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Picklescan missing detection when calling numpy.f2py.crackfortran.getlincoefGHSA-r8g5-cgf2-4m4m

Fix: mmaitre314/picklescan#53

GHSA-r8g5-cgf2-4m4m is a Deserialization of Untrusted Data vulnerability in picklescan. A fix is available for picklescan — see the affected versions and patch details below.

Also known asCVE-2025-71362
Published
Updated
Affected
1 pkg
Patched
1 / 1
Exploits
None indexed
Exploitation data as of Oct 30, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

Proof-of-concept exploit code exists

  • CISA’s SSVC triage found public proof-of-concept exploit code for this CVE, though no confirmed active exploitation.
  • A successful exploit gives an attacker total control of the affected component, not partial access.

Exploitation and automatability from CISA’s SSVC triage for GHSA-r8g5-cgf2-4m4m.

EPSS Exploitation Probability

via FIRST.org ↗
0.4%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs37th percentile — riskier than 37% of all scored CVEsHighest risk
0.00%0.31%0.62%0.93%0.3%0.4%0.4%0.4%Aug 26Oct 26Oct 26

Probability of exploitation in the next 30 days, from FIRST.org EPSS.

Real-World Exposure

1 pkg affected
🐍picklescan

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.

Description

Summary

An unsafe deserialization vulnerability allows an attacker to execute arbitrary code on the host when loading a malicious pickle payload from an untrusted source.

Details

The numpy.f2py.crackfortran module exposes many functions that call eval on arbitrary strings of values. This is the case for getlincoef and _eval_length. This list is probably not exhaustive.

According to https://numpy.org/doc/stable/reference/security.html#advice-for-using-numpy-on-untrusted-data, the whole numpy.f2py should be considered unsafe when loading a pickle.

PoC

from numpy.f2py.crackfortran import getlincoef

class EvilClass:
    def __reduce__(self):
        payload = "__import__('os').system('echo \"successful attack\"')"
        return getlincoef, (payload, [])

Impact

Who is impacted? Any organization or individual relying on picklescan to detect malicious pickle files from untrusted sources. What is the impact? Attackers can embed malicious code in pickle file that remains undetected but executes when the pickle file is loaded. Supply Chain Attack: Attackers can distribute infected pickle files across ML models, APIs, or saved Python objects.

Note

The problem was originally reported to the joblib project, but this was deemed unrelated to joblib itself. However, I checked that picklescan was indeed vulnerable.

Affected Packages

1 total 1 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPIpicklescanall versions0.0.33pip install --upgrade 'picklescan==0.0.33'

Detection & mitigation playbook

Open-source dependency
  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for picklescan, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

  2. Fix

    Update picklescan to 0.0.33 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-r8g5-cgf2-4m4m is resolved across your whole dependency graph.

  3. Workarounds

    Do not deserialise data from untrusted sources: where the format allows it, restrict deserialisation to an explicit allowlist of expected types, and prefer a data-only format (JSON, Protobuf) over one that can reconstruct arbitrary objects until you can upgrade.

Frequently Asked Questions

### Summary An unsafe deserialization vulnerability allows an attacker to execute arbitrary code on the host when loading a malicious pickle payload from an untrusted source. ### Details The `numpy.f2py.crackfortran` module exposes many functions that call `eval` on arbitrary strings of values. This is the case for `getlincoef` and `_eval_length`. This list is probably not exhaustive. According to https://numpy.org/doc/stable/reference/security.html#advice-for-using-numpy-on-untrusted-data, the whole `numpy.f2py` should be considered unsafe when loading a pickle. ### PoC ```python from n
O3 Security · Impact-Aware SCA

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