GHSA-FFPJ-XV5C-P3GW

Vulnerability from github – Published: 2026-07-24 16:55 – Updated: 2026-07-24 16:55
VLAI
Summary
Open WebUI: ReDoS in skill-mention regexes causes whole-instance DoS on default config
Details

Summary

Two regexes in backend/open_webui/utils/middleware.py that parse <$skillId|label> skill-mention tags backtrack in O(n²) on input that contains <$ followed by a long run with no closing >. Both run synchronously, on the asyncio event loop, on every chat completion with no feature gate. Because the default deployment is a single uvicorn worker, one such input pins a CPU core inside re and freezes the entire instance for all users until the worker is killed. Any authenticated user can trigger it with one chat message; it also fires accidentally on benign retrieved content (a RAG chunk or tool output) containing the pattern.

Affected versions

>= 0.9.2, < 0.10.0. Fixed in v0.10.0 (there is no 0.9.7 release). - SKILL_MENTION_RE (the extract pattern) has been O(n²) since v0.9.2; exploitable on 0.9.2–0.9.5 with a large input (hundreds of KB). - v0.9.6 added a second, far more aggressive O(n²) in the strip pattern (introduced by the "keep label as readable text" change), so on 0.9.6 a small input is enough to hang the instance.

Both are fixed by the same patch.

Affected component

backend/open_webui/utils/middleware.py (line numbers as of v0.9.6):

# line 2223 — used by extract_skill_ids_from_messages(), called unconditionally (~line 2625)
SKILL_MENTION_RE = re.compile(r'<\$([^|>]+)\|?[^>]*>')

# line 2247 — used by strip_skill_mentions(), called unconditionally (line 2662)
strip_re = re.compile(r'<\$[^|>]+\|?([^>]*)>')

extract_skill_ids_from_messages() runs before the if all_skill_ids: block (that guard gates only skill injection, not the regex), and strip_skill_mentions() runs with no guard at all. Neither requires a skill to exist or any setting to be enabled. Both functions are plain synchronous calls inside the async process_chat_payload coroutine, so they block the event loop; with the default UVICORN_WORKERS=1 (backend/start.sh) the whole instance stalls.

Root cause

[^|>] is a subset of [^>], so the quantifier pair [^|>]+ \|? [^>]* is ambiguous: on input that never closes with >, [^|>]+ greedily consumes the tail, > fails, and the engine backtracks through every split point between [^|>]+ and [^>]* — O(n) positions each doing O(n) work. Polynomial, not exponential, but more than enough to hang a single worker on a ~100 KB input.

Proof of concept

Standalone (no Open WebUI required):

import re, time
EXTRACT = re.compile(r'<\$([^|>]+)\|?[^>]*>')
STRIP   = re.compile(r'<\$[^|>]+\|?([^>]*)>')
for n in (8_000, 16_000, 32_000, 64_000):
    s = '<$' + ('a' * n)
    for name, rx in (('extract', EXTRACT), ('strip', STRIP)):
        t = time.perf_counter(); rx.search(s)
        print(f'n={n:>6} {name:>7} = {(time.perf_counter()-t)*1000:8.1f} ms')

Time quadruples per doubling of n (textbook O(n²)); the strip pattern runs for ~6 seconds on a 64k blob and for minutes on a ~96 KB one.

End-to-end against a live instance (default config): 1. docker run ghcr.io/open-webui/open-webui:v0.9.6 on defaults. 2. Log in as any user (no admin or skill setup). 3. Send a chat message containing <$ followed by 50k+ characters with no >. 4. One CPU core pegs in re; UI and API stop responding for every user until the worker is killed.

Patch

Rewrite the optional |label as a non-capturing optional group so the two quantifiers no longer overlap. Both patterns become linear; captures and substituted output are unchanged on well-formed <$id|label>, <$id|>, and bare <$id> mentions.

SKILL_MENTION_RE = re.compile(r'<\$([^|>]+)(?:\|[^>]*)?>')
strip_re         = re.compile(r'<\$[^|>]+(?:\|([^>]*))?>')

After the patch the same hostile input returns in under 1 ms. Shipped in v0.10.0.

Credit

Reported by @Vlad-WKG, including a correct root-cause analysis and patch.

Show details on source website

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "open-webui"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0.9.2"
            },
            {
              "fixed": "0.10.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2026-59220"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-1333"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-07-24T16:55:55Z",
    "nvd_published_at": "2026-07-09T17:17:03Z",
    "severity": "MODERATE"
  },
  "details": "## Summary\nTwo regexes in `backend/open_webui/utils/middleware.py` that parse `\u003c$skillId|label\u003e` skill-mention tags backtrack in O(n\u00b2) on input that contains `\u003c$` followed by a long run with no closing `\u003e`. Both run synchronously, on the asyncio event loop, on **every** chat completion with no feature gate. Because the default deployment is a single uvicorn worker, one such input pins a CPU core inside `re` and freezes the entire instance for all users until the worker is killed. Any authenticated user can trigger it with one chat message; it also fires accidentally on benign retrieved content (a RAG chunk or tool output) containing the pattern.\n\n## Affected versions\n`\u003e= 0.9.2, \u003c 0.10.0`. Fixed in **v0.10.0** (there is no 0.9.7 release).\n- `SKILL_MENTION_RE` (the extract pattern) has been O(n\u00b2) since **v0.9.2**; exploitable on 0.9.2\u20130.9.5 with a large input (hundreds of KB).\n- **v0.9.6** added a second, far more aggressive O(n\u00b2) in the strip pattern (introduced by the \"keep label as readable text\" change), so on 0.9.6 a small input is enough to hang the instance.\n\nBoth are fixed by the same patch.\n\n## Affected component\n`backend/open_webui/utils/middleware.py` (line numbers as of v0.9.6):\n\n```python\n# line 2223 \u2014 used by extract_skill_ids_from_messages(), called unconditionally (~line 2625)\nSKILL_MENTION_RE = re.compile(r\u0027\u003c\\$([^|\u003e]+)\\|?[^\u003e]*\u003e\u0027)\n\n# line 2247 \u2014 used by strip_skill_mentions(), called unconditionally (line 2662)\nstrip_re = re.compile(r\u0027\u003c\\$[^|\u003e]+\\|?([^\u003e]*)\u003e\u0027)\n```\n\n`extract_skill_ids_from_messages()` runs before the `if all_skill_ids:` block (that guard gates only skill *injection*, not the regex), and `strip_skill_mentions()` runs with no guard at all. Neither requires a skill to exist or any setting to be enabled. Both functions are plain synchronous calls inside the async `process_chat_payload` coroutine, so they block the event loop; with the default `UVICORN_WORKERS=1` (`backend/start.sh`) the whole instance stalls.\n\n## Root cause\n`[^|\u003e]` is a subset of `[^\u003e]`, so the quantifier pair `[^|\u003e]+ \\|? [^\u003e]*` is ambiguous: on input that never closes with `\u003e`, `[^|\u003e]+` greedily consumes the tail, `\u003e` fails, and the engine backtracks through every split point between `[^|\u003e]+` and `[^\u003e]*` \u2014 O(n) positions each doing O(n) work. Polynomial, not exponential, but more than enough to hang a single worker on a ~100 KB input.\n\n## Proof of concept\nStandalone (no Open WebUI required):\n\n```python\nimport re, time\nEXTRACT = re.compile(r\u0027\u003c\\$([^|\u003e]+)\\|?[^\u003e]*\u003e\u0027)\nSTRIP   = re.compile(r\u0027\u003c\\$[^|\u003e]+\\|?([^\u003e]*)\u003e\u0027)\nfor n in (8_000, 16_000, 32_000, 64_000):\n    s = \u0027\u003c$\u0027 + (\u0027a\u0027 * n)\n    for name, rx in ((\u0027extract\u0027, EXTRACT), (\u0027strip\u0027, STRIP)):\n        t = time.perf_counter(); rx.search(s)\n        print(f\u0027n={n:\u003e6} {name:\u003e7} = {(time.perf_counter()-t)*1000:8.1f} ms\u0027)\n```\n\nTime quadruples per doubling of `n` (textbook O(n\u00b2)); the strip pattern runs for ~6 seconds on a 64k blob and for minutes on a ~96 KB one.\n\nEnd-to-end against a live instance (default config):\n1. `docker run ghcr.io/open-webui/open-webui:v0.9.6` on defaults.\n2. Log in as any user (no admin or skill setup).\n3. Send a chat message containing `\u003c$` followed by 50k+ characters with no `\u003e`.\n4. One CPU core pegs in `re`; UI and API stop responding for every user until the worker is killed.\n\n## Patch\nRewrite the optional `|label` as a non-capturing optional group so the two quantifiers no longer overlap. Both patterns become linear; captures and substituted output are unchanged on well-formed `\u003c$id|label\u003e`, `\u003c$id|\u003e`, and bare `\u003c$id\u003e` mentions.\n\n```python\nSKILL_MENTION_RE = re.compile(r\u0027\u003c\\$([^|\u003e]+)(?:\\|[^\u003e]*)?\u003e\u0027)\nstrip_re         = re.compile(r\u0027\u003c\\$[^|\u003e]+(?:\\|([^\u003e]*))?\u003e\u0027)\n```\n\nAfter the patch the same hostile input returns in under 1 ms. Shipped in v0.10.0.\n\n## Credit\nReported by @Vlad-WKG, including a correct root-cause analysis and patch.",
  "id": "GHSA-ffpj-xv5c-p3gw",
  "modified": "2026-07-24T16:55:55Z",
  "published": "2026-07-24T16:55:55Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/open-webui/open-webui/security/advisories/GHSA-ffpj-xv5c-p3gw"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-59220"
    },
    {
      "type": "WEB",
      "url": "https://github.com/open-webui/open-webui/commit/61a26722155ec6ee1b629cf8dfcf975098c18331"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/open-webui/open-webui"
    },
    {
      "type": "WEB",
      "url": "https://github.com/open-webui/open-webui/releases/tag/v0.10.0"
    }
  ],
  "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:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "Open WebUI: ReDoS in skill-mention regexes causes whole-instance DoS on default config"
}



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