HighVulnerability

CVE-2026-59974: Stanza archive extraction path traversal in unzip during model download

Source: NVD(opens in a new tab)
Identifier: CVE-2026-59974
Published: September 16, 2026
Record updated: October 9, 2026

Known exploitation: Not listed in the CISA Known Exploited Vulnerabilities catalog at the last check.
EPSS: 0.4%

Summary

Stanza, a Stanford NLP Python library, prior to 1.14.0 extracts downloaded model and resource archives in stanza/resources/common.py via zipfile.ZipFile.extractall without validating member paths. Archives reached through stanza.download and stanza.install_corenlp containing parent-directory traversal entries can write outside the model directory, overwriting files writable by the Stanza process and potentially enabling code execution through shell configuration, SSH authorization data, Python packages, or executable scripts.

Mitigation

Fixed in version 1.14.0.

Details

Scores and exploitation

CVSS score: 7.8(high)
CVSS vector: CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
Attack vector: local
Attack complexity: low
Privileges required: none
User interaction: required
EPSS: 0.4%Estimated probability that this CVE is exploited in the next 30 days, from the FIRST Exploit Prediction Scoring System. Read on November 4, 2026.
Disclosure date: September 16, 2026

Weaknesses and techniques

Weakness (CWE): CWE-22
Attack pattern (CAPEC): CAPEC-126
AI threat technique (MITRE ATLAS): AML.T0010

Classification

Attack type: Supply chain
Attack sophistication: Moderate
AI component targeted: Framework
Impact: Confidentiality,
Integrity,
Safety
Labels: security,
industry

How this record was produced

Summaries, mitigations and labels on this page are generated automatically from the source. The linked source is authoritative. The source gives this advisory a description and no title, so the title above is a headline generated from the source text.

Original source: https://nvd.nist.gov/vuln/detail/CVE-2026-59974

First tracked: September 16, 2026 at 02:08 PM ET, from NVD/CVE Database

Classifier: claude-haiku-5-5, prompt v4

Classifier confidence: 85% (self-assessed)

Summary

Mitigation

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