Raw vector
CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:HSummary
CVE-2025-64512 is a high-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Pdfminer Pdfminer.Six. Its CVSS base score is 8.6 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 23th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and SI-10 (Information Input Validation) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
CVE-2025-64512 is a deserialization vulnerability (CWE-502) in pdfminer.six, a community-maintained fork of the original PDFMiner tool for extracting information from PDF documents. In versions prior to 20251107, the CMapDB._load_data() function uses pickle.loads() to deserialize pickle files intended to be from the cmap/ directory within the pdfminer.six distribution. However, a malicious PDF can specify an alternative directory and filename ending in .pickle.gz, causing the tool to load and execute arbitrary code from a malicious, zipped pickle file during PDF processing.
The vulnerability has a CVSS v3.1 base score of 8.6 (AV:L/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H). Exploitation requires local access and user interaction, such as a victim running pdfminer.six on a specially crafted PDF file, with low complexity and no privileges needed. Successful exploitation allows arbitrary code execution with high impacts on confidentiality, integrity, and availability, and changes the scope to affect the entire system.
Mitigation is provided by upgrading to pdfminer.six version 20251107, which addresses the issue. The GitHub security advisory (GHSA-wf5f-4jwr-ppcp), fixing commit (b808ee05dd7f0c8ea8ec34bdf394d40e63501086), and release page detail the patch. Debian LTS announcements confirm updates for affected packages in their repositories.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-38315
Vulnerability Data
Pdfminer.six is a community maintained fork of the original PDFMiner, a tool for extracting information from PDF documents. Prior to version 20251107, pdfminer.six will execute arbitrary code from a malicious pickle file if provided with a malicious PDF file. The…
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`CMapDB._load_data()` function in pdfminer.six uses `pickle.loads()` to deserialize pickle files. These pickle files are supposed to be part of the pdfminer.six distribution stored in the `cmap/` directory, but a malicious PDF can specify an alternative directory and filename as long as the filename ends in `.pickle.gz`. A malicious, zipped pickle file can then contain code which will automatically execute when the PDF is processed. Version 20251107 fixes the issue.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can uncover deserialization flaws before deployment.
Input validation directly stops deserialization of untrusted data by ensuring inputs are valid before processing.
Engineering principles such as safe deserialization and input sanitization structurally prevent the weakness from being introduced.
Integrity verification tools can detect malformed or tampered serialized data after the fact.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
PR.PS-02 addresses only post-deployment updates/patching and cannot prevent introduction of unsafe deserialization code, yet it can remediate some instances when the flaw exists in outdated libraries or components.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Security testing includes validation of deserialization routines and the use of untrusted data, reducing the likelihood that unsafe object reconstruction will be deployed.
Requiring vetted libraries, regular updates and SAST before release reduces the likelihood that deserialization logic will accept and act on attacker-controlled serialized objects.
Regular scanning of third-party libraries and timely patching reduce the likelihood that unsafe deserialization vulnerabilities remain active.
Mandatory malware scanning of data received over networks or storage media intercepts malicious serialized payloads before they are deserialized by the target application.