JupyterHub is software that allows users to create a multi-user server for Jupyter notebooks. In versions 4.1.0 through 5.4.4, XSRF protection (updated in 4.1.0) inappropriately treated requests with Sec-Fetch-Mode: no-cors as same-origin requests, bypassing XSRF checks. The JSON API is not affected, only HTTP form endpoints, such as /hub/spawn and /hub/accept-share, meaning attackers could trigger server spawn (but not access the server) and if the attacker is a JupyterHub user permitted to share access to their server, cause a user to accept a share and have access to the attacker's server. This issue has been fixed in version 5.4.5. If developers are unable to immediately upgrade, they can temporarily mitigate this issue by dropping requests to JupyterHub with Sec-Fetch-Mode: no-cors if they are using a reverse proxy.
This vulnerability carries a MEDIUM severity rating with a CVSS v3.1 score of 5.4, indicating it can be exploited remotely over the network with relatively low complexity though user interaction is required and does not require pre-existing privileges . The vulnerability impacts limited integrity, and limited availability for affected systems. Impacting 1 product from jupyter 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.
2026-05-22T21:16:43.177
2026-07-23T11:10:00.120
Analyzed
CVSSv3.1: 5.4 (MEDIUM)
| Type | Vendor | Product | Version/Range | Vulnerable? |
|---|---|---|---|---|
| Application | jupyter | jupyterhub | < 5.4.5 | 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.