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GHSA-F2FF-P2WW-7P4P
Vulnerability from github – Published: 2026-08-17 17:21 – Updated: 2026-08-17 17:21
VLAI
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:
group_commentsruns first ingroup()(grouping.py:439), before the_group_matchingtoken-count guard (grouping.py:34-39). So the entire quadratic cost is paid even on oversized input.MAX_GROUPING_TOKENSdoes not provide protection on this vector.- 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
Severity
{
"affected": [
{
"database_specific": {
"last_known_affected_version_range": "\u003c= 0.5.5"
},
"package": {
"ecosystem": "PyPI",
"name": "sqlparse"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "0.6.0"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2026-71491"
],
"database_specific": {
"cwe_ids": [
"CWE-400",
"CWE-407"
],
"github_reviewed": true,
"github_reviewed_at": "2026-08-17T17:21:00Z",
"nvd_published_at": null,
"severity": "HIGH"
},
"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 (`\u0027-- c\\n\u0027` repeated) lexes in O(n) but `group_comments` is O(n\u00b2):\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\u00d7 per 2\u00d7 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",
"id": "GHSA-f2ff-p2ww-7p4p",
"modified": "2026-08-17T17:21:00Z",
"published": "2026-08-17T17:21:00Z",
"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"
}
],
"schema_version": "1.4.0",
"severity": [
{
"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",
"type": "CVSS_V4"
}
],
"summary": "sqlparse: Quadratic O(n\u00b2) DoS in group_comments"
}
BREW-ATHENACLI-CVE-2026-71491 (GHSA-F2FF-P2WW-7P4P)
Vulnerability from osv_homebrew – Published: 2026-08-18 08:40 – Updated: 2026-09-09 23:42 – Source website
VLAI
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:
group_commentsruns first ingroup()(grouping.py:439), before the_group_matchingtoken-count guard (grouping.py:34-39). So the entire quadratic cost is paid even on oversized input.MAX_GROUPING_TOKENSdoes not provide protection on this vector.- 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
Severity
References
{
"affected": [
{
"ecosystem_specific": {
"fix": null,
"range_state": "affected",
"resource": "sqlparse",
"resource_purl": "pkg:pypi/sqlparse@0.4.4",
"upstream_fixed_in": "0.6.0"
},
"package": {
"ecosystem": "Homebrew",
"name": "athenacli",
"purl": "pkg:brew/athenacli"
},
"ranges": [
{
"events": [
{
"introduced": "0"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"database_specific": {
"confidence": "high",
"source": "matched",
"strategy": "registry",
"upstream_evidence": [
{
"ecosystem": "PyPI",
"key": "pkg:pypi/sqlparse@0.4.4",
"name": "sqlparse",
"resource": "sqlparse",
"strategy": "registry",
"subject_version": "0.4.4"
}
]
},
"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 (`\u0027-- c\\n\u0027` repeated) lexes in O(n) but `group_comments` is O(n\u00b2):\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\u00d7 per 2\u00d7 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",
"id": "BREW-athenacli-CVE-2026-71491",
"modified": "2026-09-09T23:42:04Z",
"published": "2026-08-18T08:40:55Z",
"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"
}
],
"schema_version": "1.7.3",
"severity": [
{
"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",
"type": "CVSS_V4"
}
],
"summary": "sqlparse: Quadratic O(n\u00b2) DoS in group_comments",
"upstream": [
"GHSA-f2ff-p2ww-7p4p",
"CVE-2026-71491",
"PYSEC-2026-3697"
]
}
BREW-DOLPHIE-CVE-2026-71491 (GHSA-F2FF-P2WW-7P4P)
Vulnerability from osv_homebrew – Published: 2026-08-18 08:47 – Updated: 2026-09-12 08:52 – Source website
VLAI
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:
group_commentsruns first ingroup()(grouping.py:439), before the_group_matchingtoken-count guard (grouping.py:34-39). So the entire quadratic cost is paid even on oversized input.MAX_GROUPING_TOKENSdoes not provide protection on this vector.- 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
Severity
References
{
"affected": [
{
"ecosystem_specific": {
"fix": "bump",
"range_state": "fixed",
"resource": "sqlparse",
"resource_purl": "pkg:pypi/sqlparse@0.6.0",
"upstream_fixed_in": "0.6.0"
},
"package": {
"ecosystem": "Homebrew",
"name": "dolphie",
"purl": "pkg:brew/dolphie"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "6.16.0"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"database_specific": {
"confidence": "high",
"source": "matched",
"strategy": "registry",
"upstream_evidence": [
{
"ecosystem": "PyPI",
"key": "pkg:pypi/sqlparse@0.6.0",
"name": "sqlparse",
"resource": "sqlparse",
"strategy": "registry",
"subject_version": "0.6.0"
}
]
},
"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 (`\u0027-- c\\n\u0027` repeated) lexes in O(n) but `group_comments` is O(n\u00b2):\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\u00d7 per 2\u00d7 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",
"id": "BREW-dolphie-CVE-2026-71491",
"modified": "2026-09-12T08:52:42Z",
"published": "2026-08-18T08:47:49Z",
"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"
}
],
"schema_version": "1.7.3",
"severity": [
{
"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",
"type": "CVSS_V4"
}
],
"summary": "sqlparse: Quadratic O(n\u00b2) DoS in group_comments",
"upstream": [
"GHSA-f2ff-p2ww-7p4p",
"CVE-2026-71491",
"PYSEC-2026-3697"
]
}
BREW-LITECLI-CVE-2026-71491 (GHSA-F2FF-P2WW-7P4P)
Vulnerability from osv_homebrew – Published: 2026-08-18 09:06 – Updated: 2026-09-10 19:42 – Source website
VLAI
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:
group_commentsruns first ingroup()(grouping.py:439), before the_group_matchingtoken-count guard (grouping.py:34-39). So the entire quadratic cost is paid even on oversized input.MAX_GROUPING_TOKENSdoes not provide protection on this vector.- 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
Severity
References
{
"affected": [
{
"ecosystem_specific": {
"fix": "bump",
"range_state": "fixed",
"resource": "sqlparse",
"resource_purl": "pkg:pypi/sqlparse@0.6.0",
"upstream_fixed_in": "0.6.0"
},
"package": {
"ecosystem": "Homebrew",
"name": "litecli",
"purl": "pkg:brew/litecli"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "1.17.1_3"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"database_specific": {
"confidence": "high",
"source": "matched",
"strategy": "registry",
"upstream_evidence": [
{
"ecosystem": "PyPI",
"key": "pkg:pypi/sqlparse@0.6.0",
"name": "sqlparse",
"resource": "sqlparse",
"strategy": "registry",
"subject_version": "0.6.0"
}
]
},
"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 (`\u0027-- c\\n\u0027` repeated) lexes in O(n) but `group_comments` is O(n\u00b2):\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\u00d7 per 2\u00d7 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",
"id": "BREW-litecli-CVE-2026-71491",
"modified": "2026-09-10T19:42:52Z",
"published": "2026-08-18T09:06:13Z",
"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"
}
],
"schema_version": "1.7.3",
"severity": [
{
"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",
"type": "CVSS_V4"
}
],
"summary": "sqlparse: Quadratic O(n\u00b2) DoS in group_comments",
"upstream": [
"GHSA-f2ff-p2ww-7p4p",
"CVE-2026-71491",
"PYSEC-2026-3697"
]
}
BREW-MYCLI-CVE-2026-71491 (GHSA-F2FF-P2WW-7P4P)
Vulnerability from osv_homebrew – Published: 2026-08-17 17:34 – Updated: 2026-09-10 00:35 – Source website
VLAI
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:
group_commentsruns first ingroup()(grouping.py:439), before the_group_matchingtoken-count guard (grouping.py:34-39). So the entire quadratic cost is paid even on oversized input.MAX_GROUPING_TOKENSdoes not provide protection on this vector.- 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
Severity
References
{
"affected": [
{
"ecosystem_specific": {
"fix": "bump",
"range_state": "fixed",
"resource": "sqlparse",
"resource_purl": "pkg:pypi/sqlparse@0.6.0",
"upstream_fixed_in": "0.6.0"
},
"package": {
"ecosystem": "Homebrew",
"name": "mycli",
"purl": "pkg:brew/mycli"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.19.0"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"database_specific": {
"confidence": "high",
"source": "matched",
"strategy": "registry",
"upstream_evidence": [
{
"ecosystem": "PyPI",
"key": "pkg:pypi/sqlparse@0.6.0",
"name": "sqlparse",
"resource": "sqlparse",
"strategy": "registry",
"subject_version": "0.6.0"
}
]
},
"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 (`\u0027-- c\\n\u0027` repeated) lexes in O(n) but `group_comments` is O(n\u00b2):\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\u00d7 per 2\u00d7 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",
"id": "BREW-mycli-CVE-2026-71491",
"modified": "2026-09-10T00:35:46Z",
"published": "2026-08-17T17:34:03Z",
"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"
}
],
"schema_version": "1.7.3",
"severity": [
{
"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",
"type": "CVSS_V4"
}
],
"summary": "sqlparse: Quadratic O(n\u00b2) DoS in group_comments",
"upstream": [
"GHSA-f2ff-p2ww-7p4p",
"CVE-2026-71491",
"PYSEC-2026-3697"
]
}
BREW-PGCLI-CVE-2026-71491 (GHSA-F2FF-P2WW-7P4P)
Vulnerability from osv_homebrew – Published: 2026-08-17 17:42 – Updated: 2026-09-10 00:51 – Source website
VLAI
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:
group_commentsruns first ingroup()(grouping.py:439), before the_group_matchingtoken-count guard (grouping.py:34-39). So the entire quadratic cost is paid even on oversized input.MAX_GROUPING_TOKENSdoes not provide protection on this vector.- 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
Severity
References
{
"affected": [
{
"ecosystem_specific": {
"fix": "bump",
"range_state": "fixed",
"resource": "sqlparse",
"resource_purl": "pkg:pypi/sqlparse@0.6.0",
"upstream_fixed_in": "0.6.0"
},
"package": {
"ecosystem": "Homebrew",
"name": "pgcli",
"purl": "pkg:brew/pgcli"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "4.6.0"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"database_specific": {
"confidence": "high",
"source": "matched",
"strategy": "registry",
"upstream_evidence": [
{
"ecosystem": "PyPI",
"key": "pkg:pypi/sqlparse@0.6.0",
"name": "sqlparse",
"resource": "sqlparse",
"strategy": "registry",
"subject_version": "0.6.0"
}
]
},
"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 (`\u0027-- c\\n\u0027` repeated) lexes in O(n) but `group_comments` is O(n\u00b2):\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\u00d7 per 2\u00d7 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",
"id": "BREW-pgcli-CVE-2026-71491",
"modified": "2026-09-10T00:51:13Z",
"published": "2026-08-17T17:42:48Z",
"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"
}
],
"schema_version": "1.7.3",
"severity": [
{
"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",
"type": "CVSS_V4"
}
],
"summary": "sqlparse: Quadratic O(n\u00b2) DoS in group_comments",
"upstream": [
"GHSA-f2ff-p2ww-7p4p",
"CVE-2026-71491",
"PYSEC-2026-3697"
]
}
BREW-SQLPARSE-CVE-2026-71491 (CVE-2026-71491)
Vulnerability from osv_homebrew – Published: 2026-08-17 17:55 – Updated: 2026-09-10 01:21 – Source website
VLAI
Summary
sqlparse: Quadratic O(n²) DoS in group_comments
Details
sqlparse is a non-validating SQL parser module for Python. Prior to 0.6.0, group_comments in sqlparse/engine/grouping.py repeatedly rescans comment-only statements before the MAX_GROUPING_TOKENS guard, causing quadratic CPU consumption through sqlparse.parse() and sqlparse.format(sql, strip_comments=True). This issue is fixed in version 0.6.0.
Severity
References
{
"affected": [
{
"ecosystem_specific": {
"fix": "bump",
"range_state": "fixed",
"upstream_fixed_in": "0.6.0"
},
"package": {
"ecosystem": "Homebrew",
"name": "sqlparse",
"purl": "pkg:brew/sqlparse"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "0.6.0"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"database_specific": {
"confidence": "high",
"source": "matched",
"strategy": "git",
"upstream_evidence": [
{
"ecosystem": "GIT",
"key": "https://github.com/andialbrecht/sqlparse",
"name": "https://github.com/andialbrecht/sqlparse",
"strategy": "git",
"subject_version": "0.6.0"
},
{
"ecosystem": "PyPI",
"key": "pkg:pypi/sqlparse@0.6.0",
"name": "sqlparse",
"strategy": "registry",
"subject_version": "0.6.0"
},
{
"ecosystem": "Debian",
"key": "Debian/sqlparse",
"name": "sqlparse",
"strategy": "distro"
},
{
"ecosystem": "GIT",
"key": "upstream:https://github.com/andialbrecht/sqlparse",
"name": "https://github.com/andialbrecht/sqlparse",
"strategy": "distro",
"subject_version": "0.6.0"
},
{
"ecosystem": "PyPI",
"key": "upstream:pkg:pypi/sqlparse@0.6.0",
"name": "sqlparse",
"strategy": "distro",
"subject_version": "0.6.0"
},
{
"ecosystem": "Ubuntu",
"key": "Ubuntu/sqlparse",
"name": "sqlparse",
"strategy": "distro"
}
]
},
"details": "sqlparse is a non-validating SQL parser module for Python. Prior to 0.6.0, group_comments in sqlparse/engine/grouping.py repeatedly rescans comment-only statements before the MAX_GROUPING_TOKENS guard, causing quadratic CPU consumption through sqlparse.parse() and sqlparse.format(sql, strip_comments=True). This issue is fixed in version 0.6.0.",
"id": "BREW-sqlparse-CVE-2026-71491",
"modified": "2026-09-10T01:21:20Z",
"published": "2026-08-17T17:55:23Z",
"references": [
{
"type": "ADVISORY",
"url": "https://github.com/CVEProject/cvelistV5/tree/main/cves/2026/71xxx/CVE-2026-71491.json"
},
{
"type": "ADVISORY",
"url": "https://github.com/andialbrecht/sqlparse/security/advisories/GHSA-f2ff-p2ww-7p4p"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-71491"
},
{
"type": "FIX",
"url": "https://github.com/andialbrecht/sqlparse/commit/ef2012a5eeb491e604dea2b00d516904a3830c87"
}
],
"schema_version": "1.7.3",
"severity": [
{
"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",
"type": "CVSS_V4"
}
],
"summary": "sqlparse: Quadratic O(n\u00b2) DoS in group_comments",
"upstream": [
"CVE-2026-71491",
"GHSA-f2ff-p2ww-7p4p",
"PYSEC-2026-3697"
]
}
CVE-2026-71491 (GCVE-0-2026-71491)
Vulnerability from cvelistv5 – Published: 2026-08-17 17:16 – Updated: 2026-08-17 22:01
VLAI
EPSS
VEX
Title
sqlparse: Quadratic O(n²) DoS in group_comments
Summary
sqlparse is a non-validating SQL parser module for Python. Prior to 0.6.0, group_comments in sqlparse/engine/grouping.py repeatedly rescans comment-only statements before the MAX_GROUPING_TOKENS guard, causing quadratic CPU consumption through sqlparse.parse() and sqlparse.format(sql, strip_comments=True). This issue is fixed in version 0.6.0.
Severity
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-08-17 22:00 UTC
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/andialbrecht/sqlparse/security… | x_refsource_CONFIRM |
| https://github.com/andialbrecht/sqlparse/commit/e… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| andialbrecht | sqlparse |
Affected:
< 0.6.0
|
{
"containers": {
"adp": [
{
"metrics": [
{
"other": {
"content": {
"id": "CVE-2026-71491",
"options": [
{
"Exploitation": "none"
},
{
"Automatable": "yes"
},
{
"Technical Impact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2026-08-17T22:00:09.876988Z",
"version": "2.0.3"
},
"type": "ssvc"
}
}
],
"providerMetadata": {
"dateUpdated": "2026-08-17T22:01:34.222Z",
"orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"shortName": "CISA-ADP"
},
"title": "CISA ADP Vulnrichment"
}
],
"cna": {
"affected": [
{
"product": "sqlparse",
"vendor": "andialbrecht",
"versions": [
{
"status": "affected",
"version": "\u003c 0.6.0"
}
]
}
],
"descriptions": [
{
"lang": "en",
"value": "sqlparse is a non-validating SQL parser module for Python. Prior to 0.6.0, group_comments in sqlparse/engine/grouping.py repeatedly rescans comment-only statements before the MAX_GROUPING_TOKENS guard, causing quadratic CPU consumption through sqlparse.parse() and sqlparse.format(sql, strip_comments=True). This issue is fixed in version 0.6.0."
}
],
"metrics": [
{
"cvssV4_0": {
"attackComplexity": "LOW",
"attackRequirements": "NONE",
"attackVector": "NETWORK",
"baseScore": 8.7,
"baseSeverity": "HIGH",
"privilegesRequired": "NONE",
"subAvailabilityImpact": "NONE",
"subConfidentialityImpact": "NONE",
"subIntegrityImpact": "NONE",
"userInteraction": "NONE",
"vectorString": "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",
"version": "4.0",
"vulnAvailabilityImpact": "HIGH",
"vulnConfidentialityImpact": "NONE",
"vulnIntegrityImpact": "NONE"
}
}
],
"problemTypes": [
{
"descriptions": [
{
"cweId": "CWE-400",
"description": "CWE-400: Uncontrolled Resource Consumption",
"lang": "en",
"type": "CWE"
}
]
},
{
"descriptions": [
{
"cweId": "CWE-407",
"description": "CWE-407: Inefficient Algorithmic Complexity",
"lang": "en",
"type": "CWE"
}
]
}
],
"providerMetadata": {
"dateUpdated": "2026-08-17T17:16:48.973Z",
"orgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
"shortName": "GitHub_M"
},
"references": [
{
"name": "https://github.com/andialbrecht/sqlparse/security/advisories/GHSA-f2ff-p2ww-7p4p",
"tags": [
"x_refsource_CONFIRM"
],
"url": "https://github.com/andialbrecht/sqlparse/security/advisories/GHSA-f2ff-p2ww-7p4p"
},
{
"name": "https://github.com/andialbrecht/sqlparse/commit/ef2012a5eeb491e604dea2b00d516904a3830c87",
"tags": [
"x_refsource_MISC"
],
"url": "https://github.com/andialbrecht/sqlparse/commit/ef2012a5eeb491e604dea2b00d516904a3830c87"
}
],
"source": {
"advisory": "GHSA-f2ff-p2ww-7p4p",
"discovery": "UNKNOWN"
},
"title": "sqlparse: Quadratic O(n\u00b2) DoS in group_comments"
}
},
"cveMetadata": {
"assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
"assignerShortName": "GitHub_M",
"cveId": "CVE-2026-71491",
"datePublished": "2026-08-17T17:16:48.973Z",
"dateReserved": "2026-08-06T19:56:23.725Z",
"dateUpdated": "2026-08-17T22:01:34.222Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.2"
}
PYSEC-2026-3697
Vulnerability from pysec - Published: 2026-08-19 11:56 - Updated: 2026-08-19 12:16
VLAI
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:
group_commentsruns first ingroup()(grouping.py:439), before the_group_matchingtoken-count guard (grouping.py:34-39). So the entire quadratic cost is paid even on oversized input.MAX_GROUPING_TOKENSdoes not provide protection on this vector.- 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
Severity
Impacted products
| Name | purl | sqlparse | pkg:pypi/sqlparse |
|---|
Aliases
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "sqlparse",
"purl": "pkg:pypi/sqlparse"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "0.6.0"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"0.1.0",
"0.1.1",
"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",
"0.1.2",
"0.1.3",
"0.1.4",
"0.1.5",
"0.1.6",
"0.1.7",
"0.1.8",
"0.1.9",
"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"
]
}
],
"aliases": [
"CVE-2026-71491",
"GHSA-f2ff-p2ww-7p4p"
],
"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 (`\u0027-- c\\n\u0027` repeated) lexes in O(n) but `group_comments` is O(n\u00b2):\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\u00d7 per 2\u00d7 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",
"id": "PYSEC-2026-3697",
"modified": "2026-08-19T12:16:39.177334Z",
"published": "2026-08-19T11:56:27.016412Z",
"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"
},
{
"type": "PACKAGE",
"url": "https://pypi.org/project/sqlparse"
},
{
"type": "ADVISORY",
"url": "https://github.com/advisories/GHSA-f2ff-p2ww-7p4p"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-71491"
}
],
"severity": [
{
"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",
"type": "CVSS_V4"
}
],
"summary": "sqlparse: Quadratic O(n\u00b2) DoS in group_comments"
}
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Trend slope:
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(linear fit over daily sighting counts)
Show additional events:
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
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They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
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Browse all ATT&CK techniques and the vulnerabilities related to each.
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