Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:U/C:H/I:H/A:HSummary
CVE-2026-27099 is a high-severity Cross-site Scripting (CWE-79) vulnerability in Jenkins Jenkins. Its CVSS base score is 8.0 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked at the 38th 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-2026-27099 is a stored cross-site scripting (XSS) vulnerability in Jenkins, affecting versions 2.483 through 2.550 (inclusive) and LTS versions 2.492.1 through 2.541.1 (inclusive). The issue arises because Jenkins does not properly escape user-provided descriptions in the "Mark temporarily offline" offline cause field for agents, allowing injected scripts to be stored and later rendered in the user interface. This flaw is classified under CWE-79 and carries a CVSS v3.1 base score of 8.0 (AV:N/AC:L/PR:L/UI:R/S:U/C:H/I:H/A:H).
Attackers with Agent/Configure or Agent/Disconnect permissions can exploit this vulnerability by marking an agent temporarily offline and supplying a malicious payload in the description field. When authorized users view the agent's status or related pages, the unescaped script executes in their browsers, potentially leading to session hijacking, data theft, or unauthorized actions on behalf of the victim within the Jenkins instance.
The official Jenkins security advisory details mitigation steps, including upgrading to Jenkins LTS 2.541.2 or later, or Jenkins weekly 2.551 or later, available at https://www.jenkins.io/security/advisory/2026-02-18/#SECURITY-3669. Security practitioners should review the advisory for full patch information and verify affected instances promptly.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-8091
Vulnerability Data
Jenkins 2.483 through 2.550 (both inclusive), LTS 2.492.1 through 2.541.1 (both inclusive) does not escape the user-provided description of the "Mark temporarily offline" offline cause, resulting in a stored cross-site scripting (XSS) vulnerability exploitable by attackers with Agent/Configure or Agent/Disconnect…
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- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.1.2V1.3.2
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can discover missing or incorrect input neutralization through targeted web-application tests.
Input validation directly enforces neutralization of untrusted data before it reaches web output generation.
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.
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).
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.
Secure-coding testing and automated code-analysis tools are applied to detect improper neutralization of script-related content during web-page generation.
Knowledge exchange on emerging attack techniques and patches reduces the likelihood that cross-site scripting flaws remain unaddressed in deployed applications.
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.
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.
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.
Webpage malware scanning and block-listing of known malicious sites reduce the likelihood that reflected or stored script payloads reach a user’s browser.