CVE-2025-71360
Received Received - Intake

Pickle Deserialization RCE in PickleScan

Vulnerability report for CVE-2025-71360, including description, CVSS score, EPSS score, affected products, exploitability, helpful resources, and attack-flow context.

Publication date: 2026-07-04

Last updated on: 2026-07-04

Assigner: VulnCheck

Description

picklescan before 0.0.29 fails to detect malicious pickle files using idlelib.calltip.get_entity function in reduce methods. Attackers can embed undetected code in pickle files that executes remote commands when loaded by victims.

CVSS Scores

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Meta Information

Published
2026-07-04
Last Modified
2026-07-04
Generated
2026-07-04
AI Q&A
2026-07-04
EPSS Evaluated
N/A
NVD
EUVD

Affected Vendors & Products

Showing 1 associated CPE
Vendor Product Version / Range
mmaitre314 picklescan to 0.0.29 (exc)

Helpful Resources

Exploitability

CWE
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KEV
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CWE ID Description
CWE-502 The product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid.

Attack-Flow Graph

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Executive Summary

CVE-2025-71360 is a vulnerability in the picklescan library versions before 0.0.29 where the library fails to detect malicious pickle files that use the Python function idlelib.calltip.get_entity within reduce methods.

Attackers can craft pickle files embedding code that executes remote commands when loaded by victims because picklescan's safety checks do not detect this threat.

This allows remote code execution when the victim loads the malicious pickle file, potentially leading to unauthorized actions on the victim's system.

Impact Analysis

This vulnerability can lead to remote code execution on systems that use picklescan to verify pickle files before loading them.

Attackers can exploit this flaw to run arbitrary commands remotely by embedding malicious payloads in pickle files that bypass detection.

This poses a significant risk especially for organizations relying on picklescan to secure PyTorch models or other pickle-based files, as it enables supply chain attacks where malicious code spreads through infected models or objects.

Detection Guidance

This vulnerability involves picklescan versions before 0.0.29 failing to detect malicious pickle files that use the idlelib.calltip.get_entity function within reduce methods. Detection involves verifying the version of picklescan in use and ensuring it is updated to 0.0.29 or later, which includes the patch for this issue.

Since the vulnerability is related to the failure of picklescan to detect malicious pickle files, a practical detection step is to check pickle files for suspicious use of idlelib.calltip.get_entity in reduce methods before loading them.

Suggested commands include:

  • Check the installed picklescan version: `pip show picklescan`
  • Update picklescan to the patched version: `pip install --upgrade picklescan`
  • Manually inspect pickle files for suspicious reduce methods calling idlelib.calltip.get_entity using Python scripts or tools that parse pickle files.
Mitigation Strategies

The immediate mitigation step is to upgrade picklescan to version 0.0.29 or later, where the vulnerability has been patched.

Additionally, avoid loading pickle files from untrusted or unauthenticated sources, as malicious pickle files can execute remote code when loaded.

Implement strict validation and scanning of pickle files before loading them, and consider alternative safer serialization formats if possible.

Compliance Impact

The vulnerability allows attackers to execute remote code by embedding malicious payloads in pickle files that bypass picklescan detection. This can lead to unauthorized code execution and potential compromise of systems processing these files.

Such unauthorized remote code execution risks could impact compliance with standards and regulations like GDPR and HIPAA, which require protection of sensitive data and secure processing environments. If exploited, this vulnerability could lead to data breaches or unauthorized access, thereby violating these regulations.

However, the provided information does not explicitly mention compliance impacts or specific regulatory considerations.

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