CVE-2026-30876
Chamilo Lms ≤ 1.11.36
Raw vector
CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:L/VI:N/VA:N/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-2026-30876 is a medium-severity Observable Response Discrepancy (CWE-204) vulnerability in Chamilo Chamilo Lms. Its CVSS base score is 6.3 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Account Discovery (T1087); ranked at the 11th 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 SI-11 (Error Handling) and IA-6 (Authentication Feedback) — see the control section below for these in your framework.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-12498
Vulnerability Data
Chamilo LMS is a learning management system. Prior to version 1.11.36, Chamilo is vulnerable to user enumeration with valid/invalid username. This issue has been patched in version 1.11.36.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
CWE-204 enables direct account/user enumeration via response discrepancies, mapping to Account Discovery.
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
Mitigating Controls (NIST 800-53 r5) AI
Directly requires error messages to avoid revealing information (such as username validity) that could be exploited, addressing the CWE-204 response discrepancy.
Obscures authentication feedback so that differences between valid and invalid usernames are not observable to an attacker.
Limits rapid probing of usernames via unsuccessful logon throttling, reducing the practicality of enumeration even if responses differ.
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.
Secure SDLC practices directly prevent introduction of inconsistent response behavior that leaks internal state.
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 can detect observable response discrepancies before deployment.
Network security controls can enforce uniform responses and suppress observable discrepancies.
Secure SDLC practices include error-handling and response standardization to avoid information disclosure.
Application security requirements typically mandate consistent, non-revealing error messages.
Secure architecture principles discourage designs that leak internal state via differing responses.
Secure coding standards explicitly require uniform error handling to prevent information leakage.