Deserialization of Untrusted DataWeakness · CWE-502

CVE-2025-14925

HIGH · 7.8 CVSS v3.0 Published 2025-12-23
Mitigation only
No fix yet — a mitigation exists. There is no fixed release. A documented workaround reduces exposure in the meantime.
See remediation →
81/100
Remediation priority · High
No privileges

Official description Straight from the sourceThe vendor's or NVD's own wording, published unedited. Authoritative, but often terse — it says what broke, rarely what to do.

NVD · unedited
Hugging Face Accelerate Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Hugging Face Accelerate. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the parsing of checkpoints. The issue results from the lack of proper validation of user-supplied data, which can result in deserialization of untrusted data. An attacker can leverage this vulnerability to execute code in the context of the current process. Was ZDI-CAN-27985.

Technical summary Written by usOur analysis, written from the advisory, the CVSS vector and the affected-version data. It adds context the advisory leaves out, and never invents facts that are not in the source.

dbcve analysis · moderate confidence

Hugging Face Accelerate contains a deserialization vulnerability in its checkpoint parsing logic. The library fails to properly validate user-supplied data during checkpoint loading, allowing attackers to craft malicious checkpoint files that execute arbitrary code when opened by victims.

MitigationUsers should avoid loading checkpoints from untrusted sources. The library maintainers should implement strict input validation and safe deserialization practices for checkpoint files.

Verify against the referenced sources before acting — the references below are authoritative for this CVE, this summary is not.

CVSS breakdown How the score is builtThe industry scoring standard. It rates how the flaw is reached, what it takes to exploit, and what an attacker gains — the score is derived from those, not the other way round.

From the vector
Attack vector
Local
Complexity
Low
Privileges
None
User interaction
Required
Scope
Unchanged
Confidentiality
High
Integrity
High
Availability
High

CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H

Am I affected? How to checkSteps we derive from the advisory and the affected-version data, so you can decide whether this CVE reaches your setup. They are a guide, not a scan — your own configuration is the authority.

dbcve checks

Work through these to decide whether this CVE applies to you.

  1. Identify if Accelerate is installed
    Run 'pip show accelerate' or 'pip list | grep -i accelerate' to check if the library is present in your environment
    Affected if Accelerate is not installed, the vulnerability does not apply to your environment
  2. Determine installed Accelerate version
    Run 'pip show accelerate' and note the Version field, then compare it against the affected version range for this CVE
    Affected if The installed version falls within the vulnerable version range and you load checkpoint files
  3. Check for checkpoint loading code
    Search your codebase for calls to 'from_pretrained', 'load_checkpoint', or similar Accelerate checkpoint loading functions using grep or IDE search
    Affected if Your code loads checkpoint files using Accelerate functions, exposing you to the vulnerable code path
  4. Audit checkpoint file sources
    Review your data pipelines and code to identify where checkpoint files originate (local storage, untrusted URLs, user uploads, shared repositories)
    Affected if You load checkpoints from untrusted or third-party sources without validation
  5. Inspect custom checkpoint deserialization
    Review any custom implementation that parses Accelerate checkpoint files directly, looking for unpickling or unsafe deserialization of checkpoint data
    Affected if Custom code performs unsafe deserialization on checkpoint data without validation

You are affected if Hugging Face Accelerate is installed at a vulnerable version AND your environment loads checkpoint files, particularly from untrusted or third-party sources.

Generated from the published advisory. Verify against your own configuration.

Check your environment

Paste your version and any relevant configuration and it will be compared against the affected criteria above. Do not include secrets or credentials.

AI-assisted, checked against the advisory. Informational, not a guarantee.

Remediation Closing itWhat it takes to close this. Where a vendor fix exists we point at it; where none exists we say so plainly, and can build one. Effort estimates are scoped from the advisory, not from your codebase.

From vendor data
Mitigation available No clean upgrade yet — mitigate in the meantime
Mitigation

Users should avoid loading checkpoints from untrusted sources. The library maintainers should implement strict input validation and safe deserialization practices for checkpoint files.

Have this fixed Scoped from the published advisory
  • Consultation4.0 h
  • Implementation8.0 h
  • Testing8.0 h
  • Review / QA4.0 h
24.0 hours of engineering $4,160
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References Go to the primary sourcePrimary sources — vendor advisories, patches and trackers. Where our summary and a reference disagree, the reference wins.

Primary sources

Practitioner notes

Contributed

Peer-ranked notes from engineers who’ve handled CVE-2025-14925 in production — separate from our analysis above.

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What this is

A place for practitioners to share what actually worked: a mitigation you’ve tested, a configuration change, a version- or environment-specific caveat, or a link to a verified patch. The most useful notes rise to the top as peers upvote them, so the signal stays high.

What belongs here
  • Verified mitigations, workarounds, and config changes
  • Version or environment caveats, and links to real fixes
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