CyberRota Analysis
AI-GeneratedArc's SQL-native time-series database is vulnerable to unauthorized access through its user-SQL validator, which inadequately restricts certain DuckDB I/O functions, allowing potential exploitation of scalar table functions in `SELECT` clauses. This could lead to unauthorized data access or manipulation, posing a significant risk to data integrity and confidentiality. Organizations using Arc prior to version 26.06.1 should prioritize patching to mitigate this high-severity vulnerability.
Public Exploit Signal
A public exploit, PoC, GitHub repository or Metasploit reference was detected for this CVE.
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Original NVD Description
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`.