| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| OAuthenticator is software that allows OAuth2 identity providers to be plugged in and used with JupyterHub. Prior to version 17.4.0, an authentication bypass vulnerability in oauthenticator allows an attacker with an unverified email address on an Auth0 tenant to login to JupyterHub. When email is used as the usrname_claim, this gives users control over their username and the possibility of account takeover. This issue has been patched in version 17.4.0. |
| Jupyter Scheduler is collection of extensions for programming jobs to run now or run on a schedule. The list of conda environments of `jupyter-scheduler` users maybe be exposed, potentially revealing information about projects that a specific user may be working on. This vulnerability has been patched in version(s) 1.1.6, 1.2.1, 1.8.2 and 2.5.2. |
| LTI JupyterHub Authenticator is a JupyterHub authenticator for LTI. Prior to version 1.6.3, the LTI 1.1 validator stores OAuth nonces in a class-level dictionary that grows without bounds. Nonces are added before signature validation, so an attacker with knowledge of a valid consumer key can send repeated requests with unique nonces to gradually exhaust server memory, causing a denial of service. This issue has been patched in version 1.6.3. |
| The nbconvert tool, jupyter nbconvert, converts Jupyter notebooks to various other formats via Jinja templates. Versions of nbconvert up to and including 7.16.6 on Windows have a vulnerability in which converting a notebook containing SVG output to a PDF results in unauthorized code execution. Specifically, a third party can create a `inkscape.bat` file that defines a Windows batch script, capable of arbitrary code execution. When a user runs `jupyter nbconvert --to pdf` on a notebook containing SVG output to a PDF on a Windows platform from this directory, the `inkscape.bat` file is run unexpectedly. This issue has been patched in version 7.17.0. |
| Jupyter Core is a package for the core common functionality of Jupyter projects. When using Jupyter Core prior to version 5.8.0 on Windows, the shared `%PROGRAMDATA%` directory is searched for configuration files (`SYSTEM_CONFIG_PATH` and `SYSTEM_JUPYTER_PATH`), which may allow users to create configuration files affecting other users. Only shared Windows systems with multiple users and unprotected `%PROGRAMDATA%` are affected. Users should upgrade to Jupyter Core version 5.8.0 or later to receive a patch. Some other mitigations are available. As administrator, modify the permissions on the `%PROGRAMDATA%` directory so it is not writable by unauthorized users; or as administrator, create the `%PROGRAMDATA%\jupyter` directory with appropriately restrictive permissions; or as user or administrator, set the `%PROGRAMDATA%` environment variable to a directory with appropriately restrictive permissions (e.g. controlled by administrators _or_ the current user). |
| OAuthenticator provides plugins for JupyterHub to use common OAuth providers, as well as base classes for writing one's own Authenticators with any OAuth 2.0 provider. `GoogleOAuthenticator.hosted_domain` is used to restrict what Google accounts can be authorized access to a JupyterHub. The restriction is intented to be to Google accounts part of one or more Google organization verified to control specified domain(s). Prior to version 16.3.0, the actual restriction has been to Google accounts with emails ending with the domain. Such accounts could have been created by anyone which at one time was able to read an email associated with the domain. This was described by Dylan Ayrey (@dxa4481) in this [blog post] from 15th December 2023). OAuthenticator 16.3.0 contains a patch for this issue. As a workaround, restrict who can login another way, such as `allowed_users` or `allowed_google_groups`. |
| jupyterlab is an extensible environment for interactive and reproducible computing, based on the Jupyter Notebook Architecture. Prior to version 4.4.8, links generated with LaTeX typesetters in Markdown files and Markdown cells in JupyterLab and Jupyter Notebook did not include the noopener attribute. This is deemed to have no impact on the default installations. Theoretically users of third-party LaTeX-rendering extensions could find themselves vulnerable to reverse tabnabbing attacks if links generated by those extensions included target=_blank (no such extensions are known at time of writing) and they were to click on a link generated in LaTeX (typically visibly different from other links). This issue has been patched in version 4.4.8. |
| JupyterLab extension template is a `copier` template for JupyterLab extensions. Repositories created using this template with `test` option include `update-integration-tests.yml` workflow which has an RCE vulnerability. Extension authors hosting their code on GitHub are urged to upgrade the template to the latest version. Users who made changes to `update-integration-tests.yml`, accept overwriting of this file and re-apply your changes later. Users may wish to temporarily disable GitHub Actions while working on the upgrade. We recommend rebasing all open pull requests from untrusted users as actions may run using the version from the `main` branch at the time when the pull request was created. Users who are upgrading from template version prior to 4.3.0 may wish to leave out proposed changes to the release workflow for now as it requires additional configuration. |
| `jupyterhub-ltiauthenticator` is a JupyterHub authenticator for learning tools interoperability (LTI). LTI13Authenticator that was introduced in `jupyterhub-ltiauthenticator` 1.3.0 wasn't validating JWT signatures. This is believed to allow the LTI13Authenticator to authorize a forged request. Only users that has configured a JupyterHub installation to use the authenticator class `LTI13Authenticator` are affected. `jupyterhub-ltiauthenticator` version 1.4.0 removes LTI13Authenticator to address the issue. No known workarounds are available. |
| JupyterHub is an open source multi-user server for Jupyter notebooks. By tricking a user into visiting a malicious subdomain, the attacker can achieve an XSS directly affecting the former's session. More precisely, in the context of JupyterHub, this XSS could achieve full access to JupyterHub API and user's single-user server. The affected configurations are single-origin JupyterHub deployments and JupyterHub deployments with user-controlled applications running on subdomains or peer subdomains of either the Hub or a single-user server. This vulnerability is fixed in 4.1.0. |
| JupyterLab is an extensible environment for interactive and reproducible computing, based on the Jupyter Notebook and Architecture. Users of JupyterLab who click on a malicious link may get their `Authorization` and `XSRFToken` tokens exposed to a third party when running an older `jupyter-server` version. JupyterLab versions 4.1.0b2, 4.0.11, and 3.6.7 are patched. No workaround has been identified, however users should ensure to upgrade `jupyter-server` to version 2.7.2 or newer which includes a redirect vulnerability fix. |
| JupyterLab is an extensible environment for interactive and reproducible computing, based on the Jupyter Notebook and Architecture. This vulnerability depends on user interaction by opening a malicious Markdown file using JupyterLab preview feature. A malicious user can access any data that the attacked user has access to as well as perform arbitrary requests acting as the attacked user. JupyterLab version 4.0.11 has been patched. Users are advised to upgrade. Users unable to upgrade should disable the table of contents extension. |
| Jupyter Server Proxy is a Jupyter notebook server extension to proxy web services. Versions of Jupyter Server Proxy prior to 3.2.1 are vulnerable to Server-Side Request Forgery (SSRF). Any user deploying Jupyter Server or Notebook with jupyter-proxy-server extension enabled is affected. A lack of input validation allows authenticated clients to proxy requests to other hosts, bypassing the `allowed_hosts` check. Because authentication is required, which already grants permissions to make the same requests via kernel or terminal execution, this is considered low to moderate severity. Users may upgrade to version 3.2.1 to receive a patch or, as a workaround, install the patch manually. |
| The Jupyter Server provides the backend (i.e. the core services, APIs, and REST endpoints) for Jupyter web applications. Prior to version 1.15.4, unauthorized actors can access sensitive information from server logs. Anytime a 5xx error is triggered, the auth cookie and other header values are recorded in Jupyter Server logs by default. Considering these logs do not require root access, an attacker can monitor these logs, steal sensitive auth/cookie information, and gain access to the Jupyter server. Jupyter Server version 1.15.4 contains a patch for this issue. There are currently no known workarounds. |
| The Jupyter notebook is a web-based notebook environment for interactive computing. Prior to version 6.4.9, unauthorized actors can access sensitive information from server logs. Anytime a 5xx error is triggered, the auth cookie and other header values are recorded in Jupyter server logs by default. Considering these logs do not require root access, an attacker can monitor these logs, steal sensitive auth/cookie information, and gain access to the Jupyter server. Jupyter notebook version 6.4.x contains a patch for this issue. There are currently no known workarounds. |
| OAuthenticator is an OAuth token library for the JupyerHub login handler. CILogonOAuthenticator is provided by the OAuthenticator package, and lets users log in to a JupyterHub via CILogon. This is primarily used to restrict a JupyterHub only to users of a given institute. The allowed_idps configuration trait of CILogonOAuthenticator is documented to be a list of domains that indicate the institutions whose users are authorized to access this JupyterHub. This authorization is validated by ensuring that the *email* field provided to us by CILogon has a *domain* that matches one of the domains listed in `allowed_idps`.If `allowed_idps` contains `berkeley.edu`, you might expect only users with valid current credentials provided by University of California, Berkeley to be able to access the JupyterHub. However, CILogonOAuthenticator does *not* verify which provider is used by the user to login, only the email address provided. So a user can login with a GitHub account that has email set to `<something>@berkeley.edu`, and that will be treated exactly the same as someone logging in using the UC Berkeley official Identity Provider. The patch fixing this issue makes a *breaking change* in how `allowed_idps` is interpreted. It's no longer a list of domains, but configuration representing the `EntityID` of the IdPs that are allowed, picked from the [list maintained by CILogon](https://cilogon.org/idplist/). Users are advised to upgrade. |
| Jupyter Notebook is a web-based notebook environment for interactive computing. Prior to version 6.4.12, authenticated requests to the notebook server with `ContentsManager.allow_hidden = False` only prevented listing the contents of hidden directories, not accessing individual hidden files or files in hidden directories (i.e. hidden files were 'hidden' but not 'inaccessible'). This could lead to notebook configurations allowing authenticated access to files that may reasonably be expected to be disallowed. Because fully authenticated requests are required, this is of relatively low impact. But if a server's root directory contains sensitive files whose only protection from the server is being hidden (e.g. `~/.ssh` while serving $HOME), then any authenticated requests could access files if their names are guessable. Such contexts also necessarily have full access to the server and therefore execution permissions, which also generally grants access to all the same files. So this does not generally result in any privilege escalation or increase in information access, only an additional, unintended means by which the files could be accessed. Version 6.4.12 contains a patch for this issue. There are currently no known workarounds. |
| Jupyter Server provides the backend (i.e. the core services, APIs, and REST endpoints) for Jupyter web applications like Jupyter Notebook. Prior to version 1.17.1, if notebook server is started with a value of `root_dir` that contains the starting user's home directory, then the underlying REST API can be used to leak the access token assigned at start time by guessing/brute forcing the PID of the jupyter server. While this requires an authenticated user session, this URL can be used from a cross-site scripting payload or from a hooked or otherwise compromised browser to leak this access token to a malicious third party. This token can be used along with the REST API to interact with Jupyter services/notebooks such as modifying or overwriting critical files, such as .bashrc or .ssh/authorized_keys, allowing a malicious user to read potentially sensitive data and possibly gain control of the impacted system. This issue is patched in version 1.17.1. |
| Jupyter Core is a package for the core common functionality of Jupyter projects. Jupyter Core prior to version 4.11.2 contains an arbitrary code execution vulnerability in `jupyter_core` that stems from `jupyter_core` executing untrusted files in CWD. This vulnerability allows one user to run code as another. Version 4.11.2 contains a patch for this issue. There are no known workarounds. |
| The editor in IPython Notebook before 3.2.2 and Jupyter Notebook 4.0.x before 4.0.5 allows remote attackers to execute arbitrary JavaScript code via a crafted file, which triggers a redirect to files/, related to MIME types. |
