Raw vector
CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:HSummary
CVE-2026-44209 is a high-severity Improper Neutralization of Special Elements Used in a Template Engine (CWE-1336) vulnerability in Redhat (inferred from references). Its CVSS base score is 7.5 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Template Injection (T1221); ranked at the 43th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
This vulnerability is AI-related — categorised as NLP and Transformers; in the Supply Chain and Deployment risk domain.
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.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-31997
Vulnerability Data
Banks generates meaningful LLM prompts using a template language that makes sense. Prior to 2.4.2, banks uses jinja2.Environment() (unsandboxed) to render prompt templates. Applications that pass user-supplied strings as the template argument to Prompt() are vulnerable to Server-Side Template Injection…
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(SSTI), which can lead to Remote Code Execution (RCE) on the host system. This vulnerability is fixed in 2.4.2.
- CWE(s)
AI Security AnalysisAI
- AI Category
- NLP and Transformers
- Risk Domain
- Supply Chain and Deployment
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: llm
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.3.2V1.3.7V1.3.10V1.1.2
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and static analysis can discover missing neutralization of template directives.
Input validation rejects or sanitizes untrusted data before it reaches the template engine, stopping injection of special syntax.
Security engineering principles require use of safe templating APIs and proper escaping of external input.
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 proper input neutralization in template engines to prevent injection.
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 can detect template-injection flaws but does not itself implement neutralization controls.
Secure development life cycle mandates input validation and sanitization that directly prevents template-injection weaknesses.
Application security requirements explicitly call for neutralizing special elements in template engines.
Secure architecture principles reduce the likelihood of unsafe template processing but do not prescribe specific neutralization techniques.
Secure coding standards require proper escaping or sandboxing of template directives, directly mitigating CWE-1336.