CVE-2026-2969
Datapizza Ai 0.0.2
Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:H/UI:N/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N/E:P/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:XSummary
CVE-2026-2969 is a medium-severity Incomplete Filtering of Special Elements (CWE-791) vulnerability in Datapizza Datapizza Ai. Its CVSS base score is 5.1 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Template Injection (T1221); ranked at the 49th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
This vulnerability is AI-related — categorised as NLP and Transformers; in the LLM/Generative AI Risks 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.
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-2026-2969 is a server-side template injection (SSTI) vulnerability in the datapizza-labs datapizza-ai version 0.0.2. The flaw affects the ChatPromptTemplate function within the file datapizza-ai-core/datapizza/modules/prompt/prompt.py, specifically in the Jinja2 Template Handler component. Manipulation of the Prompt argument leads to improper neutralization of special elements used in the template engine, as classified under CWE-791 and CWE-1336. The vulnerability was published on 2026-02-23 and carries a CVSS v3.1 base score of 4.7 (AV:N/AC:L/PR:H/UI:N/S:U/C:L/I:L/A:L).
The vulnerability enables remote exploitation by attackers with high privileges (PR:H), requiring network access but low attack complexity and no user interaction. Successful exploitation allows limited impacts, including low-level disclosure of confidential information, modification of data, and denial of service. An exploit has been publicly disclosed, increasing the risk of active use.
Advisories from VulDB and the hacktivesec GitHub disclosure detail the issue, including a proof-of-concept (POC) for SSTI exploitation. The vendor was contacted early but provided no response, and no patches or mitigations are mentioned in the available references.
Notably, a public exploit is available via the disclosure repository, and the affected software's AI context—handling chat prompt templates—highlights relevance to AI/ML prompt engineering pipelines using Jinja2.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-7585
Vulnerability Data
A flaw has been found in datapizza-labs datapizza-ai 0.0.2. Affected is the function ChatPromptTemplate of the file datapizza-ai-core/datapizza/modules/prompt/prompt.py of the component Jinja2 Template Handler. This manipulation of the argument Prompt causes improper neutralization of special elements used in a template…
more
engine. Remote exploitation of the attack is possible. The exploit has been published and may be used. The vendor was contacted early about this disclosure but did not respond in any way.
- CWE(s)
AI Security AnalysisAI
- AI Category
- NLP and Transformers
- Risk Domain
- LLM/Generative AI Risks
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: ai
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.3.2V1.3.7V1.3.10
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and static analysis can discover missing neutralization of template directives.
Input validation directly requires complete filtering of special elements on received data before further processing or forwarding.
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 complete input filtering and sanitization to prevent this weakness.
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 and acceptance can detect incomplete filtering but does not itself implement the filtering.
Secure development life cycle processes include validation activities that reduce the likelihood of CWE-791 but do not specify the control itself.
Application security requirements explicitly call for input validation and sanitization that directly mitigates incomplete special-element filtering.
Secure system architecture and engineering principles require defensive design patterns that prevent unfiltered data from reaching downstream components.
Secure coding standards mandate complete filtering and escaping of special elements, directly eliminating CWE-791.