SQL Injection in Data Asset Orchestration Platform

Dagster is an orchestration platform for the development, production, and observation of data assets. Prior to Dagster Core version 1.13.1 and prior to Dagster libraries version 0.29.1, the DuckDB, Snowflake, BigQuery, and DeltaLake I/O managers constructed SQL WHERE clauses by interpolating dynamic partition key values into queries without escaping. A user with the Add Dynamic Partitions permission could create a partition key that injects arbitrary SQL, which would execute against the target database backend under the I/O manager's credentials. Only deployments that use dynamic partitions are affected. Pipelines using static or time-window partitions are not impacted. This issue has been patched in Dagster Core version 1.13.1 and Dagster libraries version 0.29.1.

Casky was already ahead

This CVE exploits attack patterns that Casky's 301matched skills already investigate — long before this vulnerability was disclosed. Claude's reasoning model maps these techniques to MITRE ATT&CK, so practitioners who ran these skills have already seen the threat behaviour in their findings.

Analysis

Dagster's I/O managers for DuckDB, Snowflake, BigQuery, and DeltaLake constructed dynamic SQL WHERE clauses by directly interpolating partition key values without proper escaping or parameterization. This SQL injection vulnerability (CWE-89) allows users with Add Dynamic Partitions permission to inject arbitrary SQL commands that execute against backend databases. Organizations using Dagster for data orchestration face risk of unauthorized data access, modification, or deletion through a low-privilege account—making this particularly dangerous in multi-tenant environments where partition management is delegated across teams.

Casky's 301 matching skills leverage Claude's extended reasoning to identify attack patterns spanning initial access (TA0001) and exfiltration (TA0043). Security practitioners using Casky would detect the reconnaissance phase as attackers probe partition key inputs with SQL metacharacters (single quotes, comments, UNION operators), followed by detection of actual injection payloads in partition creation events. The platform maps suspicious SQL constructs in dynamic queries, anomalous database permissions escalations, and data query patterns inconsistent with legitimate partition operations—surfacing these indicators across execution logs, audit trails, and query analytics before data compromise occurs.

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Casky Risk Score

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EPSS Probability

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Shodan Exposure

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GreyNoise Signal

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301 Casky skills cover this attack pattern

These skills use Claude AI's reasoning model to surface findings in the same attack categories as CVE-2026-41490.

analyzing-apt-group-with-mitre-navigator

threat intelligence · low

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analyzing-campaign-attribution-evidence

threat intelligence · low

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analyzing-certificate-transparency-for-phishing

threat intelligence · low

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MITRE ATT&CK Techniques

TA0001 TA0043

Investigate the attack patterns behind CVE-2026-41490

Casky has 301 skills that investigate the attack patterns behind CVE-2026-41490. Run one and get CVSS-scored findings in 3 minutes.

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