Deserialization of Untrusted DataWeakness · CWE-502

CVE-2024-0140

MEDIUM · 6.8 CVSS v3.1 Published 2025-01-28
Mitigation only
No fix yet — a mitigation exists. There is no fixed release. A documented workaround reduces exposure in the meantime.
See remediation →
68/100
Remediation priority · Elevated

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
NVIDIA RAPIDS contains a vulnerability in cuDF and cuML, where a user could cause a deserialization of untrusted data issue. A successful exploit of this vulnerability might lead to code execution, data tampering, denial of service, and information disclosure.

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

NVIDIA RAPIDS cuDF and cuML libraries contain a deserialization vulnerability where processing untrusted data can lead to arbitrary code execution, data tampering, denial of service, or information disclosure. This class of flaw typically stems from unsafe object deserialization without proper validation, allowing attackers to manipulate the deserialization process.

MitigationImplement input validation and use safe deserialization patterns; consult NVIDIA's security advisories for specific patched versions of cuDF and cuML, and upgrade to the latest secure release.

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
Low
User interaction
Required
Scope
Unchanged
Confidentiality
Low
Integrity
High
Availability
High

CVSS:3.1/AV:L/AC:L/PR:L/UI:R/S:U/C:L/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 cuDF is installed
    Run 'pip list' or 'conda list' and look for 'cudf' in the output, or import in Python with 'import cudf; print(cudf.__version__)'
    Affected if cuDF is installed and the version is lower than the patched release mentioned in NVIDIA's security advisory for CVE-2024-0140
  2. Identify if cuML is installed
    Run 'pip list' or 'conda list' and look for 'cuml' in the output, or import in Python with 'import cuml; print(cuml.__version__)'
    Affected if cuML is installed and the version is lower than the patched release mentioned in NVIDIA's security advisory for CVE-2024-0140
  3. Verify if untrusted data deserialization is occurring
    Search codebases for usage of pickle, joblib, or similar deserialization functions on data from untrusted sources, especially involving cuDF DataFrames or cuML models
    Affected if Code processes untrusted serialized data through cuDF or cuML without validation
  4. Check for exposed API endpoints or services processing external input
    Audit any APIs, web services, or data pipelines that accept external serialized objects and pass them to cuDF or cuML functions
    Affected if External untrusted input is directly deserialized and processed by RAPIDS libraries

Environment is affected if either cuDF or cuML is installed with a version below the patched release AND the system processes untrusted serialized data through these libraries.

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

Implement input validation and use safe deserialization patterns; consult NVIDIA's security advisories for specific patched versions of cuDF and cuML, and upgrade to the latest secure release.

Have this fixed Scoped from the published advisory
  • Consultation8.0 h
  • Implementation16.0 h
  • Testing12.0 h
  • Review / QA6.0 h
42.0 hours of engineering $7,360
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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-2024-0140 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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