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CVE-2024-39705VulnerabilityPublished Updated

CVE-2024-39705: nltk · n/a

Affects nltkSource CVE Database V5

0

Not known to be exploited · CVSS 9.8 Critical.

Data as of 25 Oct 2026, 19:02 UTC

CVSS 3.1 base score
9.8Critical
How severe the flaw is on the 0–10 CVSS scale.
EPSS
1.3% chance of exploitation in 30 days – higher than 71% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 27 Jun 2024

  2. Detectable: no evidence on record.

    No public nuclei template indexed

  3. Weaponised: no evidence on record.

    No public exploit code indexed in Metasploit or Exploit-DB

  4. Exploited in the wild: no evidence on record.

    Not in CISA KEV and no source reports exploitation

  5. Observed by OffSeq Mirage: no evidence on record.

    No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 2026-10-25.

What to do

Affected software

ProductAffectedFixed in
PyPInltkpkg:pypi/nltkOther threatsAffected
  • <=3.8.1
Fixed in–

Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.

AI-suggested

To mitigate CVE-2024-39705, organizations should immediately audit their use of NLTK, particularly any automated processes that download or load external data packages. Avoid using untrusted or unauthenticated data sources for NLTK package downloads. Where possible, disable or restrict the integrated data package download functionality. Implement strict input validation and sandboxing for any deserialization operations. Monitor network traffic and logs for unusual activity related to NLTK data downloads. Apply principle of least privilege to systems running NLTK to limit potential damage from exploitation. Stay alert for official patches or updates from NLTK maintainers and apply them promptly once available. Consider using alternative NLP libraries or manually vetting and verifying all data packages before loading. Employ runtime application self-protection (RASP) or endpoint detection and response (EDR) solutions to detect anomalous behavior indicative of exploitation attempts.

Description

NLTK through 3.8.1 allows remote code execution if untrusted packages have pickled Python code, and the integrated data package download functionality is used. This affects, for example, averaged_perceptron_tagger and punkt.

References

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