Deserialization of Untrusted DataWeakness · CWE-502

CVE-2025-71372

HIGH · 8.1 CVSS v3.1 Published 2026-07-04
Mitigation only
No fix yet — a mitigation exists. There is no fixed release. A documented workaround reduces exposure in the meantime.
See remediation →
88/100
Remediation priority · High
Remotely reachable No privileges 7 weeks old

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
Picklescan before 0.0.33 fails to detect the numpy.f2py.crackfortran.getlincoef gadget in pickle __reduce__ methods, allowing arbitrary code execution. Attackers can craft malicious pickle files that execute arbitrary Python code when loaded, bypassing Picklescan's safety checks and enabling supply-chain poisoning of shared model files.

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 · high confidence

Picklescan before 0.0.33 fails to detect the numpy.f2py.crackfortran.getlincoef gadget in pickle __reduce__ methods, enabling attackers to craft malicious pickle files that execute arbitrary Python code when loaded. This bypasses Picklescan's safety checks and enables supply-chain poisoning of shared model files.

MitigationUpdate Picklescan to version 0.0.33 or later to include detection of the numpy.f2py.crackfortran.getlincoef gadget. Re-scan any previously validated pickle files to ensure they were not crafted using this bypass technique.

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
Network
Complexity
Low
Privileges
None
User interaction
Required
Scope
Unchanged
Confidentiality
High
Integrity
High
Availability
None

CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:N

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. Check installed Picklescan version
    Run 'pip show picklescan' or 'pip list | grep -i picklescan' to display the installed version
    Affected if The version displayed is lower than 0.0.33 (e.g., 0.0.32, 0.0.31, etc.)
  2. Verify numpy availability for gadget usage
    Run 'python -c "import numpy; print(numpy.__version__)"' to confirm numpy is installed
    Affected if numpy is installed, meaning the numpy.f2py.crackfortran.getlincoef gadget could theoretically be used in malicious pickles against this installation
  3. Test Picklescan detection capability
    Create a minimal pickle file containing numpy.f2py.crackfortran.getlincoef in the __reduce__ method, then scan it with picklescan to see if it is flagged as malicious
    Affected if Picklescan reports the file as safe or fails to detect the gadget, indicating the bypass is present
  4. Check for recent Picklescan updates
    Run 'pip index versions picklescan' to see available versions and compare to your installed version
    Affected if A version 0.0.33 or later is available but you have not upgraded
  5. Review previously scanned pickle files
    Re-examine any pickle files that were previously validated by Picklescan versions before 0.0.33 using the updated scanner
    Affected if Files previously marked as safe are now flagged, indicating they may have used the bypass gadget

You are affected if Picklescan version is below 0.0.33 and you rely on it to validate pickle files that could contain the numpy.f2py.crackfortran.getlincoef gadget.

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.

dbcve · scoped
Mitigation available No clean upgrade yet — mitigate in the meantime
Mitigation

Update Picklescan to version 0.0.33 or later to include detection of the numpy.f2py.crackfortran.getlincoef gadget. Re-scan any previously validated pickle files to ensure they were not crafted using this bypass technique.

Recommended fix High confidence

0.0.33 or later

  1. Check the current installed version of picklescan using: pip show picklescan or picklescan --version
  2. Upgrade to version 0.0.33 or later using: pip install picklescan>=0.0.33
  3. Verify the upgrade was successful by running: pip show picklescan to confirm the installed version is 0.0.33 or higher

Generated from the published advisory — verify against the referenced sources before acting.

Have this fixed Scoped from the published advisory
  • Consultation2.0 h
  • Implementation1.0 h
  • Testing3.0 h
  • Review / QA1.0 h
7.0 hours of engineering $1,210
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Scan for this in your stack

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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-2025-71372 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
  • No weaponised exploit code, or anything meant to cause harm
  • No spam, self-promotion, credentials, or personal data