CVE-2026-47735 (GCVE-0-2026-47735)
Vulnerability from cvelistv5 – Published: 2026-08-21 22:42 – Updated: 2026-08-25 13:35
VLAI
EPSS
VEX
Title
Arc has an authenticated arbitrary local-file read via DuckDB I/O functions that bypasses RBAC table-level checks
Summary
Arc is an open, SQL-native time-series database for telemetry. Prior to version 26.06.1, Arc's user-SQL validator (`internal/api/query.go:ValidateSQLRequest`) blocked only `read_parquet(` and `arc_partition_agg(` via regex denylist. The broader DuckDB I/O function family — `read_csv_auto`, `read_csv`, `read_json`, `read_json_auto`, `read_text`, `read_blob`, `glob`, `parquet_metadata`, `parquet_schema`, `read_xlsx`, etc. — was not blocked. RBAC table-reference extraction inspected only `FROM`/`JOIN` clauses, so scalar table functions in the `SELECT` list slipped past both layers. This is fixed in 2026.06.1 via a structural sandbox at the DuckDB layer. After lockdown, DuckDB refuses to open any file outside the allowlist and refuses further `INSTALL`/`LOAD`. Already-loaded extensions remain callable. Some workarounds are available. Restrict API access to known-trusted networks via firewall rules or, as a temporary mitigation, add `read_csv*`/`read_json*`/`glob` etc. to `dangerousSQLPattern` in `internal/api/query.go`.
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-08-25 13:35 UTC
CWE
Assigner
References
4 references
| URL | Tags |
|---|---|
| https://github.com/Basekick-Labs/arc/security/adv… | x_refsource_CONFIRM |
| https://github.com/Basekick-Labs/arc/pull/442 | x_refsource_MISC |
| https://github.com/Basekick-Labs/arc/commit/91bdc… | x_refsource_MISC |
| https://github.com/Basekick-Labs/arc/releases/tag… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Basekick-Labs | arc |
Affected:
< 2026.06.1
|
guessed |
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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