7.5
HIGH CVSS 3.1
CVE-2026-59893
sqlparse: Inefficient Regex Handling of Dollar-Quoted SQL Literals Leads to ReDoS (Denial of Service)
Description

sqlparse is a non-validating SQL parser module for Python. Prior to 0.6.0, 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, causing quadratic CPU consumption through sqlparse.parse(), sqlparse.format(), and sqlparse.split(). This issue is fixed in version 0.6.0.

INFO

Published Date :

Aug. 17, 2026, 6:17 p.m.

Last Modified :

Aug. 17, 2026, 6:17 p.m.

Remotely Exploit :

Yes !
Affected Products

The following products are affected by CVE-2026-59893 vulnerability. Even if cvefeed.io is aware of the exact versions of the products that are affected, the information is not represented in the table below.

No affected product recoded yet

CVSS Scores
The Common Vulnerability Scoring System is a standardized framework for assessing the severity of vulnerabilities in software and systems. We collect and displays CVSS scores from various sources for each CVE.
Score Version Severity Vector Exploitability Score Impact Score Source
CVSS 3.1 HIGH [email protected]
Solution
Update sqlparse to version 0.6.0 or later to fix performance issues.
  • Update sqlparse to version 0.6.0 or later.
  • Avoid parsing unmatched delimiters.
References to Advisories, Solutions, and Tools

Here, you will find a curated list of external links that provide in-depth information, practical solutions, and valuable tools related to CVE-2026-59893.

URL Resource
https://github.com/andialbrecht/sqlparse/commit/d1d80602741f77ec78e5a04ce4719244cf32352e
https://github.com/andialbrecht/sqlparse/security/advisories/GHSA-prg7-hcfm-mfcr
CWE - Common Weakness Enumeration

While CVE identifies specific instances of vulnerabilities, CWE categorizes the common flaws or weaknesses that can lead to vulnerabilities. CVE-2026-59893 is associated with the following CWEs:

Common Attack Pattern Enumeration and Classification (CAPEC)

Common Attack Pattern Enumeration and Classification (CAPEC) stores attack patterns, which are descriptions of the common attributes and approaches employed by adversaries to exploit the CVE-2026-59893 weaknesses.

We scan GitHub repositories to detect new proof-of-concept exploits. Following list is a collection of public exploits and proof-of-concepts, which have been published on GitHub (sorted by the most recently updated).

Results are limited to the first 15 repositories due to potential performance issues.

The following list is the news that have been mention CVE-2026-59893 vulnerability anywhere in the article.

The following table lists the changes that have been made to the CVE-2026-59893 vulnerability over time.

Vulnerability history details can be useful for understanding the evolution of a vulnerability, and for identifying the most recent changes that may impact the vulnerability's severity, exploitability, or other characteristics.

  • New CVE Received by [email protected]

    Aug. 17, 2026

    Action Type Old Value New Value
    Added Affected [{'vendor': 'andialbrecht', 'product': 'sqlparse', 'versions': [{'status': 'affected', 'version': '< 0.6.0'}]}]
    Added Description sqlparse is a non-validating SQL parser module for Python. Prior to 0.6.0, 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, causing quadratic CPU consumption through sqlparse.parse(), sqlparse.format(), and sqlparse.split(). This issue is fixed in version 0.6.0.
    Added CVSS V3.1 AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
    Added CWE CWE-1333
    Added Reference https://github.com/andialbrecht/sqlparse/commit/d1d80602741f77ec78e5a04ce4719244cf32352e
    Added Reference https://github.com/andialbrecht/sqlparse/security/advisories/GHSA-prg7-hcfm-mfcr
EPSS is a daily estimate of the probability of exploitation activity being observed over the next 30 days. Following chart shows the EPSS score history of the vulnerability.