PatchSiren cyber security CVE debrief
CVE-2026-59894 andialbrecht CVE debrief
CVE-2026-59894 sqlparse Injection Vulnerability: The sqlparse module for Python, prior to version 0.6.0, fails to escape existing backslashes before quotes in sqlparse.format output_format='python' and output_format='php'. This allows crafted SQL to terminate the generated string and inject Python or PHP code. Developers and security teams using sqlparse in Python projects should assess their exposure and verify version 0.6.0 or later. The issue is fixed in version 0.6.0 and requires review of generated SQL output to prevent potential code injection.
- Vendor
- andialbrecht
- Product
- sqlparse
- CVSS
- MEDIUM 6.2
- CISA KEV
- Not listed in stored evidence
- Original CVE published
- 2026-08-17
- Original CVE updated
- 2026-09-18
- Advisory published
- 2026-08-17
- Advisory updated
- 2026-09-18
Who should care
Developers and security teams using sqlparse in Python projects should assess their exposure and verify version 0.6.0 or later. The vulnerability allows crafted SQL to terminate the generated string and inject Python or PHP code. Review generated SQL output to prevent potential code injection. Affected operators, platforms, and security teams should review compensating controls and monitoring for exposed assets.
Why it matters
CVE-2026-59894 sqlparse Injection Vulnerability: Assess sqlparse usage, verify version 0.6.0 or later, and review generated SQL output to prevent potential code injection.
- Potential code injection through generated SQL output
- Required verification of sqlparse version and usage
- Possible impact on downstream consumers executing or importing generated source
Technical summary
The sqlparse module for Python, prior to version 0.6.0, fails to escape existing backslashes before quotes in sqlparse.format output_format='python' and output_format='php'. This allows crafted SQL to terminate the generated string and inject Python or PHP code when a downstream consumer executes or imports the generated source. The issue is fixed in version 0.6.0 and requires review of generated SQL output to prevent potential code injection. Developers and security teams using sqlparse in Python projects should assess their exposure.
Defensive priority
Assess sqlparse usage, verify version 0.6.0 or later, and review generated SQL output.
Recommended defensive actions
- Assess sqlparse usage in Python projects
- Verify sqlparse version 0.6.0 or later
- Review generated SQL output for potential injection
- Confirm whether affected product deployments exist in managed environments and assign an owner for follow-up
- Plan vendor-supported updates or mitigations through normal change control where exposure is confirmed
- Review compensating controls for exposed systems while remediation is scheduled and verified
- Check relevant monitoring, detection, and logs for exposed assets that need extra review
Evidence notes
The CVE record and NVD entry provide details on the sqlparse vulnerability. The issue is fixed in version 0.6.0. Developers should verify sqlparse version and review generated SQL output for potential injection. The vulnerability allows crafted SQL to terminate the generated string and inject Python or PHP code. Official CVE Program record and NIST NVD detail page provide source-provided CVE metadata and vulnerability assessment.
Sources and references
Verified primary and authoritative sources
-
CVE-2026-59894 CVE Program record
Publisher, destination, and source semantics verified
URL: https://www.cve.org/CVERecord?id=CVE-2026-59894
CVE Program - Official CVE Program record with source-provided CVE metadata.
-
CVE-2026-59894 NVD vulnerability detail
Publisher, destination, and source semantics verified
URL: https://nvd.nist.gov/vuln/detail/CVE-2026-59894
NIST National Vulnerability Database - Official NIST NVD detail page and source-specific vulnerability assessment.
Supplemental references
-
Source reference
Unverified legacy reference
URL: https://github.com/andialbrecht/sqlparse/security/advisories/GHSA-3496-9g83-7v6x
Methodology and review provenance
AI-assisted synthesis based on stored public vulnerability evidence. System validation, approval state, and publication status do not by themselves establish human review of this revision. PatchSiren helps prioritize defensive review and does not prove exposure or remediation on any system.