CVE-2025-71363
Received Received - Intake

Code Execution via Undetected cProfile.run in Picklescan

Vulnerability report for CVE-2025-71363, including description, CVSS score, EPSS score, affected products, exploitability, helpful resources, and attack-flow context.

Publication date: 2026-06-30

Last updated on: 2026-06-30

Assigner: VulnCheck

Description

picklescan before 0.0.30 fails to detect cProfile.run function calls in pickle reduce methods, allowing attackers to execute arbitrary code. Remote attackers can craft malicious pickle files with cProfile.run payloads that bypass picklescan detection and achieve code execution upon deserialization.

CVSS Scores

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Meta Information

Published
2026-06-30
Last Modified
2026-06-30
Generated
2026-07-01
AI Q&A
2026-07-01
EPSS Evaluated
N/A
NVD
EUVD

Affected Vendors & Products

Showing 1 associated CPE
Vendor Product Version / Range
picklescan picklescan to 0.0.30 (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

This vulnerability exists in picklescan versions before 0.0.30, where the software fails to detect the use of the cProfile.run function within pickle reduce methods.

Because of this failure, attackers can craft malicious pickle files containing cProfile.run payloads that bypass picklescan's detection mechanisms.

When these malicious pickle files are deserialized, they allow remote attackers to execute arbitrary code on the affected system.

Impact Analysis

This vulnerability can have a significant impact as it allows remote attackers to execute arbitrary code on your system without requiring privileges or user interaction beyond deserialization.

Successful exploitation could lead to compromise of confidentiality and integrity of your system, as indicated by the high CVSS scores.

Attackers could potentially run malicious commands or software, leading to unauthorized access or manipulation of data.

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