CVE-2025-1889 in picklescan
Summary
by MITRE • 03/03/2025
picklescan before 0.0.22 only considers standard pickle file extensions in the scope for its vulnerability scan. An attacker could craft a malicious model that uses Pickle and include a malicious pickle file with a non-standard file extension. Because the malicious pickle file inclusion is not considered as part of the scope of picklescan, the file would pass security checks and appear to be safe, when it could instead prove to be problematic.
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Analysis
by VulDB Data Team • 12/29/2025
The vulnerability identified in picklescan version 0.0.22 and earlier represents a significant security flaw in Python pickle file analysis tools that operates under the principle of file extension validation. This issue stems from the tool's restrictive approach to identifying pickle files, which relies exclusively on standard file extensions such as .pkl, .pickle, and .pkl.gz. The vulnerability creates a false sense of security by allowing malicious actors to bypass detection mechanisms through the use of non-standard file extensions, effectively circumventing the intended security controls. The root cause of this weakness lies in the tool's failure to implement comprehensive file type detection beyond simple extension matching, which is a common pattern observed in many static analysis tools that prioritize ease of implementation over robust security coverage.
This vulnerability directly maps to CWE-471, which addresses the issue of "Use of Non-Standard Functionality in a Context Where Standard Functionality is Expected," and potentially relates to CWE-20, "Improper Input Validation," as the tool fails to properly validate the actual content of files rather than relying solely on superficial attributes. The operational impact of this vulnerability is particularly concerning in environments where automated security scanning is employed as part of continuous integration pipelines or security monitoring systems. Attackers can exploit this weakness by creating malicious pickle files with unconventional extensions such as .model, .dat, .bin, or other non-standard naming conventions, which would be silently ignored by picklescan's scanning process. This allows potentially harmful pickle data to bypass security checks and infiltrate systems, creating opportunities for remote code execution or other malicious activities that leverage Python's pickle deserialization vulnerabilities.
The attack surface for this vulnerability extends beyond simple bypass scenarios, as it represents a fundamental flaw in the security tool's design philosophy. When picklescan fails to detect malicious pickle files due to extension mismatches, it creates a false positive scenario where security teams may believe their systems are protected when in reality they are vulnerable to pickle-based attacks. This issue aligns with ATT&CK technique T1059.007, which covers "Command and Scripting Interpreter: Python," as malicious pickle files often contain Python code that can execute arbitrary commands when deserialized. The vulnerability also intersects with ATT&CK technique T1566.001, covering "Phishing: Spearphishing Attachment," as attackers can craft phishing emails with malicious pickle files that appear legitimate to automated security scanners. Organizations using picklescan in their security infrastructure may experience a false sense of security, leading to delayed incident response and potentially catastrophic consequences when malicious pickle files are actually executed.
The mitigation strategy for this vulnerability requires immediate implementation of enhanced file detection mechanisms that go beyond simple extension matching. Security teams should update to picklescan version 0.0.22 or later, which addresses this specific issue by implementing more robust file type identification methods. The tool should incorporate magic number detection or content-based file type analysis to identify pickle files regardless of their file extensions. Additionally, organizations should implement layered security approaches that include multiple detection mechanisms, such as network-based intrusion detection systems, behavioral monitoring, and comprehensive file validation processes. System administrators should also consider implementing file extension whitelisting policies combined with content-based verification to ensure that all potentially dangerous file types are properly identified and handled. The vulnerability serves as a reminder of the critical importance of comprehensive input validation and the dangers of relying solely on superficial file attribute checks rather than implementing robust content analysis mechanisms that can identify malicious file types regardless of their naming conventions.