Librenms
CVE-2025-23201
MEDIUM
Severity by source
AV:N/AC:L/PR:N/UI:R/S:U/C:L/I:L/A:N
Primary rating from GitHub Advisory · only source for this CVE.
CVSS VectorGitHub Advisory
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:L/I:L/A:N
Lifecycle Timeline
4DescriptionGitHub Advisory
librenms is a community-based GPL-licensed network monitoring system. Affected versions are subject to Cross-site Scripting (XSS) on the parameters:/addhost -> param: community. Librenms versions up to 24.10.1 allow remote attackers to inject malicious scripts. When a user views or interacts with the page displaying the data, the malicious script executes immediately, leading to potential unauthorized actions or data exposure. This issue has been addressed in release version 24.11.0. Users are advised to upgrade. There are no known workarounds for this vulnerability.
AnalysisAI
librenms is a community-based GPL-licensed network monitoring system. Rated medium severity (CVSS 5.4), this vulnerability is remotely exploitable, no authentication required, low attack complexity. Public exploit code available and no vendor patch available.
Technical ContextAI
This vulnerability is classified as Cross-Site Scripting (XSS) (CWE-79), which allows attackers to inject malicious scripts into web pages viewed by other users. librenms is a community-based GPL-licensed network monitoring system. Affected versions are subject to Cross-site Scripting (XSS) on the parameters:/addhost -> param: community. Librenms versions up to 24.10.1 allow remote attackers to inject malicious scripts. When a user views or interacts with the page displaying the data, the malicious script executes immediately, leading to potential unauthorized actions or data exposure. This issue has been addressed in release version 24.11.0. Users are advised to upgrade. There are no known workarounds for this vulnerability. Affected products include: Librenms. Version information: up to 24.10.1.
RemediationAI
No vendor patch is available at time of analysis. Monitor vendor advisories for updates. Sanitize all user input, use Content-Security-Policy headers, encode output contextually (HTML, JS, URL). Use frameworks with built-in XSS protection.
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External POC / Exploit Code
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