Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:H/UI:N/VC:L/VI:L/VA:H/SC:N/SI:N/SA:N/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-2025-52998 is a high-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Chamilo Chamilo Lms. Its CVSS base score is 7.0 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 30th 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.
CVE-2025-52998 is a critical vulnerability (CVSS 9.8, CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H) affecting Chamilo, an open-source learning management system, in versions prior to 1.11.30. The issue arises from unsafe deserialization of spoofable data (CWE-502), enabling attackers to instantiate arbitrary classes and fully control their properties. This flaw allows modification of the web application's operational logic.
The vulnerability can be exploited remotely by unauthenticated attackers over the network with low attack complexity and no user interaction required. By supplying malicious serialized data, an attacker gains the ability to create objects of arbitrary classes and manipulate their properties, potentially leading to severe impacts on confidentiality, integrity, and availability as reflected in the CVSS scores.
Mitigation is available in Chamilo version 1.11.30, which patches the deserialization flaw. Organizations should upgrade to this version immediately. Key resources include the patching commit at https://github.com/chamilo/chamilo-lms/commit/ba7e15d8cfefcd451de939e98d461b17e72eb627, the release announcement at https://github.com/chamilo/chamilo-lms/releases/tag/v1.11.30, and the GitHub security advisory at https://github.com/chamilo/chamilo-lms/security/advisories/GHSA-6mwg-2mw5-rx5v.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-208180
Vulnerability Data
Chamilo is a learning management system. Prior to version 1.11.30, in the application, deserialization of data is performed, the data can be spoofed. An attacker can create objects of arbitrary classes, as well as fully control their properties, and thus…
more
modify the logic of the web application's operation. This issue has been patched in version 1.11.30.
- 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.