Jupyter Server Proxy allows users to run arbitrary external processes alongside their Jupyter notebook servers and provides authenticated web access. Prior to versions 3.2.3 and 4.1.1, Jupyter Server Proxy did not check user authentication appropriately when proxying websockets, allowing unauthenticated access to anyone who had network access to the Jupyter server endpoint. This vulnerability can allow unauthenticated remote access to any websocket endpoint set up to be accessible via Jupyter Server Proxy. In many cases, this leads to remote unauthenticated arbitrary code execution, due to how affected instances use websockets. The websocket endpoints exposed by `jupyter_server` itself is not affected. Projects that do not rely on websockets are also not affected. Versions 3.2.3 and 4.1.1 contain a fix for this issue.
This vulnerability carries a CRITICAL severity rating with a CVSS v3.1 score of 9.0, indicating it can be exploited remotely over the network but requires specific conditions to be met without requiring user interaction and does not require pre-existing privileges . The vulnerability impacts confidentiality (data exposure), integrity (unauthorized modifications), and availability (service disruption) for affected systems. Impacting 1 product from jupyter organizations running these solutions should prioritize assessment and patching.
Reported in 2024, 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.
2024-03-20T20:15:08.680
2025-02-21T16:37:13.663
Analyzed
CVSSv3.1: 9.0 (CRITICAL)
| Type | Vendor | Product | Version/Range | Vulnerable? |
|---|---|---|---|---|
| Application | jupyter | jupyter_server_proxy | < 3.2.3 | Yes |
| Application | jupyter | jupyter_server_proxy | < 4.1.1 | Yes |
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 jupyter'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.