CVE-2025-71365: Picklescan Remote Code Execution Vulnerability

HIGH
Advisory Identifier: GHSA-3329-ghmp-jmv5
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CVSS 8.1
CWE-502 CWE-94
Published
Advisory Summary

CVE-2025-71365 is a HIGH (CVSS 8.1) remote code execution vulnerability (CWE-502: Deserialization of Untrusted Data) affecting Picklescan libraries in the PyPI ecosystem. The issue involves picklescan is vulnerable to rce through missing detection when calling numpy.f2py.crackfortran.myeval. Remediation is available by upgrading affected packages to version 0.0.33.

CVE-2025-71365 at a Glance

CVE Identifier CVE-2025-71365
GHSA Identifier GHSA-3329-ghmp-jmv5
Severity HIGH
CVSS v3.1 Base Score 8.1
CWE Classification CWE-502: Deserialization of Untrusted Data
Affected Product Picklescan
Package Ecosystem PyPI
Published Date
Last Updated

Security Impact

CVSS: 8.1

The security impact metrics below are parsed directly from the CVSS v3.1 vector string (CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:N).

Attack Vector Network (AV:N)
Attack Complexity Low (AC:L)
Privileges Required None (PR:N)
User Interaction Required (UI:R)
Scope Unchanged (S:U)
Confidentiality High (C:H)
Integrity High (I:H)
Availability None (A:N)

How to Fix CVE-2025-71365

To remediate this vulnerability, upgrade all affected Picklescan dependencies to a patched release. Both direct and transitive dependencies should be checked, as frameworks or security libraries may pull in vulnerable versions transitively.

picklescan fixed: 0.0.33 
pip install picklescan>=0.0.33
Verify Direct and Transitive Dependencies

Run the following command in your project directory to verify that all resolved dependencies use the patched release: 

pip show picklescan

How to Check if You Are Affected

To determine whether your Python environment is affected by CVE-2025-71365, inspect your installed packages using pip:

pip show picklescan

Analyze the terminal output to locate any version of Picklescan in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than 0.0.33), your application is affected.

Note: The pip show picklescan command checks currently installed packages in your active Python environment.

Technical Details

Vulnerability Mechanism & Technical Analysis

This vulnerability is classified under CWE-502: Deserialization of Untrusted Data, where the product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid. In Picklescan, software state validation or input boundaries are circumvented during processing. Review the official source advisory statement below for specific affected components, classes, and reproduction details.

Source Advisory Statement

### Summary Picklescan uses numpy.f2py.crackfortran.myeval, which is a function in numpy to execute remote pickle files. ### Details The attack payload executes in the following steps: - First, the attacker crafts the payload by calling the numpy.f2py.crackfortran.myeval function in its reduce method - Then, when the victim checks whether the pickle file is safe by using the Picklescan library and this library doesn't detect any dangerous functions, they decide to use pickle.load() on this malicious pickle file, thus leading to remote code execution. ### PoC ``` class RCE: def __reduce__(self): from numpy.f2py.crackfortran import myeval return (myeval, ("os.system('ls')",)) ``` ### Impact Any organization or individual relying on picklescan to detect malicious pickle files inside PyTorch models. Attackers can embed malicious code in pickle file that remains undetected but executes when the pickle file is loaded. Attackers can distribute infected pickle files across ML models, APIs, or saved Python objects. ### Report by Pinji Chen (cpj24@mails.tsinghua.edu.cn) from the NISL lab (https://netsec.ccert.edu.cn/about) at Tsinghua University, Guanheng Liu (coolwind326@gmail.com).

CVE-2025-71365 Affected Picklescan Versions

1 component(s)
Fixed Versions:
0.0.33
Product / Package Ecosystem Affected Versions Fixed Version
picklescan
pypi/picklescan
PyPI
< 0.0.33
0.0.33

References

GitHub Advisory / Wiki ADVISORY
https://github.com/mmaitre314/picklescan/security/advisories/GHSA-3329-ghmp-jmv5
NVD — CVE-2025-71365 NVD
https://nvd.nist.gov/vuln/detail/CVE-2025-71365
Picklescan Source Repository REPOSITORY
https://github.com/mmaitre314/picklescan/pull/53
Security Fix Commit FIX COMMIT
https://github.com/mmaitre314/picklescan/commit/70c1c6c31beb6baaf52c8db1b6c3c0e84a6f9dab
Picklescan Source Repository REPOSITORY
https://github.com/mmaitre314/picklescan
www.vulncheck.com/advisories/picklesc... WEB
https://www.vulncheck.com/advisories/picklescan-arbitrary-code-execution-via-numpy-f2py-crackfortran-myeval-detection-bypass

Frequently Asked Questions

What is CVE-2025-71365?
CVE-2025-71365 is a security vulnerability in Picklescan involving Picklescan is vulnerable to RCE through missing detection when calling numpy.f2py.crackfortran.myeval under CWE-502: Deserialization of Untrusted Data.
Which Picklescan versions are affected?
Affected versions include releases prior to 0.0.33 across affected packages: picklescan.
What version fixes CVE-2025-71365?
Upgrading to 0.0.33 (or the latest patched release for your respective branch) resolves the vulnerability.
Is picklescan affected?
Yes, picklescan is affected in releases prior to 0.0.33. Upgrade your dependency to 0.0.33 or later.
What is the CVSS score of CVE-2025-71365?
CVE-2025-71365 has a CVSS v3.1 base score of 8.1 (HIGH) with vector string CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:N.
What CWE is associated with CVE-2025-71365?
CVE-2025-71365 is classified under CWE-502: Deserialization of Untrusted Data (The product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid.).
How can I check PyPI dependencies for CVE-2025-71365?
Run the dependency tree command: 'pip show picklescan'. This command lists direct and transitive dependencies in your build configuration so you can verify if a vulnerable version is resolved.
Machine-readable OSV JSON OSV v1.5 Schema
Normalized schema output
View Raw JSON 
{
  "schema_version" : "1.4.0",
  "id" : "GHSA-3329-ghmp-jmv5",
  "modified" : "2026-09-23T18:15:41Z",
  "published" : "2025-12-29T20:04:09Z",
  "aliases" : [ "CVE-2025-71365" ],
  "summary" : "Picklescan is vulnerable to RCE through missing detection when calling numpy.f2py.crackfortran.myeval",
  "details" : "### Summary\nPicklescan uses numpy.f2py.crackfortran.myeval, which is a function in numpy to execute remote pickle files.\n\n### Details\nThe attack payload executes in the following steps:\n\n- First, the attacker crafts the payload by calling the numpy.f2py.crackfortran.myeval function in its reduce method\n- Then, when the victim checks whether the pickle file is safe by using the Picklescan library and this library doesn't detect any dangerous functions, they decide to use pickle.load() on this malicious pickle file, thus leading to remote code execution.\n\n### PoC\n```\nclass RCE:\n    def __reduce__(self):\n        from numpy.f2py.crackfortran import myeval\n        return (myeval, (\"os.system('ls')\",))\n```\n\n\n### Impact\nAny organization or individual relying on picklescan to detect malicious pickle files inside PyTorch models.\nAttackers can embed malicious code in pickle file that remains undetected but executes when the pickle file is loaded.\nAttackers can distribute infected pickle files across ML models, APIs, or saved Python objects.\n\n### Report by\nPinji Chen (cpj24@mails.tsinghua.edu.cn) from the NISL lab (https://netsec.ccert.edu.cn/about) at Tsinghua University, Guanheng Liu (coolwind326@gmail.com).",
  "severity" : [ {
    "type" : "CVSS_V3",
    "score" : "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:N"
  }, {
    "type" : "CVSS_V4",
    "score" : "CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:P/VC:H/VI:H/VA:N/SC:N/SI:N/SA:N"
  } ],
  "affected" : [ {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "picklescan"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "0"
      }, {
        "fixed" : "0.0.33"
      } ]
    } ]
  } ],
  "references" : [ {
    "type" : "WEB",
    "url" : "https://github.com/mmaitre314/picklescan/security/advisories/GHSA-3329-ghmp-jmv5"
  }, {
    "type" : "ADVISORY",
    "url" : "https://nvd.nist.gov/vuln/detail/CVE-2025-71365"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/mmaitre314/picklescan/pull/53"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/mmaitre314/picklescan/commit/70c1c6c31beb6baaf52c8db1b6c3c0e84a6f9dab"
  }, {
    "type" : "PACKAGE",
    "url" : "https://github.com/mmaitre314/picklescan"
  }, {
    "type" : "WEB",
    "url" : "https://www.vulncheck.com/advisories/picklescan-arbitrary-code-execution-via-numpy-f2py-crackfortran-myeval-detection-bypass"
  } ],
  "database_specific" : {
    "cwe_ids" : [ "CWE-502", "CWE-94" ],
    "severity" : "HIGH",
    "github_reviewed" : true,
    "github_reviewed_at" : "2025-12-29T20:04:09Z",
    "nvd_published_at" : null
  }
}