{"items":[{"id":"NVI-00012125","kind":"vulnerability","title":"PraisonAI: PGVector and Cassandra knowledge stores interpolate vector dimensions into DDL","revision":3,"unknowns":["Customer inventory, deployment, reachability and exploitation have not been inspected."],"lifecycle":"active","identifiers":["GHSA-wf65-4jjx-q444","CVE-2026-60090"],"plain_summary":"GitHub lists this reviewed advisory for praisonai. Published version ranges and source prerequisites are shown below; this is not an inspection of a visitor’s application.","review_status":"source_listed","control_topics":[],"public_actions":[{"summary":"Identify the exact component and deployed version, examine the linked publisher’s conditions, and retain evidence of any mitigation.","source_ids":["sr-0476e7868ce6445945b3b4dc3818851f"],"action_type":"investigate","limitations":"Confirm current vendor support, compatibility and deployment evidence. This report has not tested a fix in your system.","current_supported_target":null}],"schema_version":"1.1.0","source_metrics":[{"kind":"EPSS","as_of":"2026-11-02T12:00:30.000Z","value":"0.702%","meaning":"FIRST EPSS model v2026.06.15; exploitation probability over 30 days, percentile 0.5326. Missing scores are unknown.","source_id":"sr-0476e7868ce6445945b3b4dc3818851f"}],"why_it_matters":"Published affected context helps an owner decide what evidence to gather. This report has not examined your application.","related_sources":[{"id":"sr-aec2ba9fcb1d9cdbca3cd5debdcc97a3","url":"https://github.com/advisories/GHSA-wf65-4jjx-q444","basis":"vendor_advisory","notes":"GitHub Advisory Database; CC-BY-4.0. Each advisory links its original attribution. Null normalizes fields.","title":"GHSA-wf65-4jjx-q444","publisher":"GitHub Advisory Database","observed_at":"2026-11-01T00:58:38.867Z"},{"id":"sr-0476e7868ce6445945b3b4dc3818851f","url":"https://www.first.org/epss/data.html","basis":"official_catalog","notes":"FIRST EPSS; probability of exploitation in the next 30 days, not local compromise. Dataset date/model retained; FIRST services terms apply.","title":"CVE-2026-60090","publisher":"FIRST EPSS","observed_at":"2026-11-02T20:15:58.859Z"}],"affected_context":[{"certainty":"source_listed","source_ids":["sr-aec2ba9fcb1d9cdbca3cd5debdcc97a3"],"technology":"praisonai","known_exclusions":[],"conditions_summary":"# PGVector and Cassandra knowledge stores interpolate vector dimensions into DDL\n\n## Summary\n\nThe PGVector and Cassandra knowledge-store backends validate SQL/CQL identifiers such as schema, keyspace, and collection names, but still insert the caller-controlled `dimension` argument directly into `CREATE TABLE` vector column declarations. A caller that can influence collection creation dimensions can append SQL/CQL tokens to the generated DDL executed by the database driver.\n\n## Technical Details\n\nThe affected boundary is the vector-store collection creation API. The shared `KnowledgeStore.create_collection()` contract declares `dimension: int`, but Python type hints are not enforced at runtime. Backends that interpolate that value into DDL must validate the runtime value before constructing SQL/CQL.\n\n`src/praisonai/praisonai/persistence/knowledge/pgvector.py` already treats DDL identifier interpolation as security-sensitive: `__init__()` calls `validate_identifier(schema, name=\"schema\")`, and `_table_name()` calls `validate_identifier(collection, name=\"collection name\")` before returning `f\"{self.schema}.praison_vec_{collection}\"`. However, `PGVectorKnowledgeStore.create_collection","public_affected_ranges":["<= 4.6.77"]}],"null_published_at":"2026-11-03T17:49:15.000Z","source_updated_at":"2026-10-08T17:17:02.000Z","source_disclosed_at":"2026-10-08T17:17:01.000Z","is_synthetic_fixture":false,"null_last_reviewed_at":null,"public_change_summary":"Dated EPSS estimate updated; this is not a new disclosure or proof of exploitation.","null_first_observed_at":"2026-11-01T00:58:38.867Z"},{"id":"NVI-00012125","kind":"vulnerability","title":"PraisonAI: PGVector and Cassandra knowledge stores interpolate vector dimensions into DDL","revision":2,"unknowns":["Customer inventory, deployment, reachability and exploitation have not been inspected."],"lifecycle":"active","identifiers":["GHSA-wf65-4jjx-q444","CVE-2026-60090"],"plain_summary":"GitHub lists this reviewed advisory for praisonai. Published version ranges and source prerequisites are shown below; this is not an inspection of a visitor’s application.","review_status":"source_listed","control_topics":[],"public_actions":[{"summary":"Identify the exact component and deployed version, examine the linked publisher’s conditions, and retain evidence of any mitigation.","source_ids":["sr-1d67acfd58308b2701d0713fda462046"],"action_type":"investigate","limitations":"Confirm current vendor support, compatibility and deployment evidence. This report has not tested a fix in your system.","current_supported_target":null}],"schema_version":"1.1.0","source_metrics":[{"kind":"EPSS","as_of":"2026-10-31T12:00:27.000Z","value":"0.702%","meaning":"FIRST EPSS model v2026.06.15; exploitation probability over 30 days, percentile 0.53273. Missing scores are unknown.","source_id":"sr-1d67acfd58308b2701d0713fda462046"}],"why_it_matters":"Published affected context helps an owner decide what evidence to gather. This report has not examined your application.","related_sources":[{"id":"sr-aec2ba9fcb1d9cdbca3cd5debdcc97a3","url":"https://github.com/advisories/GHSA-wf65-4jjx-q444","basis":"vendor_advisory","notes":"GitHub Advisory Database; CC-BY-4.0. Each advisory links its original attribution. Null normalizes fields.","title":"GHSA-wf65-4jjx-q444","publisher":"GitHub Advisory Database","observed_at":"2026-11-01T00:58:38.867Z"},{"id":"sr-1d67acfd58308b2701d0713fda462046","url":"https://www.first.org/epss/data.html","basis":"official_catalog","notes":"FIRST EPSS; probability of exploitation in the next 30 days, not local compromise. Dataset date/model retained; FIRST services terms apply.","title":"CVE-2026-60090","publisher":"FIRST EPSS","observed_at":"2026-11-01T01:39:43.083Z"}],"affected_context":[{"certainty":"source_listed","source_ids":["sr-aec2ba9fcb1d9cdbca3cd5debdcc97a3"],"technology":"praisonai","known_exclusions":[],"conditions_summary":"# PGVector and Cassandra knowledge stores interpolate vector dimensions into DDL\n\n## Summary\n\nThe PGVector and Cassandra knowledge-store backends validate SQL/CQL identifiers such as schema, keyspace, and collection names, but still insert the caller-controlled `dimension` argument directly into `CREATE TABLE` vector column declarations. A caller that can influence collection creation dimensions can append SQL/CQL tokens to the generated DDL executed by the database driver.\n\n## Technical Details\n\nThe affected boundary is the vector-store collection creation API. The shared `KnowledgeStore.create_collection()` contract declares `dimension: int`, but Python type hints are not enforced at runtime. Backends that interpolate that value into DDL must validate the runtime value before constructing SQL/CQL.\n\n`src/praisonai/praisonai/persistence/knowledge/pgvector.py` already treats DDL identifier interpolation as security-sensitive: `__init__()` calls `validate_identifier(schema, name=\"schema\")`, and `_table_name()` calls `validate_identifier(collection, name=\"collection name\")` before returning `f\"{self.schema}.praison_vec_{collection}\"`. However, `PGVectorKnowledgeStore.create_collection","public_affected_ranges":["<= 4.6.77"]}],"null_published_at":"2026-11-01T14:34:14.102Z","source_updated_at":"2026-10-08T17:17:02.000Z","source_disclosed_at":"2026-10-08T17:17:01.000Z","is_synthetic_fixture":false,"null_last_reviewed_at":null,"public_change_summary":"Dated EPSS estimate updated; this is not a new disclosure or proof of exploitation.","null_first_observed_at":"2026-11-01T00:58:38.867Z"},{"id":"NVI-00012125","kind":"vulnerability","title":"PraisonAI: PGVector and Cassandra knowledge stores interpolate vector dimensions into DDL","revision":1,"unknowns":["Customer inventory, deployment, reachability and exploitation have not been inspected."],"lifecycle":"active","identifiers":["GHSA-wf65-4jjx-q444","CVE-2026-60090"],"plain_summary":"GitHub lists this reviewed advisory for praisonai. Published version ranges and source prerequisites are shown below; this is not an inspection of a visitor’s application.","review_status":"source_listed","control_topics":[],"public_actions":[{"summary":"Identify the exact component and deployed version, examine the linked publisher’s conditions, and retain evidence of any mitigation.","source_ids":["sr-aec2ba9fcb1d9cdbca3cd5debdcc97a3"],"action_type":"investigate","limitations":"Confirm current vendor support, compatibility and deployment evidence. This report has not tested a fix in your system.","current_supported_target":null}],"schema_version":"1.1.0","source_metrics":[],"why_it_matters":"Published affected context helps an owner decide what evidence to gather. This report has not examined your application.","related_sources":[{"id":"sr-aec2ba9fcb1d9cdbca3cd5debdcc97a3","url":"https://github.com/advisories/GHSA-wf65-4jjx-q444","basis":"vendor_advisory","notes":"GitHub Advisory Database; CC-BY-4.0. Each advisory links its original attribution. Null normalizes fields.","title":"GHSA-wf65-4jjx-q444","publisher":"GitHub Advisory Database","observed_at":"2026-11-01T00:58:38.867Z"}],"affected_context":[{"certainty":"source_listed","source_ids":["sr-aec2ba9fcb1d9cdbca3cd5debdcc97a3"],"technology":"praisonai","known_exclusions":[],"conditions_summary":"# PGVector and Cassandra knowledge stores interpolate vector dimensions into DDL\n\n## Summary\n\nThe PGVector and Cassandra knowledge-store backends validate SQL/CQL identifiers such as schema, keyspace, and collection names, but still insert the caller-controlled `dimension` argument directly into `CREATE TABLE` vector column declarations. A caller that can influence collection creation dimensions can append SQL/CQL tokens to the generated DDL executed by the database driver.\n\n## Technical Details\n\nThe affected boundary is the vector-store collection creation API. The shared `KnowledgeStore.create_collection()` contract declares `dimension: int`, but Python type hints are not enforced at runtime. Backends that interpolate that value into DDL must validate the runtime value before constructing SQL/CQL.\n\n`src/praisonai/praisonai/persistence/knowledge/pgvector.py` already treats DDL identifier interpolation as security-sensitive: `__init__()` calls `validate_identifier(schema, name=\"schema\")`, and `_table_name()` calls `validate_identifier(collection, name=\"collection name\")` before returning `f\"{self.schema}.praison_vec_{collection}\"`. However, `PGVectorKnowledgeStore.create_collection","public_affected_ranges":["<= 4.6.77"]}],"null_published_at":"2026-11-01T01:03:56.632Z","source_updated_at":"2026-10-08T17:17:02.000Z","source_disclosed_at":"2026-10-08T17:17:01.000Z","is_synthetic_fixture":false,"null_last_reviewed_at":null,"public_change_summary":"First indexed by Null; source disclosure date is shown separately.","null_first_observed_at":"2026-11-01T00:58:38.867Z"}],"next_cursor":null,"snapshot_revision":"42594"}