PYSEC-2026-3697

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Import Source
https://github.com/pypa/advisory-database/blob/main/vulns/sqlparse/PYSEC-2026-3697.yaml
JSON Data
https://api.osv.dev/v1/vulns/PYSEC-2026-3697
Aliases
Published
2026-08-19T11:56:27Z
Modified
2026-08-19T12:45:05Z
Severity
  • 8.7 (High) CVSS_V4 - 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 CVSS Calculator
Summary
sqlparse: Quadratic O(n²) DoS in group_comments
Details

Summary

A comment-only statement (-- c\n*n) may cause a Denial of Service (DoS).

Details

Location: sqlparse/engine/grouping.py:331-341 (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):

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:

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

References

Affected packages

PyPI / sqlparse

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
0 Unknown introduced version / All previous versions are affected
Fixed
0.6.0

Affected versions

0.*
0.1.0
0.1.1
0.1.2
0.1.3
0.1.4
0.1.5
0.1.6
0.1.7
0.1.8
0.1.9
0.1.10
0.1.11
0.1.12
0.1.13
0.1.14
0.1.15
0.1.16
0.1.17
0.1.18
0.1.19
0.2.0
0.2.1
0.2.2
0.2.3
0.2.4
0.3.0
0.3.1
0.4.0
0.4.1
0.4.2
0.4.3
0.4.4
0.5.0
0.5.1
0.5.2
0.5.3
0.5.4
0.5.5

Database specific

source
"https://github.com/pypa/advisory-database/blob/main/vulns/sqlparse/PYSEC-2026-3697.yaml"