CVE-2025-10157 is a critical vulnerability affecting mmaitre314's picklescan tool, versions up to and including 0.0.30. Picklescan is designed to analyze Python pickle files to detect unsafe or malicious payloads before deserialization. The vulnerability arises from a protection mechanism failure (CWE-693) where the tool performs an exact match check on module names to identify unsafe globals. However, this approach is flawed because it does not account for submodules of dangerous packages. For example, while the module 'asyncio' is flagged as unsafe, a submodule such as 'asyncio.unix_events' is not recognized as dangerous due to the exact string matching logic. Consequently, malicious payloads can be crafted to exploit these submodules, bypassing the unsafe globals check. When picklescan incorrectly classifies such files as safe, the malicious pickle can be loaded and executed, leading to arbitrary code execution. The vulnerability has a CVSS 4.0 base score of 9.3, indicating critical severity, with attack vector network (AV:N), low attack complexity (AC:L), no privileges or user interaction required (PR:N/UI:N), and high impact on confidentiality, integrity, and availability (C:H/I:H/A:H). No known exploits are currently reported in the wild, and no patches have been published yet. This vulnerability highlights the risks of relying on simplistic module name matching in security scanners for deserialization payloads, emphasizing the need for more robust and context-aware analysis.

For European organizations, the impact of this vulnerability can be significant, especially those relying on Python applications that utilize pickle deserialization and employ picklescan for security scanning. Successful exploitation allows remote attackers to execute arbitrary code without authentication or user interaction, potentially leading to full system compromise, data breaches, and disruption of critical services. Sectors such as finance, healthcare, government, and critical infrastructure, which often use Python-based automation and data processing tools, could be particularly at risk. The ability to bypass security checks undermines trust in the supply chain and internal security controls, increasing the risk of lateral movement and persistent threats within networks. Additionally, the lack of available patches means organizations must rely on immediate mitigation strategies to prevent exploitation. Given the high CVSS score and the nature of the vulnerability, the potential for severe operational and reputational damage is substantial.

1. Immediate mitigation should include disabling or restricting the use of picklescan versions up to 0.0.30 until a patched version is released. 2. Implement strict input validation and sandboxing around any pickle deserialization processes to limit the scope and privileges of executed code. 3. Employ alternative or supplementary security tools that perform more comprehensive analysis of pickle payloads, including recursive module and submodule inspection, to detect malicious constructs. 4. Monitor network and application logs for unusual activity indicative of exploitation attempts, such as unexpected module imports or execution patterns. 5. Educate developers and security teams about the limitations of exact module name matching and encourage adoption of safer serialization formats (e.g., JSON) where feasible. 6. Prepare incident response plans specific to deserialization attacks to enable rapid containment and remediation. 7. Engage with the vendor or open-source community to track patch releases and apply updates promptly once available.