Cyber Resilience

CVE-2023-4347

XSS in Librenms ≤ 23.8.0

Public PoCHigh EPSSXSS
Published
15 August 2023
Modified
21 November 2024
Patch / advisory
View advisory
CVSS Score v3.1 5.4
Click a component to see what it means
Raw vectorCVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:C/C:L/I:L/A:N
EPSS Score 0.67 99.2th percentile
Risk Priority 70 floored blend · peak EPSS

Summary

CVE-2023-4347 is a medium-severity Cross-site Scripting (CWE-79) vulnerability in Librenms Librenms. Its CVSS base score is 5.4 (Medium).

Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked in the top 0.8% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.

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-2023-4347 is a reflected cross-site scripting vulnerability (CWE-79) affecting the LibreNMS network monitoring application in versions prior to 23.8.0. The flaw resides in the web interface and carries a CVSS 3.1 score of 5.4, reflecting network attack vector, low attack complexity, required low-privileged authentication, and user interaction.

An authenticated attacker can supply a crafted URL that, when visited by another user, executes arbitrary JavaScript in the victim’s browser context. Successful exploitation yields limited impacts on confidentiality and integrity with scope change, allowing actions such as session token theft or unauthorized configuration changes within the LibreNMS instance.

The referenced GitHub commit (91c57a1ee54631e071b6b0c952d99c8ee892e824) and associated huntr.dev report document the remediation; administrators should upgrade to LibreNMS 23.8.0 or later to eliminate the reflected XSS vectors. The EPSS score has reached a peak of 0.8103 with a current value of 0.7733, indicating sustained but not sharply rising exploitation interest since disclosure.

OWASP Top 10 for Web (2025)

A05:2025 Injection

EU & UK References

Vulnerability Data

Cross-site Scripting (XSS) - Reflected in GitHub repository librenms/librenms prior to 23.8.0.

CWE(s)
CWE-79

Related Threats

MITRE ATT&CK Enterprise Techniques

T1185 Browser Session Hijacking Collection
Adversaries may take advantage of security vulnerabilities and inherent functionality in browser software to change content, modify user-behaviors, and intercept information as part of various browser session hijacking techniques.
attack.mitre.org →
T1539 Steal Web Session Cookie Credential Access
An adversary may steal web application or service session cookies and use them to gain access to web applications or Internet services as an authenticated user without needing credentials.
attack.mitre.org →
T1659 Content Injection Initial Access
Adversaries may gain access and continuously communicate with victims by injecting malicious content into systems through online network traffic.
attack.mitre.org →
T1189 Drive-by Compromise Initial Access
Adversaries may gain access to a system through a user visiting a website over the normal course of browsing.
attack.mitre.org →
T1190 Exploit Public-Facing Application Initial Access
Adversaries may attempt to exploit a weakness in an Internet-facing host or system to initially access a network.
attack.mitre.org →
Derived from this CVE’s CWE(s) via the direct CWE→ATT&CK cross-walk.

CVEs Like This One

CVE-2023-5060Same product: Librenms Librenms
CVE-2023-48295Same product: Librenms Librenms
CVE-2023-4978Same product: Librenms Librenms
CVE-2023-4979Same product: Librenms Librenms
CVE-2023-4981Same product: Librenms Librenms
CVE-2023-4980Same product: Librenms Librenms
CVE-2023-4982Same product: Librenms Librenms
CVE-2023-37308Same product class: network monitoring / SIEM
CVE-2023-33231Same product class: network monitoring / SIEM
CVE-2023-6364Same product class: network monitoring / SIEM

Affected Assets

librenms
librenms
≤ 23.8.0

Mitigating Controls

Control response

Prevent
Stop it (NIST 800-53)

—

Detect
Catch it (NIST detect / respond)

—

Harden
Shrink the surface (DISA STIG)

—

Validate
Prove the fix (OWASP ASVS)
  • V1.1.2
  • V1.3.2

Likely Mitigating Controls AI

Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.

CA-8 Penetration Testing
addresses: CWE-79

Penetration testing submits XSS payloads to web applications, detecting cross-site scripting flaws for subsequent remediation.

SI-10 Information Input Validation
addresses: CWE-79

Validates web inputs to reject script-related content that could produce XSS.

SI-15 Information Output Filtering
addresses: CWE-79

Output validation against expected content can reject or sanitize script content in generated web pages, reducing XSS exploitability.

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-06 mostly match
prevents

Secure SDLC practices directly target introduction of XSS via coding standards/testing (mostly), yet the single broad outcome leaves many specific neutralization vectors unaddressed (partial).

PR.PS-02 partial match
prevents

Patching and EOL replacement can remediate known XSS instances in libraries or frameworks (partial) but do nothing to enforce input neutralization in application code (none).

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.

A.8.29 Security testing in development and acceptance mostly match
finds

Secure-coding testing and automated code-analysis tools are applied to detect improper neutralization of script-related content during web-page generation.

A.5.6 Contact with special interest groups partial match
prevents

Knowledge exchange on emerging attack techniques and patches reduces the likelihood that cross-site scripting flaws remain unaddressed in deployed applications.

A.5.7 Threat intelligence partial match
prevents

Operational indicators of compromise for web-application attacks can be incorporated into WAF or input-filtering rules, lowering the likelihood that unsanitized data reaches the browser.

A.8.25 Secure development life cycle partial match
prevents

Requiring language-specific secure-coding standards and automated scanning during the SDLC catches missing output encoding or improper neutralization of untrusted data before the software reaches production.

A.8.28 Secure coding partial match
prevents

Secure-coding standards, SAST scans and removal of insecure code samples together eliminate the failure to neutralize script content that produces cross-site scripting flaws.

A.8.7 Protection against malware none match
none

Webpage malware scanning and block-listing of known malicious sites reduce the likelihood that reflected or stored script payloads reach a user’s browser.

References