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-rc3
- 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.
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
- CCC.Vector.Capabilities
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
- CCC.Vector.Capabilities
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
- CCC.Vector.Capabilities
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
- CCC.Vector.Capabilities
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.
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
- CCC.Vector.Capabilities
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
- CCC.Vector.Capabilities