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Picklescan: ZIP archive scan bypass is possible through non-exhaustive Cyclic Redundancy Check

Critical severity GitHub Reviewed Published Sep 8, 2025 in mmaitre314/picklescan • Updated Sep 18, 2025

Package

pip picklescan (pip)

Affected versions

<= 0.0.30

Patched versions

0.0.31

Description

Summary

Picklescan's ability to scan ZIP archives for malicious pickle files is compromised when the archive contains a file with a bad Cyclic Redundancy Check (CRC). Instead of attempting to scan the files within the archive, whatever the CRC is, Picklescan fails in error and returns no results. This allows attackers to potentially hide malicious pickle payloads within ZIP archives that PyTorch might still be able to load (as PyTorch often disables CRC checks).

Details

Picklescan likely utilizes Python's built-in zipfile module to handle ZIP archives. When zipfile encounters a file within an archive that has a mismatch between the declared CRC and the calculated CRC, it can raise an exception (e.g., BadZipFile or a related error). It appears that Picklescan does not try to scan the files whatever the CRC is.
This behavior contrasts with PyTorch's model loading capabilities, which in many cases might bypass CRC checks for ZIP archives - whatever the configuration is. This discrepancy creates a blind spot where a malicious model packaged in a ZIP with a bad CRC could be loaded by PyTorch while being completely missed by Picklescan.

PoC

  1. Download an existing Pytorch model with a bad CRC

wget <https://huggingface.co/jinaai/jina-embeddings-v2-base-en/resolve/main/pytorch_model.bin?download=true> -O pytorch_model.bin

  1. Attempt to scan the corrupted ZIP file with PickleScan:
# Assuming you have Picklescan installed and in your PATH
picklescan -p pytorch_model.bin

Screenshot 2025-06-29 at 13 52 07
Observed Result: Picklescan returns no results and presents an error message indicating a problem with the ZIP file, but it doesn’t attempt to scan any potentially valid pickle files within the archive.

Expected Result: Picklescan should either:

  • Attempt to extract and scan other valid files within the ZIP archive, even if some have CRC errors.
  • Report a warning indicating that the ZIP archive has CRC errors and might be incomplete or corrupted, but still attempt to scan any accessible content.

Impact

Severity: High
Affected Users: Any organization or individual using Picklescan to analyze PyTorch models or other files distributed as ZIP archives for malicious pickle content.
Impact Details: Attackers can craft malicious PyTorch models containing embedded pickle payloads, package them into ZIP archives, and intentionally introduce CRC errors. This would cause Picklescan to fail to analyze the archive, while PyTorch is still able to load the model (depending on its configuration regarding CRC checks). This creates a significant vulnerability where malicious code can be distributed and potentially executed without detection by Picklescan.
Ex: Picklescan on HuggingFace goes into error (https://huggingface.co/jinaai/jina-embeddings-v2-base-en/tree/main)
Screenshot 2025-06-29 at 13 55 58

Recommendations:
Picklescan should not fail on Bad CRC check, especially if Pytorch is not checking CRC.
Relaxed Zipfile is perfect to fix this issue:

--- picklescan/src/picklescan/relaxed_zipfile.py
+++ picklescan/src/picklescan/relaxed_zipfile.py
@@ class RelaxedZipFile(zipfile.ZipFile):
         try:
             # Skip the file header:
             fheader = zef_file.read(sizeFileHeader)
             if len(fheader) != sizeFileHeader:
                 raise zipfile.BadZipFile("Truncated file header")

             fheader = struct.unpack(structFileHeader, fheader)
             if fheader[_FH_SIGNATURE] != stringFileHeader:
                 raise zipfile.BadZipFile("Bad magic number for file header")

             zef_file.read(fheader[_FH_FILENAME_LENGTH])
             if fheader[_FH_EXTRA_FIELD_LENGTH]:
                 zef_file.read(fheader[_FH_EXTRA_FIELD_LENGTH])

-            return zipfile.ZipExtFile(zef_file, mode, zinfo, pwd, True)
+
+            # Create the ZipExtFile and disable CRC check
+            ext_file = zipfile.ZipExtFile(zef_file, mode, zinfo, pwd)
+            # Monkey-patch to skip CRC validation
+            ext_file._expected_crc = None
+            return ext_file

         except BaseException:
             zef_file.close()
             raise

References

@mmaitre314 mmaitre314 published to mmaitre314/picklescan Sep 8, 2025
Published to the GitHub Advisory Database Sep 10, 2025
Reviewed Sep 10, 2025
Last updated Sep 18, 2025

Severity

Critical

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

EPSS score

Exploit Prediction Scoring System (EPSS)

This score estimates the probability of this vulnerability being exploited within the next 30 days. Data provided by FIRST.
(39th percentile)

Weaknesses

Protection Mechanism Failure

The product does not use or incorrectly uses a protection mechanism that provides sufficient defense against directed attacks against the product. Learn more on MITRE.

Improper Handling of Exceptional Conditions

The product does not handle or incorrectly handles an exceptional condition. Learn more on MITRE.

CVE ID

CVE-2025-10156

GHSA ID

GHSA-mjqp-26hc-grxg

Source code

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