCC.Vector.TH02 Embedding and Index Poisoning

    Adversaries may insert malicious or adversarial vectors into the index through ingestion endpoints, polluting the dataset and degrading search quality, or subtly steering results toward specific outcomes.

    Capabilities
    • CCC.Vector.Capabilities
      • CCC.Vector.CP02
      • CCC.Vector.CP05
      • CCC.Vector.CP07

  2. CCC.Vector.TH05 Embedding Format or Dimension Attacks

    Poor validation of embedding formats or dimensions can cause service crashes or logic errors. This can result in denial of service or incorrect similarity results.

    Capabilities
    • CCC.Vector.Capabilities
      • CCC.Vector.CP08
      • CCC.Vector.CP09