Security in Jupyter notebooks¶
As Jupyter notebooks become more popular for sharing and collaboration, the potential for malicious people to attempt to exploit the notebook for their nefarious purposes increases. IPython 2.0 introduces a security model to prevent execution of untrusted code without explicit user input.
The whole point of Jupyter is arbitrary code execution. We have no desire to limit what can be done with a notebook, which would negatively impact its utility.
The security problem we need to solve is that no code should execute just because a user has opened a notebook that they did not write. Like any other program, once a user decides to execute code in a notebook, it is considered trusted, and should be allowed to do anything.
Our security model¶
- Untrusted HTML is always sanitized
- Outputs generated by the user are trusted
- The central question of trust is “Did the current user do this?”
The details of trust¶
Jupyter notebooks store a signature in metadata, which is used to answer the question “Did the current user do this?”
This signature is a digest of the notebooks contents plus a secret key, known only to the user. The secret key is a user-only readable file in the Jupyter profile’s security directory. By default, this is:
The notebook secret being stored in the profile means that loading a notebook in another profile results in it being untrusted, unless you copy or symlink the notebook secret to share it across profiles.
Any output generated during an interactive session is trusted.
A notebook’s trust is updated when the notebook is saved. If there are
any untrusted outputs still in the notebook, the notebook will not be
trusted, and no signature will be stored. If all untrusted outputs have
been removed (either via
Clear Output or re-execution), then the
notebook will become trusted.
While trust is updated per output, this is only for the duration of a single session. A notebook file on disk is either trusted or not in its entirety.
Sometimes re-executing a notebook to generate trusted output is not an option, either because dependencies are unavailable, or it would take a long time. Users can explicitly trust a notebook in two ways:
At the command-line, with:
jupyter trust /path/to/notebook.ipynb
After loading the untrusted notebook, with
File / Trust Notebook
These two methods simply load the notebook, compute a new signature with the user’s key, and then store the newly signed notebook.
Reporting security issues¶
If you find a security vulnerability in Jupyter, either a failure of the code to properly implement the model described here, or a failure of the model itself, please report it to firstname.lastname@example.org.
If you prefer to encrypt your security reports,
you can use
this PGP public key.
Affected use cases¶
Some use cases that work in Jupyter 1.0 will become less convenient in 2.0 as a result of the security changes. We do our best to minimize these annoyance, but security is always at odds with convenience.
We plan to provide a mechanism for notebook themes, but in the meantime
styling the notebook can only be done via either
custom.css or CSS
in HTML output. The latter only have an effect if the notebook is
trusted, because otherwise the output will be sanitized just like
When collaborating on a notebook, people probably want to see the outputs produced by their colleagues’ most recent executions. Since each collaborator’s key will differ, this will result in each share starting in an untrusted state. There are three basic approaches to this:
- re-run notebooks when you get them (not always viable)
- explicitly trust notebooks via
jupyter trustor the notebook menu (annoying, but easy)
- share a notebook secret, and use a Jupyter profile dedicated to the collaboration while working on the project.
Multiple profiles or machines¶
Since the notebook secret is stored in a profile directory by default, opening a notebook with a different profile or on a different machine will result in a different key, and thus be untrusted. The only current way to address this is by sharing the notebook secret. This can be facilitated by setting the configurable:
c.NotebookApp.secret_file = "/path/to/notebook_secret"
in each profile, and only sharing the secret once per machine.