Raw vector
CVSS:3.0/AV:N/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:HSummary
CVE-2026-0771 is a high-severity Code Injection (CWE-94) vulnerability in Langflow Langflow. Its CVSS base score is 7.1 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); 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 LLM Application Platforms; in the Supply Chain and Deployment risk domain.
The strongest mitigations our analysis identified map to CM-7 (Least Functionality) 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-2026-4460
Vulnerability Data
Langflow PythonFunction Code Injection Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Langflow. Attack vectors and exploitability will vary depending on the configuration of the product. The specific flaw exists within…
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the handling of Python function components. Depending upon product configuration, an attacker may be able to introduce custom Python code into a workflow. An attacker can leverage this vulnerability to execute code in the context of the application. Was ZDI-CAN-27497.
- CWE(s)
AI Security AnalysisAI
- AI Category
- LLM Application Platforms
- Risk Domain
- Supply Chain and Deployment
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: langflow
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Direct RCE via Python code injection in a remotely accessible application component maps to public-facing app exploitation and Python interpreter abuse.
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
Mitigating Controls (NIST 800-53 r5) AI
Directly blocks introduction of attacker-supplied Python code into workflows by validating all inputs to PythonFunction components before execution.
Enforces least functionality by disabling or restricting the PythonFunction component unless explicitly required, eliminating the code-injection vector.
Applies malicious-code detection and sandboxing controls to Python code loaded at runtime, limiting successful exploitation of injected functions.
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.
PR.PS-06's SDLC practices directly target injection flaws via secure coding and testing (mostly), yet as a single broad outcome it leaves many code-generation specifics unaddressed (partial).
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.
Banning unapproved code samples and unauthenticated web services, combined with secure-coding standards and SAST, prevents the dynamic generation or inclusion of attacker-supplied code.
Controls that restrict unauthorized or malicious code from being introduced via external networks or removable media limit opportunities for an attacker to inject and execute arbitrary code.