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CVE-2026-57845VulnerabilityPublished Updated

Hugging Face Datasets through 5.1.0 contains an insecure deserialization vulnerability that allows attackers to

Source GCVE Database

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Authoritative record:CVE-2026-57845· High 8.7

Not known to be exploited · CVSS 8.7 High.

Data as of 12 Nov 2026, 22:36 UTC

CVSS 4.0 base score
8.7High
How severe the flaw is on the 0–10 CVSS scale.

Thin evidence

One scorer or none
CVSS scores by source
CNA (VulnCheck)CVSS 4.08.7
CNA (VulnCheck)CVSS 3.18.8
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 23 Oct 2026

  2. Detectable: no evidence on record.

    No public nuclei template indexed

  3. Weaponized: 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 12 Nov 2026.

What to do

Affected software

ProductAffectedFixed in
huggingfacedatasetsAffected
  • <=5.1.0
Fixed in–
GitHubdatasetspkg:github/datasetsOther threatsAffected
  • <=5.1.0
Fixed in–

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

AI-suggested

Users should avoid loading datasets using the deprecated pandas packaged builder with untrusted pickle files. Until a fix is released, do not load pickle-backed datasets from untrusted sources via datasets.load_dataset("pandas", data_files=...). Monitor the vendor advisory for updates and apply official patches once available.

Description

Hugging Face Datasets versions through 5.1.0 contain an insecure deserialization vulnerability that allows attackers to execute arbitrary Python code. This occurs when a malicious pickle file is loaded via the deprecated pandas packaged builder, specifically through pandas.read_pickle() without validation. Exploitation requires a victim to load a crafted dataset using datasets.load_dataset("pandas", data_files=...), which triggers execution of the embedded payload with the victim process's privileges.

References

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