CVE-2022-3561 in librenmsinfo

Summary

by MITRE • 11/20/2022

Cross-site Scripting (XSS) - Generic in GitHub repository librenms/librenms prior to 22.10.0.

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Analysis

by VulDB Data Team • 04/30/2025

The vulnerability identified as CVE-2022-3561 represents a cross-site scripting flaw classified as generic within the LibreNMS network monitoring platform. This issue affects versions prior to 22.10.0 and resides in the repository librenms/librenms which is widely used for network infrastructure monitoring and management. The vulnerability stems from insufficient input validation and output encoding mechanisms that fail to properly sanitize user-supplied data before rendering it within web pages. Such shortcomings create an environment where malicious actors can inject arbitrary JavaScript code through carefully crafted input fields or parameters that are subsequently executed in the context of other users' browsers.

The technical implementation of this XSS vulnerability allows attackers to exploit various entry points within the LibreNMS web interface where user input is processed and displayed without adequate sanitization measures. The flaw operates by bypassing standard security controls that should prevent malicious scripts from being executed when users view pages containing compromised content. This typically occurs when application components fail to properly encode special characters or validate input against known malicious patterns. The vulnerability manifests across multiple components of the platform where user-provided data is directly rendered in HTML contexts without appropriate escaping mechanisms, making it particularly dangerous as it can affect various functionalities including device management, alert notifications, and user interface elements.

The operational impact of this vulnerability extends beyond simple data theft or session hijacking to potentially enable complete system compromise through advanced attack vectors. An attacker could leverage this XSS flaw to execute malicious scripts in the context of authenticated users, potentially gaining access to sensitive network monitoring data, device configurations, or even administrative privileges. The attack surface is particularly concerning given that LibreNMS is commonly deployed in enterprise environments where it serves as a critical monitoring tool for network infrastructure. The vulnerability could be exploited to redirect users to malicious domains, steal session cookies, or inject persistent malicious code that remains active until the browser session ends. According to CWE classification, this vulnerability maps to CWE-79 which specifically addresses cross-site scripting flaws, while ATT&CK framework categorizes this under T1566 for initial access through malicious inputs and T1059 for command and control through script execution.

Mitigation strategies for CVE-2022-3561 primarily focus on immediate version upgrades to 22.10.0 or later where the vulnerability has been addressed through proper input validation and output encoding implementations. Organizations should conduct comprehensive security assessments of their LibreNMS deployments to identify all instances of affected versions and implement patch management procedures to ensure timely updates. Additional defensive measures include implementing proper content security policies, enabling web application firewalls, and conducting regular security audits of input handling mechanisms. The fix typically involves strengthening input validation routines and ensuring that all user-supplied data is properly escaped before rendering in HTML contexts, thereby preventing malicious scripts from being executed in user browsers. Security teams should also consider implementing monitoring solutions to detect potential exploitation attempts and establish incident response procedures specifically addressing XSS vulnerabilities in network monitoring platforms.

Responsible

Huntr.dev

Reservation

10/17/2022

Disclosure

11/20/2022

Moderation

accepted

CPE

ready

EPSS

0.00324

KEV

no

Activities

very low

Sources

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