Vectors submitted with unexpected dimensionality, numeric type, or degenerate values such as NaN, infinity, zero magnitude under cosine similarity, or extreme magnitude may be accepted when validation is incomplete. Indexing or query components fail, or similarity scores are distorted for every query that encounters the vector. Availability of the service and integrity of results are impacted.
Malformed Vectors Cause Failures or Incorrect Results
CCC.Vector.TH05
Related Capabilities
| ID | Title | Description |
|---|---|---|
| CCC.Vector.CP08 | Embedding Format Compatibility | The service can store vector values in standard numeric formats, such as 32-bit floating point or quantized byte and binary representations, so that embeddings produced by any external embedding model can be loaded without transformation. |
| CCC.Vector.CP09 | Vector Dimension Management | The service always enforces a fixed vector dimensionality per index or field, declared when the index is created, and rejects vectors that do not match it. |
Related Controls
| ID | Title | Description |
|---|---|---|
| CCC.Vector.CN01 | Validate Embeddings Before Indexing | Ensure all incoming embeddings are structurally and numerically validated before indexing to prevent poisoning or corruption. |