Streamlit is a data oriented application development framework for python. Streamlit Open Source versions prior to 1.54.0 running on Windows hosts have an unauthenticated Server-Side Request Forgery (SSRF) vulnerability. The vulnerability arises from improper validation of attacker-supplied filesystem paths. In certain code paths, including within the `ComponentRequestHandler`, filesystem paths are resolved using `os.path.realpath()` or `Path.resolve()` before sufficient validation occurs. On Windows systems, supplying a malicious UNC path (e.g., `\\attacker-controlled-host\share`) can cause the Streamlit server to initiate outbound SMB connections over port 445. When Windows attempts to authenticate to the remote SMB server, NTLMv2 challenge-response credentials of the Windows user running the Streamlit process may be transmitted. This behavior may allow an attacker to perform NTLM relay attacks against other internal services and/or identify internally reachable SMB hosts via timing analysis. The vulnerability has been fixed in Streamlit Open Source version 1.54.0.
This vulnerability carries a MEDIUM severity rating with a CVSS v3.1 score of 4.7, indicating it requires adjacent network access but requires specific conditions to be met without requiring user interaction and does not require pre-existing privileges . The vulnerability impacts limited data confidentiality, limited integrity, for affected systems. Impacting 1 product from snowflake organizations running these solutions should prioritize assessment and patching.
Reported in 2026, this vulnerability emerged during an era marked by increased sophistication in supply chain attacks, cloud infrastructure vulnerabilities, and software-as-a-service (SaaS) security challenges. Security practices during this period emphasized zero-trust architectures, container security, and API protection.
2026-03-26T22:16:30.880
2026-04-01T13:28:47.470
Analyzed
CVSSv3.1: 4.7 (MEDIUM)
SecUtils normalizes and enriches National Vulnerability Database (NVD) records by standardizing vendor and product identifiers, aggregating vulnerability metadata from both NVD and MITRE sources, and providing structured context for security teams. For snowflake's affected products, we extract Common Platform Enumeration (CPE) data, Common Weakness Enumeration (CWE) classifications, CVSS severity metrics, and reference data to enable rapid vulnerability prioritization and asset correlation. This record contains no exploit code, proof-of-concept instructions, or attack methodologies—only defensive intelligence necessary for patch management, risk assessment, and security operations.