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23 CVE

Critique 4 Élevée 8 Moyenne 11 Faible 0 Non évaluée 0 Exploitées (KEV) Tri : plus récentes « Jupyter jupyter server » ✕
  1. CVE-2026-114135 8.8 Élevée

    jupyter-server jupyter_server

    Jupyter Server is the backend for Jupyter web applications. From 2.0.0 until 2.6.0, enabling GatewayClient.url replaced the normal KernelWebsocketHandler with WebSocketChannelsHandler, which authenticated the user but did not call authorizer.is_authorized(...) for the execute action on the kernels resource. A restricted authenticated user could therefore open an upstream kernel channel and obtain kernel execution despite the configured Authorizer denying that action, exposing data and credentials available to the kernel and permitting modification or disruption of the kernel environment. The default gateway configuration is fixed in version 2.6.0. In 2.6.0 and later, the same authorization bypass remains possible when a deployment manually registers the deprecated jupyter_server.gateway.handlers module, because its handler still omits the configured kernel-execute authorization decision.

  2. CVE-2026-111057 10.0 Critique

    mljar mercury

    Mercury is a Python framework for sharing Jupyter notebooks as web applications and dashboards. From 3.0.0 until 3.2.4, a missing comma in BLOCKED_PATTERNS concatenates the /lab and /api/terminals regular-expression literals. Requests to /api/terminals therefore bypass the anonymous endpoint blocklist and reach Jupyter Server's terminal API. An unauthenticated attacker can use the resulting interactive operating-system shell to execute commands and access data available to the Mercury process. This issue is fixed in version 3.2.4.

  3. CVE-2026-102832 4.2 Moyenne

    jupyterlab · jupyterlab jupyterlite-core · jupyterlab notebook

    JupyterLab is an extensible environment for interactive and reproducible computing, based on the Jupyter Notebook Architecture. From 4.5.7 until 4.5.11 and 4.6.4, the markdownviewer:trust and notebook:trust command-link handlers use tracker.currentWidget to resolve the current Markdown viewer or notebook when the user answers rather than retaining the document whose command button was clicked. If another document becomes current while the prompt is open and the user chooses Trust, JupyterLab marks the second document trusted while leaving the clicked document untrusted. Later command buttons in the incorrectly trusted document run without a prompt, and trusting a notebook marks all cells trusted, saves unsaved edits, and persists the server signature to disk. Applications that bundle JupyterLab, including affected Notebook and JupyterLite releases, inherit the behavior. This issue is fixed in versions 4.5.11 and 4.6.4.

  4. CVE-2026-108752 4.2 Moyenne

    jupyterhub

    JupyterHub through 6.0.1 contains an identifier collision vulnerability that allows authenticated users to overwrite another user's named-server OAuth client by registering a hyphenated username. Attackers holding a name like alice-prod can overwrite the client for alice's server prod, breaking OAuth login and revoking tokens by stopping their own server.

  5. CVE-2026-102904 5.4 Moyenne

    jupyterlab

    JupyterLab is an extensible environment for interactive and reproducible computing, based on the Jupyter Notebook Architecture. From JupyterLab 4.0.0 until 4.5.11 and 4.6.4, the PyPI Extension Manager uninstall request reaches ExtensionHandler.post, which validates extension names for installation but passes uninstall names to PyPIExtensionManager.uninstall and python -m pip uninstall without rejecting option-like values. The security impact requires that the PyPI Extension Manager is enabled, the account can call the extension API, and kernels and terminals are disabled or delegated to remote hosts; otherwise the user can already read files and make outbound requests directly. An authenticated user with extension API access can supply a pip requirements option to make the server read a local file or fetch an internal URL, and reflected parse errors can return the first unparsable line or response content. A pip log option can also create or corrupt a chosen path with pip-generated log text, but the requester cannot select an arbitrary disclosed line or arbitrary file content, and the injection does not add code execution or availability impact beyond ordinary package removal. This issue is fixed in JupyterLab 4.5.11 and 4.6.4.

  6. CVE-2026-102830 6.8 Moyenne

    jupyterlab · jupyterlab jupyterlite-core

    JupyterLab is an extensible environment for interactive and reproducible computing, based on the Jupyter Notebook Architecture. From JupyterLab 3.0.0 until 4.5.11 and 4.6.4, and in JupyterLite Core 0.8.3 and earlier, the Plural-Forms header in a selected third-party language pack can append JavaScript after a valid plural rule because prefix-only regular-expression validation accepts a matching prefix without requiring the entire header to match. JupyterLab passes the accepted expression to new Function, so loading the catalogue and translating a plural string executes the appended code in the authenticated JupyterLab origin. Where Jupyter Server kernels, terminals, and APIs are exposed, the code can use authenticated server APIs to read or modify files and run code. Impact is much more limited in JupyterLite because it typically lacks most exposed Jupyter Server surfaces. The default English locale is unaffected because it does not load a translation catalogue. This issue is fixed in JupyterLab 4.5.11 and 4.6.4 and JupyterLite Core 0.8.4.

  7. CVE-2026-86049 7.1 Élevée

    jupyter-server jupyter_server

    Jupyter Server is the backend for Jupyter web applications. Prior to version 2.21.0, the 5xx request logging path in jupyter_server/log.py copies the Referer header into a JSON header block without applying the token scrubbing used for the request URI. A request that returns HTTP 500 while the Referer contains a token-bearing URL can therefore write that token to server logs in plaintext. An attacker who can read those logs can recover the token and use the affected user's Jupyter Server permissions. This issue is fixed in version 2.21.0.

  8. CVE-2026-73417 8.6 Élevée

    jupyterlab

    jupyterlab is an extensible environment for interactive and reproducible computing, based on the Jupyter Notebook Architecture. From 3.3.0 until 4.5.10 and 4.6.2, JupyterLab allows notebook settings to be shared and applied through an overrides.json file using the Import button in the Settings Editor. In packages/notebook-extension/schema/tracker.json and packages/notebook-extension/src/index.ts, the sideBySideLeftMarginOverride and sideBySideRightMarginOverride settings are not properly validated before being inserted into style content, allowing a crafted settings file to contain instructions that execute as code instead of only changing display preferences. A user can import the malicious file, or an attacker with access to a shared settings location can plant an overrides.json that is applied automatically. The embedded code runs with the affected user's access and can read or modify notebooks and files and run code through the notebook server, including on a connected kernel. This issue is fixed in versions 4.5.10 and 4.6.2.

  9. CVE-2026-73627 6.0 Moyenne

    jupyterlab

    JupyterLab (pip package 'jupyterlab') versions >=4.1.0,<=4.5.9 and >=4.6.0,<=4.6.1 contain a plugin manager lock-rule enforcement bypass. Two server-side enforcement gaps allow an authenticated user to circumvent administrator lock rules by making direct requests to the /lab/api/plugins endpoint, enabling or disabling plugins that were locked — including child plugins of multi-plugin extensions and plugins locked via the 'lock all' mechanism. This can impact data integrity and bypass hardening or restrictions (e.g., download/upload limits) implemented through locked plugins. Fixed in versions 4.6.2 and 4.5.10.

  10. CVE-2026-73415 7.5 Élevée

    jupyterlab

    jupyterlab is an extensible environment for interactive and reproducible computing, based on the Jupyter Notebook Architecture. Prior to 4.5.10 and 4.6.2, in packages/imageviewer/src/widget.ts, JupyterLab's ImageViewer uses URL.createObjectURL for a specially crafted SVG image and revokes the blob URL too early, allowing the image to retain an executable same-origin context when it is opened through the image viewer and then opened in a new browser tab. The resulting cross-site scripting can be used to execute arbitrary code on the JupyterLab server. This issue is fixed in versions 4.5.10 and 4.6.2.

  11. CVE-2026-54338 5.3 Moyenne

    jupyterhub

    JupyterHub is software that allows users to create a multi-user server for Jupyter notebooks. Prior to 5.5.0, invalid input to form-based login authenticators can place an unbounded attacker-controlled username in failed-login logs, allowing an unauthenticated attacker to consume logging and storage resources. This issue is fixed in version 5.5.0.

  12. CVE-2026-44182 10.0 Critique

    jupyter-server enterprise_gateway · Jupyter enterprise gateway

    Jupyter Enterprise Gateway launches remote Jupyter Notebook kernels across distributed clusters like Apache Spark, Kubernetes, and Docker Swarm. In versions prior to 3.3.0, the server interpolates untrusted environment variables (e.g., KERNEL_XXX) into Kubernetes manifests without YAML-aware escaping, enabling YAML injection attacks. Attackers can inject new fields, overwrite critical fields (e.g., duplicate securityContext keys, where the last one prevails), and inject document boundaries (--- for new documents, ... for end-of-document) to generate multiple resources, potentially creating arbitrary types, such as privileged pods. The Jinja2 template for the Kubernetes manifest contains several kernel_xxx variables, such as kernel_working_dir that are used when rendering the manifest and are all vectors for YAML injection. This issue has been fixed in version 3.3.0.

  13. CVE-2026-44181 10.0 Critique

    jupyter-server enterprise_gateway · Jupyter enterprise gateway

    Jupyter Enterprise Gateway launches remote Jupyter Notebook kernels across distributed clusters like Apache Spark, Kubernetes, and Docker Swarm. In versions 2.0.0rc2 and above, prior to 3.3.0, the environment variables (KERNEL_XXX) used during the rendering of the Kubernetes manifest are vulnerable to Server Side Template Injection (SSTI). By including Jinja2 template expressions it is possible to execution Python code and OS Commands in the Enterprise Gateway service. The code can use or steal the Kubernetes service account token, which can steal Kubernetes secrets and be used to fully compromise the Kubernetes cluster by scheduling a privileged pod or a pod with a hostPath volume mount. This issue has been fixed in version 3.3.0.

  14. CVE-2026-44180 9.8 Critique

    jupyter-server enterprise_gateway · Jupyter enterprise gateway

    Jupyter Enterprise Gateway launches remote Jupyter Notebook kernels across distributed clusters like Apache Spark, Kubernetes, and Docker Swarm. Versions 2.0.0rc1 and above prior to 3.3.0 have a prohibited UID and GID feature that by default prevents launching kernels with UID or GID 0 (root), and this restriction can be bypassed using a specially crafted KERNEL_UID or KERNEL_GID value. This input validation vulnerability allows running Jupyter kernels as root, which can be dangerous as it allows more attack surface, and may lead to container escapes, compromising the worker node and all workloads running on it. Repeated exploitation can compromise all worker nodes, and thus the entire Kubernetes cluster. It is possible to specify volume mounts, so one vector for a container escape is to use a hostPath R/W volume mount, use this UID/GID bypass to run as root, and then gain code execution in the underlying worker node by creating a crontab entry in the mounted host file system. This issue has been fixed in version 3.0.0.

  15. CVE-2026-6658 5.4 Moyenne

    jupyter/jupyter

    A vulnerability in jupyter/nbconvert versions <= 7.17.0 allows for Cross-site Scripting (XSS) via unsanitized `text/vnd.mermaid` output in HTML exports. The `data_mermaid` block in `share/templates/lab/base.html.j2` renders `text/vnd.mermaid` cell output directly into HTML without escaping, enabling attackers to inject arbitrary HTML/JavaScript by breaking out of the `<pre>` tag. This vulnerability impacts any server using nbconvert to render notebooks as HTML, allowing attackers to execute arbitrary JavaScript in the context of users viewing the HTML export.

  16. CVE-2026-44727 5.4 Moyenne

    jupyter-server jupyter_server · Red Hat Migration Toolkit for Applications 8.2 · Red Hat OpenShift AI 3.4 · Red Hat OpenShift AI (RHOAI)

    Jupyter Server is the backend for Jupyter web applications. Prior to 2.20, the nbconvert HTTP handlers in jupyter_server render user-authored notebook HTML under the Jupyter origin without a sandbox directive in their Content-Security-Policy. Combined with nbconvert.HTMLExporter's default non-sanitizing behavior, a notebook carrying an HTML payload in a display_data output triggers stored XSS with cookie access, full /api/* authority, and kernel RCE. This vulnerability is fixed in 2.20.

  17. CVE-2026-6657 8.8 Élevée

    jupyter/jupyter · Jupyter jupyter server

    A vulnerability in jupyter-server versions 1.12.0 through 2.17.0 allows an attacker to bypass CORS origin validation when the `allow_origin_pat` configuration is used. The issue arises from the use of `re.match()` for validating the `Origin` header, which only anchors at the start of the string. This allows attacker-controlled domains such as `trusted.example.com.evil.com` to pass validation against patterns intended to match `trusted.example.com`. The vulnerability affects multiple locations in the codebase, including CORS headers, WebSocket connections, referer validation, and login redirects, potentially enabling phishing attacks, arbitrary code execution, and unauthorized access to sensitive API responses.

  18. CVE-2026-5422 8.1 Élevée

    jupyter/jupyter · Jupyter jupyter server

    A path traversal vulnerability exists in jupyter-server version 2.17.0 due to an incorrect root directory boundary check in the _get_os_path() function within jupyter_server/services/contents/fileio.py. The check uses startswith(root) without appending a trailing path separator, allowing sibling directories with names starting with the same prefix as root_dir to bypass the check. Additionally, the to_os_path() function in utils.py does not strip ".." from path parts, enabling traversal sequences to bypass the vulnerable check. This vulnerability can lead to unauthorized read/write access to files in sibling directories, potentially exposing sensitive data in shared hosting environments.

  19. CVE-2026-40864 4.3 Moyenne

    jupyterhub · Jupyter jupyterhub

    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.

  20. CVE-2026-40934 6.8 Moyenne

    jupyter-server jupyter_server · Jupyter jupyter server

    Jupyter Server is the backend for Jupyter web applications. In versions 2.17.0 and earlier, the secret used to sign authentication cookies is persisted to a static file at ~/.local/share/jupyter/runtime/jupyter_cookie_secret and is never rotated when a user changes their password. After a password reset and server restart, any previously issued authentication cookie remains cryptographically valid because the signing key has not changed. An attacker who has captured a session cookie through any means retains full authenticated access to the server regardless of subsequent password changes. This affects deployments using password-based authentication, particularly shared or public-facing servers where credential rotation is expected to revoke existing sessions. This issue has been fixed in version 2.18.0.

  21. CVE-2026-40110 7.3 Élevée

    jupyter-server jupyter_server · Red Hat Migration Toolkit for Applications 8.2 · Red Hat OpenShift AI (RHOAI) · Jupyter jupyter server

    Jupyter Server is the backend for Jupyter web applications. In versions 2.17.0 and earlier, the Origin header validation uses Python's re.match() to check incoming origins against the allow_origin_pat configuration value. Because re.match() only anchors at the start of the string and does not require a full match, a pattern intended to match only a trusted domain (e.g., trusted.example.com) will also match any origin that begins with that domain followed by additional characters (e.g., trusted.example.com.evil.com). An attacker who controls such a domain can bypass the CORS origin restriction and make cross-origin requests to the Jupyter Server API from an untrusted site. This issue has been fixed in version 2.18.0.

  22. CVE-2026-35397 8.8 Élevée

    jupyter-server jupyter_server · Red Hat Migration Toolkit for Applications 8.2 · Red Hat OpenShift AI 3.4 · Red Hat OpenShift AI (RHOAI)

    Jupyter Server is the backend for Jupyter web applications. In versions 2.17.0 and earlier, a path traversal vulnerability in the REST API allows an authenticated user to escape the configured root_dir and access sibling directories whose names begin with the same prefix as the root_dir. For example, with a root_dir named "test", the API permits access to a sibling directory named "testtest" through a crafted request to the /api/contents endpoint using encoded path components. An attacker can read, write, and delete files in affected sibling directories. Multi-tenant deployments using predictable naming schemes are particularly at risk, as a user with a directory named "user1" could access directories for user10 through user19 and beyond. A user who can choose a single-character folder name could gain access to a significant number of sibling directories. Version 2.18.0 contains a fix. As a workaround, ensure folder names do not share a common prefix with any sibling directory.

  23. CVE-2025-61669 6.1 Moyenne

    jupyter-server jupyter_server · Jupyter jupyter server

    Jupyter Server is the backend for Jupyter web applications. In jupyter_server versions through 2.17.0, the next query parameter in the login flow is insufficiently validated in `LoginFormHandler._redirect_safe()`, which allows redirects to arbitrary external domains via values such as `///example.com`. An attacker can use a crafted login URL to redirect users to a malicious site and facilitate phishing attacks. This issue is fixed in version 2.18.0.