Raw vector
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:HCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2026-41883 is a high-severity Expression Language Injection (CWE-917) vulnerability. Its CVSS base score is 8.1 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 41th 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 SI-10 (Information Input Validation) and SA-8 (Security and Privacy Engineering Principles) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-28794
Vulnerability Data
OmniFaces is a utility library for Faces. Prior to versions 1.14.2, 2.7.32, 3.14.16, 4.7.5, and 5.2.3, there is a server-side EL injection leading to Remote Code Execution (RCE). This affects applications that use CDNResourceHandler with a wildcard CDN mapping (e.g.…
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libraryName:*=https://cdn.example.com/*). An attacker can craft a resource request URL containing an EL expression in the resource name, which is evaluated server-side. This issue has been patched in versions 1.14.2, 2.7.32, 3.14.16, 4.7.5, and 5.2.3.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.1.2V1.3.2V1.3.5V4.3.1
Mitigating Controls (NIST 800-53 r5) AI
Input validation directly requires checking and neutralizing special elements in externally influenced data before it is used to build executable statements such as EL expressions.
Security engineering principles include requirements for safe construction and sanitization of dynamic statements, structurally preventing expression-language injection at design time.
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 require input neutralization and safe EL construction to prevent injection flaws.
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 SDLC mandates input validation and output encoding that directly prevent expression-language injection.
Application security requirements explicitly call for controls against injection flaws including EL injection.
Secure architecture principles reduce the attack surface but do not prescribe the specific neutralization techniques needed.
Secure coding standards require proper escaping and parameterization of expression-language statements.
Security testing in development and acceptance can detect EL injection but does not itself implement the fix.