CVE-2026-71491: sqlparse Denial of Service Vulnerability

HIGH
Advisory Identifier: GHSA-f2ff-p2ww-7p4p
CWE-400 CWE-407
Published
Advisory Summary

CVE-2026-71491 is a HIGH denial of service vulnerability (CWE-400: Uncontrolled Resource Consumption) affecting sqlparse libraries in the PyPI ecosystem. The issue involves quadratic o(n²) dos in group_comments. Remediation is available by upgrading affected packages to version 0.6.0.

CVE-2026-71491 at a Glance

CVE Identifier CVE-2026-71491
GHSA Identifier GHSA-f2ff-p2ww-7p4p
Severity HIGH
CVSS v3.1 Base Score N/A
CWE Classification CWE-400: Uncontrolled Resource Consumption
Affected Product sqlparse
Package Ecosystem PyPI
Published Date
Last Updated

How to Fix CVE-2026-71491

To remediate this vulnerability, upgrade all affected sqlparse dependencies to a patched release. Both direct and transitive dependencies should be checked, as frameworks or security libraries may pull in vulnerable versions transitively.

sqlparse fixed: 0.6.0
pip install sqlparse>=0.6.0
Verify Direct and Transitive Dependencies

Run the following command in your project directory to verify that all resolved dependencies use the patched release:

pip show sqlparse

How to Check if You Are Affected

To determine whether your Python environment is affected by CVE-2026-71491, inspect your installed packages using pip:

pip show sqlparse

Analyze the terminal output to locate any version of sqlparse in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than 0.6.0), your application is affected.

Note: The pip show sqlparse command checks currently installed packages in your active Python environment.

Technical Details

Vulnerability Mechanism & Technical Analysis

This vulnerability is classified under CWE-400: Uncontrolled Resource Consumption, where the product does not properly control the allocation and maintenance of a limited resource. In sqlparse, software state validation or input boundaries are circumvented during processing. Review the official source advisory statement below for specific affected components, classes, and reproduction details.

Source Advisory Statement

### Summary A comment-only statement (`-- c\n`*n) may cause a Denial of Service (DoS). ### Details Location: [sqlparse/engine/grouping.py:331-341](https://github.com/andialbrecht/sqlparse/blob/f80af6a4007f11ada847218df8c29dc859238290/sqlparse/engine/grouping.py#L332) (`group_comments`), invoked first in `group()` at `grouping.py:439`. Reachable via `sqlparse.parse()` and `sqlparse.format(sql, strip_comments=True)`. A statement made of many single-line comments (`'-- c\n'` repeated) lexes in O(n) but `group_comments` is O(n²): ```python def group_comments(tlist): tidx, token = tlist.token_next_by(t=T.Comment) while token: eidx, end = tlist.token_not_matching( lambda tk: imt(tk, t=T.Comment) or tk.is_newline, idx=tidx) ... tidx, token = tlist.token_next_by(t=T.Comment, idx=tidx) ``` The `while` loop runs n times and each `token_next_by` / `token_not_matching` rescans the O(n) remaining tokens. When all tokens are comments/newlines nothing ever groups, yet the full scan is repeated per token. Two following factors increase the severity: 1. `group_comments` runs first in `group()` (`grouping.py:439`), before the `_group_matching` token-count guard (`grouping.py:34-39`). So the entire quadratic cost is paid even on oversized input. `MAX_GROUPING_TOKENS` does not provide protection on this vector. 2. It sits on the primary sanitizer path: `format(sql, strip_comments=True)`, used by query loggers, SQL firewalls, ORMs, and migration tools. ### PoC Tested using Python 3.14: ```python import time, sqlparse for n in (1000, 2000, 4000): s = "-- c\n" * n t = time.perf_counter() sqlparse.format(s, strip_comments=True) print(f"n={n:5d} format(strip_comments)={1000*(time.perf_counter()-t):7.1f} ms") ``` Output: ``` n= 1000 format(strip_comments)= 106.0 ms n= 2000 format(strip_comments)= 403.3 ms n= 4000 format(strip_comments)= 1602.8 ms ``` Time increase of ~4× per 2× input (quadratic). `parse()` shows the identical curve. Instrumented scan counts are exactly 1.0M / 4.0M / 16.0M tokens for n=1000/2000/4000. A ~250 KB comment-only payload forces minutes of CPU regardless of the 10000 token cap. ### Impact Denial of Service

CVE-2026-71491 Affected sqlparse Versions

1 component(s)
Fixed Versions:
0.6.0
Product / Package Ecosystem Affected Versions Fixed Version
sqlparse
PyPI
< 0.6.0
0.6.0

References

Frequently Asked Questions

What is CVE-2026-71491?
CVE-2026-71491 is a security vulnerability in sqlparse involving Quadratic O(n²) DoS in group_comments under CWE-400: Uncontrolled Resource Consumption.
Which sqlparse versions are affected?
Affected versions include releases prior to 0.6.0 across affected packages: sqlparse.
What version fixes CVE-2026-71491?
Upgrading to 0.6.0 (or the latest patched release for your respective branch) resolves the vulnerability.
Is sqlparse affected?
Yes, sqlparse is affected in releases prior to 0.6.0. Upgrade your dependency to 0.6.0 or later.
What CWE is associated with CVE-2026-71491?
CVE-2026-71491 is classified under CWE-400: Uncontrolled Resource Consumption (The product does not properly control the allocation and maintenance of a limited resource.).
How can I check PyPI dependencies for CVE-2026-71491?
Run the dependency tree command: 'pip show sqlparse'. This command lists direct and transitive dependencies in your build configuration so you can verify if a vulnerable version is resolved.
Machine-readable OSV JSON OSV v1.5 Schema
Normalized schema output
{
  "schema_version" : "1.4.0",
  "id" : "GHSA-f2ff-p2ww-7p4p",
  "modified" : "2026-08-17T17:21:00Z",
  "published" : "2026-08-17T17:21:00Z",
  "aliases" : [ "CVE-2026-71491" ],
  "summary" : "sqlparse: Quadratic O(n²) DoS in group_comments",
  "details" : "### Summary\nA comment-only statement (`-- c\\n`*n) may cause a Denial of Service (DoS).\n\n### Details\nLocation: [sqlparse/engine/grouping.py:331-341](https://github.com/andialbrecht/sqlparse/blob/f80af6a4007f11ada847218df8c29dc859238290/sqlparse/engine/grouping.py#L332) (`group_comments`), invoked first in `group()` at `grouping.py:439`. Reachable via `sqlparse.parse()` and `sqlparse.format(sql, strip_comments=True)`.\n\nA statement made of many single-line comments (`'-- c\\n'` repeated) lexes in O(n) but `group_comments` is O(n²):\n\n```python\ndef group_comments(tlist):\n    tidx, token = tlist.token_next_by(t=T.Comment)\n    while token:\n        eidx, end = tlist.token_not_matching(\n            lambda tk: imt(tk, t=T.Comment) or tk.is_newline, idx=tidx)\n        ...\n        tidx, token = tlist.token_next_by(t=T.Comment, idx=tidx)\n```\n\nThe `while` loop runs n times and each `token_next_by` / `token_not_matching` rescans the O(n) remaining tokens. When all tokens are comments/newlines nothing ever groups, yet the full scan is repeated per token.\n\nTwo following factors increase the severity:\n\n1. `group_comments` runs first in `group()` (`grouping.py:439`), before the `_group_matching` token-count guard (`grouping.py:34-39`). So the entire quadratic cost is paid even on oversized input. `MAX_GROUPING_TOKENS` does not provide protection on this vector.\n2. It sits on the primary sanitizer path: `format(sql, strip_comments=True)`, used by query loggers, SQL firewalls, ORMs, and migration tools.\n\n### PoC\nTested using Python 3.14:\n\n```python\nimport time, sqlparse\nfor n in (1000, 2000, 4000):\n    s = \"-- c\\n\" * n\n    t = time.perf_counter()\n    sqlparse.format(s, strip_comments=True)\n    print(f\"n={n:5d}  format(strip_comments)={1000*(time.perf_counter()-t):7.1f} ms\")\n```\n\nOutput:\n\n```\nn= 1000  format(strip_comments)=  106.0 ms\nn= 2000  format(strip_comments)=  403.3 ms\nn= 4000  format(strip_comments)= 1602.8 ms\n```\n\nTime increase of ~4× per 2× input (quadratic). `parse()` shows the identical curve. Instrumented scan counts are exactly 1.0M / 4.0M / 16.0M tokens for n=1000/2000/4000. A ~250 KB comment-only payload forces minutes of CPU regardless of the 10000 token cap.\n\n### Impact\nDenial of Service",
  "severity" : [ {
    "type" : "CVSS_V4",
    "score" : "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N"
  } ],
  "affected" : [ {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "sqlparse"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "0"
      }, {
        "fixed" : "0.6.0"
      } ]
    } ],
    "database_specific" : {
      "last_known_affected_version_range" : "<= 0.5.5"
    }
  } ],
  "references" : [ {
    "type" : "WEB",
    "url" : "https://github.com/andialbrecht/sqlparse/security/advisories/GHSA-f2ff-p2ww-7p4p"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/andialbrecht/sqlparse/commit/ef2012a5eeb491e604dea2b00d516904a3830c87"
  }, {
    "type" : "PACKAGE",
    "url" : "https://github.com/andialbrecht/sqlparse"
  } ],
  "database_specific" : {
    "cwe_ids" : [ "CWE-400", "CWE-407" ],
    "severity" : "HIGH",
    "github_reviewed" : true,
    "github_reviewed_at" : "2026-08-17T17:21:00Z",
    "nvd_published_at" : null
  }
}