Raw vector
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2026-29091 is a high-severity Eval Injection (CWE-95) vulnerability in Locutus Locutus. Its CVSS base score is 8.1 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique JavaScript (T1059.007); ranked in the top 47% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
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-2026-29091 is a remote code execution (RCE) vulnerability in the Locutus project, a JavaScript library that ports standard libraries from other programming languages for educational purposes. The flaw affects versions prior to 3.0.0 and resides in the implementation of the call_user_func_array function and its wrapper call_user_func. Due to insufficient validation of callback array components, the functions pass untrusted input directly to eval(), enabling arbitrary JavaScript code injection into the application's runtime environment. The issue is rated with a CVSS v3.1 base score of 8.1 (AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:H) and is associated with CWE-95 (Improper Neutralization of Directives in Dynamically Evaluated Code).
A remote attacker without privileges can exploit this vulnerability over the network by supplying a specially crafted callback array to the affected functions. Exploitation requires high attack complexity but no user interaction. Successful exploitation grants the attacker the ability to execute arbitrary JavaScript code within the application's runtime, potentially leading to high confidentiality, integrity, and availability impacts, such as data theft, modification, or denial of service.
The vulnerability has been patched in Locutus version 3.0.0, as detailed in the project's GitHub security advisory (GHSA-fp25-p6mj-qqg6) and the specific commit (977a1fb169441e35996a1d2465b512322de500ad). Security practitioners should upgrade to version 3.0.0 or later to mitigate the issue.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-10051
Vulnerability Data
Locutus brings stdlibs of other programming languages to JavaScript for educational purposes. Prior to version 3.0.0, a remote code execution (RCE) flaw was discovered in the locutus project, specifically within the call_user_func_array function implementation. The vulnerability allows an attacker to…
more
inject arbitrary JavaScript code into the application's runtime environment. This issue stems from an insecure implementation of the call_user_func_array function (and its wrapper call_user_func), which fails to properly validate all components of a callback array before passing them to eval(). This issue has been patched in version 3.0.0.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
—
—
—
V1.3.1V1.3.2
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and code analysis can discover eval-injection flaws but does not stop their introduction.
Input validation explicitly requires neutralizing untrusted data before it reaches dynamic evaluation constructs such as eval.
Least privilege limits the damage an injected code fragment can perform once executed.
Secure-development standards and tools can mandate safe coding patterns that avoid unsafe dynamic evaluation.
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 avoidance of unsafe dynamic evaluation.
PR.DS-10 protects runtime data confidentiality/integrity but has no bearing on neutralizing externally influenced input during code generation, so neither direction shows any preventive effect.
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.
Security testing in development can detect eval injection vulnerabilities before deployment.
Secure development life cycle mandates input validation and safe coding practices that directly prevent eval injection.
Application security requirements include rules against dynamic code execution of untrusted input.
Secure architecture principles discourage unsafe dynamic evaluation constructs.
Secure coding explicitly requires neutralization of input before dynamic evaluation, directly mitigating eval injection.
Separation of environments limits the blast radius if eval injection occurs in non-production.