CVE-2026-33497
Published: 24 March 2026
Summary
CVE-2026-33497 is a high-severity Path Traversal (CWE-22) vulnerability in Langflow Langflow. Its CVSS base score is 7.5 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 7.6th 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 Other AI Platforms.
The strongest mitigations our analysis identified are NIST 800-53 AC-3 (Access Enforcement) and SI-10 (Information Input Validation).
Threat & Defense at a Glance
Threat & Defense Details
Mitigating Controls (NIST 800-53 r5)AI
Directly addresses path traversal by requiring validation of untrusted inputs like folder_name and file_name parameters to reject directory traversal sequences such as '../'.
Enforces approved authorizations for file access in the download_profile_picture endpoint, preventing unauthorized reads of sensitive files like secret_key outside intended directories.
Provides boundary protection that can inspect and block network requests containing path traversal payloads targeting the unauthenticated /profile_pictures endpoint.
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Path traversal in unauthenticated public endpoint enables remote exploitation of web app (T1190) for direct local file reads (T1005) including secret_key credentials (T1552.001).
NVD Description
Langflow is a tool for building and deploying AI-powered agents and workflows. Prior to version 1.7.1, in the download_profile_picture function of the /profile_pictures/{folder_name}/{file_name} endpoint, the folder_name and file_name parameters are not strictly filtered, which allows the secret_key to be read…
more
across directories. Version 1.7.1 contains a patch.
Deeper analysisAI
CVE-2026-33497 is a path traversal vulnerability (CWE-22) in Langflow, an open-source tool for building and deploying AI-powered agents and workflows. The flaw affects versions prior to 1.7.1 and exists in the download_profile_picture function of the /profile_pictures/{folder_name}/{file_name} endpoint. There, the folder_name and file_name parameters are not strictly filtered, enabling directory traversal that exposes sensitive files such as the secret_key.
Remote attackers can exploit this vulnerability without authentication, privileges, or user interaction, as indicated by its CVSS v3.1 base score of 7.5 (AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N). Exploitation involves crafting requests with manipulated folder_name or file_name values to traverse directories and retrieve confidential data like secret keys, resulting in high-impact confidentiality violations over the network with low attack complexity.
Langflow version 1.7.1 includes a patch to address the issue. Additional details on the vulnerability and remediation are available in the GitHub Security Advisory at https://github.com/langflow-ai/langflow/security/advisories/GHSA-ph9w-r52h-28p7.
Details
- CWE(s)
Affected Products
AI Security AnalysisAI
- AI Category
- Other AI Platforms
- Risk Domain
- N/A
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: ai