IPython Documentation

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This documentation is for an old version of IPython. You can find docs for newer versions here.

Security details of IPython


This section is not thorough, and IPython.kernel.zmq needs a thorough security audit.

IPython’s IPython.kernel.zmq package exposes the full power of the Python interpreter over a TCP/IP network for the purposes of parallel computing. This feature brings up the important question of IPython’s security model. This document gives details about this model and how it is implemented in IPython’s architecture.

Process and network topology

To enable parallel computing, IPython has a number of different processes that run. These processes are discussed at length in the IPython documentation and are summarized here:

  • The IPython engine. This process is a full blown Python interpreter in which user code is executed. Multiple engines are started to make parallel computing possible.
  • The IPython hub. This process monitors a set of engines and schedulers, and keeps track of the state of the processes. It listens for registration connections from engines and clients, and monitor connections from schedulers.
  • The IPython schedulers. This is a set of processes that relay commands and results between clients and engines. They are typically on the same machine as the controller, and listen for connections from engines and clients, but connect to the Hub.
  • The IPython client. This process is typically an interactive Python process that is used to coordinate the engines to get a parallel computation done.

Collectively, these processes are called the IPython cluster, and the hub and schedulers together are referred to as the controller.

These processes communicate over any transport supported by ZeroMQ (tcp,pgm,infiniband,ipc) with a well defined topology. The IPython hub and schedulers listen on sockets. Upon starting, an engine connects to a hub and registers itself, which then informs the engine of the connection information for the schedulers, and the engine then connects to the schedulers. These engine/hub and engine/scheduler connections persist for the lifetime of each engine.

The IPython client also connects to the controller processes using a number of socket connections. As of writing, this is one socket per scheduler (4), and 3 connections to the hub for a total of 7. These connections persist for the lifetime of the client only.

A given IPython controller and set of engines engines typically has a relatively short lifetime. Typically this lifetime corresponds to the duration of a single parallel simulation performed by a single user. Finally, the hub, schedulers, engines, and client processes typically execute with the permissions of that same user. More specifically, the controller and engines are not executed as root or with any other superuser permissions.

Application logic

When running the IPython kernel to perform a parallel computation, a user utilizes the IPython client to send Python commands and data through the IPython schedulers to the IPython engines, where those commands are executed and the data processed. The design of IPython ensures that the client is the only access point for the capabilities of the engines. That is, the only way of addressing the engines is through a client.

A user can utilize the client to instruct the IPython engines to execute arbitrary Python commands. These Python commands can include calls to the system shell, access the filesystem, etc., as required by the user’s application code. From this perspective, when a user runs an IPython engine on a host, that engine has the same capabilities and permissions as the user themselves (as if they were logged onto the engine’s host with a terminal).

Secure network connections


ZeroMQ provides exactly no security. For this reason, users of IPython must be very careful in managing connections, because an open TCP/IP socket presents access to arbitrary execution as the user on the engine machines. As a result, the default behavior of controller processes is to only listen for clients on the loopback interface, and the client must establish SSH tunnels to connect to the controller processes.


If the controller’s loopback interface is untrusted, then IPython should be considered vulnerable, and this extends to the loopback of all connected clients, which have opened a loopback port that is redirected to the controller’s loopback port.


Since ZeroMQ provides no security, SSH tunnels are the primary source of secure connections. A connector file, such as ipcontroller-client.json, will contain information for connecting to the controller, possibly including the address of an ssh-server through with the client is to tunnel. The Client object then creates tunnels using either [OpenSSH] or [Paramiko], depending on the platform. If users do not wish to use OpenSSH or Paramiko, or the tunneling utilities are insufficient, then they may construct the tunnels themselves, and simply connect clients and engines as if the controller were on loopback on the connecting machine.


To protect users of shared machines, [HMAC] digests are used to sign messages, using a shared key.

The Session object that handles the message protocol uses a unique key to verify valid messages. This can be any value specified by the user, but the default behavior is a pseudo-random 128-bit number, as generated by uuid.uuid4(). This key is used to initialize an HMAC object, which digests all messages, and includes that digest as a signature and part of the message. Every message that is unpacked (on Controller, Engine, and Client) will also be digested by the receiver, ensuring that the sender’s key is the same as the receiver’s. No messages that do not contain this key are acted upon in any way. The key itself is never sent over the network.

There is exactly one shared key per cluster - it must be the same everywhere. Typically, the controller creates this key, and stores it in the private connection files ipython-{engine|client}.json. These files are typically stored in the ~/.ipython/profile_<name>/security directory, and are maintained as readable only by the owner, just as is common practice with a user’s keys in their .ssh directory.


It is important to note that the signatures protect against unauthorized messages, but, as there is no encryption, provide exactly no protection of data privacy. It is possible, however, to use a custom serialization scheme (via Session.packer/unpacker traits) that does incorporate your own encryption scheme.

Specific security vulnerabilities

There are a number of potential security vulnerabilities present in IPython’s architecture. In this section we discuss those vulnerabilities and detail how the security architecture described above prevents them from being exploited.

Unauthorized clients

The IPython client can instruct the IPython engines to execute arbitrary Python code with the permissions of the user who started the engines. If an attacker were able to connect their own hostile IPython client to the IPython controller, they could instruct the engines to execute code.

On the first level, this attack is prevented by requiring access to the controller’s ports, which are recommended to only be open on loopback if the controller is on an untrusted local network. If the attacker does have access to the Controller’s ports, then the attack is prevented by the capabilities based client authentication of the execution key. The relevant authentication information is encoded into the JSON file that clients must present to gain access to the IPython controller. By limiting the distribution of those keys, a user can grant access to only authorized persons, just as with SSH keys.

It is highly unlikely that an execution key could be guessed by an attacker in a brute force guessing attack. A given instance of the IPython controller only runs for a relatively short amount of time (on the order of hours). Thus an attacker would have only a limited amount of time to test a search space of size 2**128. For added security, users can have arbitrarily long keys.


If the attacker has gained enough access to intercept loopback connections on either the controller or client, then a duplicate message can be sent. To protect against this, recipients only allow each signature once, and consider duplicates invalid. However, the duplicate message could be sent to another recipient using the same key, and it would be considered valid.

Unauthorized engines

If an attacker were able to connect a hostile engine to a user’s controller, the user might unknowingly send sensitive code or data to the hostile engine. This attacker’s engine would then have full access to that code and data.

This type of attack is prevented in the same way as the unauthorized client attack, through the usage of the capabilities based authentication scheme.

Unauthorized controllers

It is also possible that an attacker could try to convince a user’s IPython client or engine to connect to a hostile IPython controller. That controller would then have full access to the code and data sent between the IPython client and the IPython engines.

Again, this attack is prevented through the capabilities in a connection file, which ensure that a client or engine connects to the correct controller. It is also important to note that the connection files also encode the IP address and port that the controller is listening on, so there is little chance of mistakenly connecting to a controller running on a different IP address and port.

When starting an engine or client, a user must specify the key to use for that connection. Thus, in order to introduce a hostile controller, the attacker must convince the user to use the key associated with the hostile controller. As long as a user is diligent in only using keys from trusted sources, this attack is not possible.


I may be wrong, the unauthorized controller may be easier to fake than this.

Other security measures

A number of other measures are taken to further limit the security risks involved in running the IPython kernel.

First, by default, the IPython controller listens on random port numbers. While this can be overridden by the user, in the default configuration, an attacker would have to do a port scan to even find a controller to attack. When coupled with the relatively short running time of a typical controller (on the order of hours), an attacker would have to work extremely hard and extremely fast to even find a running controller to attack.

Second, much of the time, especially when run on supercomputers or clusters, the controller is running behind a firewall. Thus, for engines or client to connect to the controller:

  • The different processes have to all be behind the firewall.


  • The user has to use SSH port forwarding to tunnel the connections through the firewall.

In either case, an attacker is presented with additional barriers that prevent attacking or even probing the system.


IPython’s architecture has been carefully designed with security in mind. The capabilities based authentication model, in conjunction with SSH tunneled TCP/IP channels, address the core potential vulnerabilities in the system, while still enabling user’s to use the system in open networks.