CVE-2026-65010
Received Received - Intake

Symlink Following in Datasets Archive Extractor

Vulnerability report for CVE-2026-65010, including description, CVSS score, EPSS score, affected products, exploitability, helpful resources, and attack-flow context.

Publication date: 2026-07-23

Last updated on: 2026-07-23

Assigner: VulnCheck

Description

Datasets through 5.00, fixed in commit ad2d853, contains a symlink-following vulnerability in Extractor.extract() that allows local attackers to write arbitrary files by pre-planting symlinks at predictable output paths. Attackers can redirect archive extraction to arbitrary filesystem locations in shared-cache environments, enabling overwrite of sensitive files and potential privilege escalation or code execution.

CVSS Scores

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Meta Information

Published
2026-07-23
Last Modified
2026-07-23
Generated
2026-07-24
AI Q&A
2026-07-23
EPSS Evaluated
N/A
NVD
EUVD

Affected Vendors & Products

Showing 2 associated CPEs
Vendor Product Version / Range
huggingface datasets 5.0.0
huggingface datasets to 5.0.0 (exc)

Helpful Resources

Exploitability

CWE
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KEV
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CWE ID Description
CWE-61 The product, when opening a file or directory, does not sufficiently account for when the file is a symbolic link that resolves to a target outside of the intended control sphere. This could allow an attacker to cause the product to operate on unauthorized files.

Attack-Flow Graph

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Executive Summary

This vulnerability is a symlink-following issue in the Hugging Face datasets library (versions 5.00 and earlier). It occurs in the Extractor.extract() function during archive extraction. An attacker with write access to a shared cache directory can pre-plant a symlink at a predictable output path. When extraction runs, the symlink is followed, causing files to be written to an arbitrary target directory instead of the intended location. This enables overwriting sensitive files, privilege escalation, or code execution.

Detection Guidance

To detect this vulnerability, inspect the Hugging Face datasets library version. Run: pip show datasets. If version is 5.00 or earlier, the system is vulnerable. Check for unexpected symlinks in the cache directory, typically ~/.cache/huggingface/datasets. Use: ls -la ~/.cache/huggingface/datasets. Look for symlinks pointing to sensitive paths.

Monitor file writes during extraction. Use strace to trace system calls: strace -f -e trace=file python your_script.py 2>&1 | grep -i symlink. Check for arbitrary file writes in shared directories.

Impact Analysis

If you use the Hugging Face datasets library in a shared environment (e.g., CI runners, multi-user servers, Docker volumes), an attacker could overwrite sensitive files, escalate privileges, or execute arbitrary code with your privileges. This happens because the library fails to properly handle symlinks during extraction, allowing redirection to unintended filesystem locations.

Compliance Impact

This vulnerability could lead to unauthorized file access or modification, violating data integrity and confidentiality requirements in GDPR and HIPAA. For example, overwriting sensitive files (e.g., configuration, logs, or databases) may result in non-compliance with access control and audit requirements. The risk is higher in shared environments where multiple users or processes interact with the same cache directory.

Mitigation Strategies

Upgrade the Hugging Face datasets library to a version beyond 5.00, specifically commit ad2d853 or later. Run: pip install --upgrade datasets. This patch removes the symlink-following vulnerability by checking and removing symlinks before extraction.

Restrict write access to the Hugging Face cache directory. Ensure only authorized users can write to ~/.cache/huggingface/datasets. Set permissions to 750 or stricter. Remove any existing symlinks in the cache directory to prevent exploitation.

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