CVE-2025-41076
Info Disclosure in Limesurvey 6.13.0
Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/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-2025-41076 is a medium-severity Generation of Error Message Containing Sensitive Information (CWE-209) vulnerability in Limesurvey Limesurvey. Its CVSS base score is 6.9 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Software (T1592.002); ranked at the 17th 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) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-198280
- 🇪🇸 INCIBE: www.incibe.es
Vulnerability Data
In version 6.13.0 of LimeSurvey, any external user can cause a 500 error in the survey system by sending a malformed session cookie. Instead of displaying a generic error message, the system exposes internal backend information, including the use of…
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the Yii framework, the MySQL/MariaDB database engine, the table name 'lime_sessions', primary keys, and fragments of the content that caused the conflict. This information can simplify the collection of data about the internal architecture of the application by an attacker.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V16.5.1
Mitigating Controls (NIST 800-53 r5) AI
si-11 directly requires error messages to avoid revealing exploitable information about the system or its data.
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 require sanitized error handling to prevent sensitive data disclosure.
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.
Secure coding standards explicitly forbid exposing sensitive data in errors.
Security testing can detect error messages that leak sensitive information.
Logging policy can require suppression of sensitive data in error messages.
Secure SDLC mandates error-handling rules that avoid leaking sensitive information.
Application security requirements can specify safe error messaging.
Secure architecture principles include proper exception handling.