monkeyking/docs/source/security.rst

.. _notebook_security:

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 problem
-----------

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.

Unlike other programs, an Jupyter notebook document includes output.
Unlike other documents, that output exists in a context that can execute
code (via Javascript).

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
-  Untrusted Javascript is never executed
-  HTML and Javascript in Markdown cells are never trusted
-  **Outputs** generated by the user are trusted
-  Any other HTML or Javascript (in Markdown cells, output generated by
   others) is never 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::

    ~/.jupyter/profile_default/security/notebook_secret

.. note::

    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.

When a notebook is opened by a user, the server computes a signature
with the user's key, and compares it with the signature stored in the
notebook's metadata. If the signature matches, HTML and Javascript
output in the notebook will be trusted at load, otherwise it will be
untrusted.

Any output generated during an interactive session is trusted.

Updating trust
**************

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.

Explicit trust
**************

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 security@ipython.org.

If you prefer to encrypt your security reports,
you can use :download:`this PGP public key <ipython_security.asc>`.

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.

Javascript and CSS in Markdown cells
************************************

While never officially supported, it had become common practice to put
hidden Javascript or CSS styling in Markdown cells, so that they would
not be visible on the page. Since Markdown cells are now sanitized (by
`Google Caja <https://developers.google.com/caja>`__), all Javascript
(including click event handlers, etc.) and CSS will be stripped.

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
Markdown.

Collaboration
*************

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 trust`` or the notebook menu
   (annoying, but easy)
-  share a notebook secret, and use an 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:

.. sourcecode:: python

    c.NotebookApp.secret_file = "/path/to/notebook_secret"

in each profile, and only sharing the secret once per machine.