Raw vector
CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:H/VI:H/VA:H/SC:H/SI:H/SA:H/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:XSummary
CVE-2025-47292 is a critical-severity Deserialization of Untrusted Data (CWE-502) vulnerability. Its CVSS base score is 9.5 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 47th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
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.
Cap Collectif is an online decision-making platform that integrates multiple tools. Prior to commit 812f2a7d271b76deab1175bdaf2be0b8102dd198, the DebateAlternateArgumentsResolver component performed unsafe deserialization of a Cursor object. This flaw, tracked as CWE-502, permitted an unauthenticated remote attacker to supply arbitrary classes for deserialization and resulted in a CVSS 4.0 score of 9.5.
An unauthenticated attacker with network access can supply a malicious serialized Cursor to the resolver, achieving remote code execution on the server. No user interaction or authentication is required, and the attack can also impact confidentiality, integrity, and availability in both the vulnerable component and dependent systems.
The vulnerability is addressed in commit 812f2a7d271b76deab1175bdaf2be0b8102dd198; the corresponding GitHub Security Advisory GHSA-hf7r-rjh4-5fc8 recommends upgrading to the patched version. The associated EPSS score remains flat at 0.0488 with no material increase since disclosure.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-28081
Vulnerability Data
Cap Collectif is an online decision making platform that integrates several tools. Before commit 812f2a7d271b76deab1175bdaf2be0b8102dd198, the `DebateAlternateArgumentsResolver` deserializes a `Cursor`, allowing any classes and which can be controlled by unauthenticated user. Exploitation of this vulnerability can lead to Remote Code…
more
Execution. The vulnerability is fixed in commit 812f2a7d271b76deab1175bdaf2be0b8102dd198.
- 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.