CVE-2026-59893 andialbrecht CVE debrief

Who should care

Defenders responsible for Python environments where SQL parsing is performed, especially on untrusted input, should assess exposure and verify sqlparse version 0.6.0 or later is in use.

Why it matters

CVE-2026-59893 sqlparse Quadratic CPU Consumption: Defenders should prioritize verifying sqlparse version 0.6.0 or later in Python environments, especially where SQL parsing is performed on untrusted input, due to potential performance impacts.

• Potential performance degradation due to increased CPU consumption
• Need for verification of sqlparse version in use
• Possible impact on systems handling large volumes of SQL input

Technical summary

The sqlparse Python module, prior to version 0.6.0, contains a vulnerability that can lead to quadratic CPU consumption. This occurs because the SQL_REGEX in sqlparse/keywords.py and the per-position loop in sqlparse/lexer.py repeatedly scan unmatched dollar-quoted literal and multiline-comment delimiters. This issue can be triggered through functions like sqlparse.parse(), sqlparse.format(), and sqlparse.split().

Defensive priority

Defenders should prioritize verifying sqlparse version 0.6.0 or later in Python environments, especially where SQL parsing is performed on untrusted input.

Recommended defensive actions

• Verify sqlparse version 0.6.0 or later is in use
• Review and limit SQL parsing on untrusted input
• Monitor for potential performance impacts
• Perform vulnerability scanning to identify exposed systems
• Implement compensating controls for exposed systems
• Review change management processes for SQL parsing updates
• Track and verify remediation of exposed assets

Evidence notes

The CVE record and NVD entry detail a vulnerability in sqlparse, a Python SQL parser module, where prior to version 0.6.0, it is susceptible to quadratic CPU consumption through repeated scanning of unmatched dollar-quoted literal and multiline-comment delimiters.

Sources and references

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.