Cyber Resilience

CVE-2026-42523

XSS in Jenkins Github ≤ 1.46.0.1

XSS
Published
29 April 2026
Modified
05 May 2026
Patch / advisory
View advisory
CVSS Score v3.1 9.0
Click a component to see what it means
Raw vectorCVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:C/C:H/I:H/A:H
EPSS Score 0.0028 21th percentile
Risk Priority 62 floored blend · peak EPSS

CVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.

Summary

CVE-2026-42523 is a critical-severity Cross-site Scripting (CWE-79) vulnerability in Jenkins Github. Its CVSS base score is 9.0 (Critical).

Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked at the 21th 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 SA-11 (Developer Testing and Evaluation) and SI-10 (Information Input Validation) — see the control section below for these in your framework.

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-2026-42523 is a stored cross-site scripting (XSS) vulnerability, mapped to CWE-79, affecting Jenkins GitHub Plugin versions 1.46.0 and earlier. The flaw occurs when the plugin improperly processes the current job URL as part of JavaScript code implementing validation for the "GitHub hook trigger for GITScm polling" feature. Published on 2026-04-29, it carries a CVSS v3.1 base score of 9.0 (AV:N/AC:L/PR:L/UI:R/S:C/C:H/I:H/A:H), reflecting critical severity due to network accessibility, low attack complexity, and potential for high impacts across confidentiality, integrity, and availability with scope change.

Non-anonymous attackers possessing Overall/Read permission can exploit this stored XSS vulnerability. By injecting malicious payloads via the job URL during plugin interactions, they can store executable JavaScript that triggers in the browsers of other users viewing the affected job configuration, requiring user interaction but enabling broad compromise within the Jenkins instance.

The official Jenkins security advisory at https://www.jenkins.io/security/advisory/2026-04-29/#SECURITY-3704 provides guidance on mitigation and patching for this issue.

OWASP Top 10 for Web (2025)

A05:2025 Injection

EU & UK References

Vulnerability Data

Jenkins GitHub Plugin 1.46.0 and earlier improperly processes the current job URL as part of JavaScript implementing validation of the feature "GitHub hook trigger for GITScm polling", resulting in a stored cross-site scripting (XSS) vulnerability exploitable by non-anonymous attackers with…

more

Overall/Read permission.

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 →
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 →
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 →
Derived from this CVE’s CWE(s) via the direct CWE→ATT&CK cross-walk.

CVEs Like This One

CVE-2023-46650Same product: Jenkins Github
CVE-2023-40342Same vendor: Jenkins
CVE-2023-33002Same vendor: Jenkins
CVE-2023-39151Same vendor: Jenkins
CVE-2023-43499Same vendor: Jenkins
CVE-2023-43495Same vendor: Jenkins
CVE-2023-25763Same vendor: Jenkins
CVE-2023-46659Same vendor: Jenkins
CVE-2023-25761Same vendor: Jenkins
CVE-2023-28670Same vendor: Jenkins

Affected Assets

jenkins
github
≤ 1.46.0.1

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

Mitigating Controls (NIST 800-53 r5) AI

SA-11 Developer Testing and Evaluation good match

Developer testing and evaluation can discover missing or incorrect input neutralization through targeted web-application tests.

SI-10 Information Input Validation good match

Input validation directly enforces neutralization of untrusted data before it reaches web output generation.

SI-15 Information Output Filtering good match

Output filtering can catch or sanitize unneutralized script content before it is served to users.

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.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.8.29 Security testing in development and acceptance partial match
finds

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

References