Security#

The information in this document focuses primarily on cloud based deployments. For on-premise deployments, additional security work that is specific to your installation method would also be required. Note that your specific installation’s security needs might be more or less stringent than what we can offer you here.

Brad Geesamen gave a wonderful talk titled Hacking and Hardening Kubernetes by Example at Kubecon NA 2017 and you can watch the talk. Highly recommended that you do so to understand the security issues you are up against when using Kubernetes to run JupyterHub.

Reporting a security issue#

If you find a security vulnerability in JupyterHub, 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 this PGP public key.

HTTPS#

This section describes how to enable HTTPS on your JupyterHub. The easiest way to do so is by using Let’s Encrypt, though we’ll also cover how to set up your own HTTPS credentials. For more information on HTTPS security see the certificates section of this blog post.

Set up your domain#

  1. Buy a domain name from a registrar. Pick whichever one you want.

  2. Create an A record from the domain you want to use, pointing to the EXTERNAL-IP of the proxy-public service. The exact way to do this will depend on the DNS provider that you’re using.

  3. Wait for the change to propagate. Propagation can take several minutes to several hours. Wait until you can type in the name of the domain you bought and it shows you the JupyterHub landing page.

    It is important that you wait - prematurely going to the next step might cause problems!

Set up automatic HTTPS#

JupyterHub uses Let’s Encrypt to automatically create HTTPS certificates for your deployment. This will cause your HTTPS certificate to automatically renew every few months. To enable this, make the following changes to your config.yaml file:

  1. Specify the two bits of information that we need to automatically provision HTTPS certificates - your domain name & a contact email address.

    proxy:
      https:
        enabled: true
        hosts:
          - <your-domain-name>
        letsencrypt:
          contactEmail: <your-email-address>
    
  2. Apply the config changes by running helm upgrade ...

  3. Wait for about a minute, now your hub should be HTTPS enabled!


NOTE:

If the proxy service is of type LoadBalancer, which it is by default, then a specific static IP address can be requested (if available) instead of a dynamically acquired one.
Although not essential for HTTPS, using a static IP address is a recommended practice for domain names referencing fixed IPs. This ensures the same IP address for multiple deployments. The IP can be provided like:

proxy:
  service:
    loadBalancerIP: xxx.xxx.xxx.xxx

More info about this can be found on the Configuration Reference page.


Set up manual HTTPS#

If you have your own HTTPS certificates & want to use those instead of the automatically provisioned Let’s Encrypt ones, that’s also possible. Note that this is considered an advanced option, so we recommend not doing it unless you have good reasons.

There are two ways to specify your manual certificate, directly in the config.yaml or by creating a Kubernetes secret.

Specify certificate in config.yaml#

  1. Add your domain name & HTTPS certificate info to your config.yaml

    proxy:
      https:
        enabled: true
        type: manual
        manual:
          key: |
            -----BEGIN RSA PRIVATE KEY-----
            ...
            -----END RSA PRIVATE KEY-----
          cert: |
            -----BEGIN CERTIFICATE-----
            ...
            -----END CERTIFICATE-----
    
  2. Apply the config changes by running helm upgrade ….

  3. Wait for about a minute, now your hub should be HTTPS enabled!

Specify certificate through Secret resource#

  1. Create a secret resource with type kubernetes.io/tls containing your certificate.

    kubectl create secret tls example-tls --key="tls.key" --cert="tls.crt"

  2. Add your domain and the name of your secret to your config.yaml.

    proxy:
      https:
        enabled: true
        hosts:
          - <your-domain-name>
        type: secret
        secret:
          name: example-tls
    
  3. Apply the config changes by running helm upgrade ….

  4. Wait for about a minute, now your hub should be HTTPS enabled!

Off-loading SSL to a Load Balancer#

In some environments with a trusted network, you may want to terminate SSL at a load balancer. If https is enabled, and proxy.https.type is set to offload, the HTTP and HTTPS front ends target the HTTP port from JupyterHub.

The HTTPS listener on the load balancer will need to be configured based on the provider. If you’re using AWS and a certificate provided by their certificate manager, your config.yml might look something like:

proxy:
  https:
    enabled: true
    type: offload
  service:
    annotations:
      # Certificate ARN
      service.beta.kubernetes.io/aws-load-balancer-ssl-cert: "arn:aws:acm:us-east-1:1234567891011:certificate/uuid"
      # The protocol to use on the backend, we use TCP since we're using websockets
      service.beta.kubernetes.io/aws-load-balancer-backend-protocol: "tcp"
      # Which ports should use SSL
      service.beta.kubernetes.io/aws-load-balancer-ssl-ports: "https"
      service.beta.kubernetes.io/aws-load-balancer-connection-idle-timeout: "3600"

Annotation options will vary by provider.

Confirm that your domain is running HTTPS#

There are many ways to confirm that a domain is running trusted HTTPS certificates. One options is to use the Qualys SSL Labs security report generator. Use the following URL structure to test your domain:

http://ssllabs.com/ssltest/analyze.html?d=<YOUR-DOMAIN>

Secure access to Helm#

Helm 3 supports the security, identity, and authorization features of modern Kubernetes. Helm’s permissions are evaluated using your kubeconfig file. Cluster administrators can restrict user permissions at whatever granularity they see fit.

Read more about organizing cluster access using kubeconfig files in the Kubernetes docs.

Delete the Kubernetes Dashboard#

The Kubernetes Dashboard gets created by default in many installations. Although the Dashboard contains useful information, the Dashboard also poses a security risk. We recommend deleting it and not using it for the time being until the Dashboard becomes properly securable.

You can mitigate this by deleting the Kubernetes Dashboard deployment from your cluster. This can be most likely performed with:

kubectl --namespace=kube-system delete deployment kubernetes-dashboard

In older clusters, you might have to do:

kubectl --namespace=kube-system delete rc kubernetes-dashboard

Use Role Based Access Control (RBAC)#

Kubernetes supports, and often requires, using Role Based Access Control (RBAC) to secure which pods / users can perform what kinds of actions on the cluster. RBAC rules can be set to provide users with minimal necessary access based on their administrative needs.

It is critical to understand that if RBAC is disabled, all pods are given root equivalent permission on the Kubernetes cluster and all the nodes in it. This opens up very bad vulnerabilites for your security.

As of the Helm chart v0.5 used with JupyterHub and BinderHub, the helm chart can natively work with RBAC enabled clusters. To provide sensible security defaults, we ship appropriate minimal RBAC rules for the various components we use. We highly recommend using these minimal or more restrictive RBAC rules.

If you want to disable the RBAC rules, for whatever reason, you can do so with the following snippet in your config.yaml:

rbac:
  enabled: false

We strongly discourage disabling the RBAC rules and remind you that this action will open up security vulnerabilities. However, some cloud providers may not support RBAC in which case you can disable it with this config.

Kubernetes API Access#

Allowing direct user access to the Kubernetes API can be dangerous. It allows users to grant themselves more privileges, access other users’ content without permission, run (unprofitable) bitcoin mining operations & various other not-legitimate activities. By default, we do not allow access to the service account credentials needed to access the Kubernetes API from user servers for this reason.

If you want to (carefully!) give access to the Kubernetes API to your users, you can do so with the following in your config.yaml:

singleuser:
  serviceAccountName: <service-account-name>

You can either manually create a service account for use by your users and specify the name of that here (recommended) or use default to give them access to the default service account for the namespace. You should ideally also (manually) set up RBAC rules for this service account to specify what permissions users will have.

This is a sensitive security issue (similar to writing sudo rules in a traditional computing environment), so be very careful.

There’s ongoing work on making this easier!

Audit Cloud Metadata server access#

Most cloud providers have a static IP that pods can reach to get metadata about the cloud. This metadata can contain very sensitive info and in the wrong hands allow attackers to take full control of your cluster and cloud resources. Due to this, it is critical to secure the metadata service from your user pods that could end up running malicious code without knowing it.

This presentation, 27 min in and onwards, provides more information on the dangers presented by this attack.

This Helm chart blocks access to this metadata in two ways by default, but you only need one.

Block metadata with a NetworkPolicy enforced by a NetworkPolicy controller#

If you have NetworkPolicy controller such as Calico in the Kubernetes cluster, it will enforce the NetworkPolicy resource created by this chart (singleuser.networkPolicy.*) that blocks user access to the metadata server. We recommend relying on this approach if you you had a NetworkPolicy controller, and then you can disable the other option.

Block metadata with a privileged initContainer running iptables#

If you can’t rely on the NetworkPolicy approach to block access to the metadata server, we suggest relying on this option. When singleuser.cloudMetadata.blockWithIptables is true as it is by default, an initContainer is added to the user pods. It will run with elevated privileges and use the iptables command line tool to block access to the metadata server.

# default configuration
singleuser:
  cloudMetadata:
    blockWithIptables: true
    ip: 169.254.169.254

Kubernetes Network Policies#

Important: When using network policies, you should be aware that a Kubernetes cluster may have partial, full, or no support for network policies. Kubernetes will silently ignore policies that aren’t supported. Please use caution before relying on network policy enforcement and verify the policies behave as expected, especially if you rely on them to restrict what users can access.

Kubernetes has optional support for network policies which lets you restrict how pods can communicate with each other and the outside world. This can provide additional security within JupyterHub, and can also be used to limit network access for users of JupyterHub.

By default, the JupyterHub helm chart enables network policies in 0.10 or later. They are disabled by default in 0.9 and earlier.

The JupyterHub chart has three network policies, one for each component (hub, proxy, single-user servers), which can be enabled and configured separately.

Enabling and disabling network policies#

By default, the JupyterHub helm chart enables network policies in 0.10 or later. They are disabled by default in 0.9 and earlier.

You can enable or disable enforcement of each network policy in config.yaml:

hub:
  networkPolicy:
    enabled: true # or false to disable
proxy:
  networkPolicy:
    enabled: true
singleuser:
  networkPolicy:
    enabled: true

Granting network access to jupyterhub pods (ingress)#

The chart’s network policy default behavior ensures that all of the jupyterhub components can talk to each other, so all of the following connections are allowed:

  • proxy ⇨ hub

  • proxy ⇨ singleuser

  • hub ⇨ proxy api

  • hub ⬄ singleuser

  • everything ⇨ DNS

and by default do not allow any other pods to talk to the jupyterhub components.

The network policies use label selectors that look like:

ingress:
  # allowed pods (hub.jupyter.org/network-access-hub) --> hub
  - from:
      - podSelector:
          matchLabels:
            hub.jupyter.org/network-access-hub: "true"

So if you are creating additional pods that want to talk to these, you can grant them access to jupyterhub components one by one by adding the right labels. Here is an example set of labels granting access to all jupyterhub components (i.e. the same behavior as without network policies):

metadata:
  name: my-service
  labels:
    hub.jupyter.org/network-access-hub: "true" # access the hub api
    hub.jupyter.org/network-access-proxy-http: "true" # access proxy public http endpoint
    hub.jupyter.org/network-access-proxy-api: "true" # access proxy api
    hub.jupyter.org/network-access-singleuser: "true" # access single-user servers directly

You can also add additional ingress rules to each network policy in your config.yaml. See the Kubernetes documentation for how to define ingress rules.

Limiting network access from pods (egress)#

By default, all of the pods allow all egress traffic, which means that code in each of the pods may make connections to anywhere in the cluster or on the Internet (unless that would be blocked by the ingress rules of the destination). This is very permissive. The default policy for all components allows all outbound (egress) network traffic, meaning JupyterHub users are able to connect to all resources inside and outside your network. You can override the egress configuration of each policy to make it more restrictive. For example, to restrict user outbound traffic to DNS, HTTP, and HTTPS:

singleuser:
  networkPolicy:
    enabled: true
    egress:
      - ports:
          - port: 53
            protocol: UDP
      - ports:
          - port: 80
      - ports:
          - port: 443

See the Kubernetes documentation for further information on defining policies.

Restricting Load Balancer Access#

By default any IP address can access your JupyterHub deployment through the load balancer service. In case you want to restrict which IP addresses are allowed to access the load balancer, you can specify a list of IP CIDR addresses in your config.yaml as follows:

proxy:
  service:
    loadBalancerSourceRanges:
      - 111.111.111.111/32
      - 222.222.222.222/32

This would restrict the access to only two IP addresses: 111.111.111.111 and 222.222.222.222.