Keystone for Other Services¶

System Scope¶

A system-scoped token implies the user has authorization to act on the deployment system. These tokens are useful for interacting with resources that affect the deployment as a whole, or exposes resources that may otherwise violate project or domain isolation.

Good examples of system-scoped resources include:

• Services: Service entities within keystone that describe the services deployed in a cloud.

• Endpoints: Endpoints that tell users where to find services deployed in a cloud.

• Hypervisors: Physical compute infrastructure that hosts instances where the instances may, or may not, be owned by the same project.

Domain Scope¶

A domain-scoped token carries a user’s authorization on a specific domain. Ideally, these tokens would be useful for listing resources aggregated across all projects with that domain. They can also be useful for creating entities that must belong to a domain. Users and groups are good examples of this. The following is an example of how a domain-scoped token could be used against a service.

Assume a domain exists called Foo, and it contains projects called bar and baz. Let’s also assume both projects contain instances running a workload. If Alice is a domain administrator for Foo, she should be able to pass her domain-scoped token to nova and ask for a list of instances. If nova supports domain-scoped tokens, the response would contain all instances in projects bar and baz.

Another example of using a domain-scoped token would be if Alice wanted to create a new project in domain Foo. When Alice sends a request to create a new project (POST /v3/projects), keystone should ensure the new project is created within the Foo domain, since that’s the authorization associated to Alice’s token.

Project Scope¶

A project-scoped token carries the role assignments a user has on a project. This type of scope is great for managing resources that fit nicely within project boundaries. Good examples of project-level resources that can be managed with project-scoped tokens are:

• Instances: Virtual compute servers that require a project association in order to be created.

• Volumes: Storage devices that can be attached to instances.

Unscoped¶

An unscoped token is a token that proves authentication, but doesn’t carry any authorization. Users can obtain unscoped tokens by simply proving their identity with credentials. Unscoped tokens can be exchanged for any of the various scoped tokens if a user has authorization on the requested scope.

An example of where unscoped tokens are specifically useful is when users perform federated authentication. First, a user will receive an unscoped token pending successful federated authentication, which they can use to query keystone for a list of projects they’re allowed to access. Then they can exchange their unscoped token for a project-scoped token allowing them to perform actions within a particular project.

Flexibility for exposing your work¶

OpenStack provides a rich set of APIs and functionality. We wrote some APIs with the intent of managing the deployment hardware, otherwise referred to as the deployment system. We wrote others to orchestrate resources in a project or a domain. Some APIs even operate on multiple levels. Since we use tokens to authorize a user’s actions against a given service, they needed to handle different scope targets. For example, when a user asks for a new instance, we expect that instance to belong to a project; thus we expect a project relayed through the token’s scope. This idea is fundamental in providing isolation, or tenancy, between projects in OpenStack.

Initially, keystone only supported the ability to generate project-scoped tokens as a product of a user having a role assignment on a project. Consequently, services had no other choice but to require project-scoped tokens to protect almost all of their APIs, even if that wasn’t an ideal option. Using project-scoped tokens to protect APIs they weren’t designed to protect required operators to write custom policy checks to secure those APIs. An example showcases this more clearly.

Let’s assume an operator wanted to create a read-only role. Users with the reader role would be able to list things owned by the project, like instances, volumes, or snapshots. The operator also wants to have a read-only role for fellow operators or auditors, allowing them to view hypervisor information or endpoints and services. Reusing the existing reader role is difficult because users with that role on a project shouldn’t see data about hypervisors, which would violate tenancy. Operators could create a new role called operator or system-reader, but then those users would still need to have that role assigned on a project to access deployment-level APIs. The concept of getting project-scoped tokens to access deployment-level resources makes no sense for abstractions like hypervisors that cannot belong to a single project. Furthermore, this requires deployers to maintain all of this in policy files. You can quickly see how only using project-scope limits our ability to protect APIs without convoluted or expensive-to-maintain solutions.

Each scope offered by keystone helps operators and users avoid these problems by giving you, the developer, multiple options for protecting APIs you write, instead of the one-size-fits-all approach we outgrew. You no longer have to hope an operator configures policy correctly so their users can consume the feature you wrote. The more options you have for protecting an API, the easier it is to provide default policies that expose more of your work to users safely.

Less custom code¶

Another crucial benefit of authorization scopes offered by keystone is less custom code. For example, if you were writing an API to manage a deployment-level resource but only allowed to consume project-scoped tokens, how would you determine an operator from an end user? Would you attempt to standardize a role name? Would you look for a unique project in the token’s scope? Would these checks be configurable in policy or hardcoded in your service?

Chances are, different services will come up with different, inconsistent solution for the same problem. These inconsistencies make it harder for developers to context switch between services that process things differently. Users also suffer from inconsistencies by having to maintain a mental mapping of different behavior between services. Having different scopes at your disposal, through keystone tokens, lets you build on a standard solution that other projects also consume, reducing the likelihood of accidentally developing inconsistencies between services. This commonality also gives us a similar set of terms we can use when we communicate with each other and users, allowing us to know what someone means by a system-admin and how that is different from a project-admin.

Reusable default roles¶

When OpenStack services originally started developing a policy enforcement engine to protect APIs, the only real concrete role we assumed to be present in the deployment was a role called admin. Because we assumed this, we were able to write policies with admin as the default. Keystone also took steps to ensure it had a role with that name during installation. While making this assumption is beneficial for some APIs, having only one option is underwhelming and leaves many common policy use cases for operators to implement through policy overrides. For example, a typical ask from operators is to have a read-only role, that only allows users with that role on a target to view its contents, restricting them from making writable changes. Another example is a membership role that isn’t the administrator. To put it clearly, a user with a member role assignment on a project may create new storage volumes, but they’re unable to perform backups. Users with the admin role on a project can access the backups functionality.

Keep in mind, the examples above are only meant to describe the need for other roles besides admin in a deployment. Service developers should be able to reuse these definitions for similar APIs and assume those roles exist. As a result, keystone implemented support for ensuring the admin, member, and reader roles are present during the installation process, specifically when running keystone-manage bootstrap. Additionally, keystone creates a relationship among these roles that make them easier for service developers to use. During creation, keystone implies that the admin role is a superset of the member role, and the member role is a superset of the reader role. The benefit may not be obvious, but what this means is that users with the admin role on a target also have the member and reader roles generated in their token. Similarly, users with the member role also have the reader role relayed in their token, even though they don’t have a direct role assignment using the reader role. This subtle relationship allows developers to use a short-hand notation for writing policies. The following assumes foobar is a project-level resource available over a service API and is protected by policies using generic roles:

"service:foobar:get": "role:admin OR role:member OR role:reader"
"service:foobar:list": "role:admin OR role:member OR role:reader"
"service:foobar:create": "role:admin OR role:member"
"service:foobar:update": "role:admin OR role:member"
"service:foobar:delete": "role:admin"

The following policies are functionally equivalent to the policies above, but rely on the implied relationship between the three roles, resulting in a simplified check string expression:

"service:foobar:get": "role:reader"
"service:foobar:list": "role:reader"
"service:foobar:create": "role:member"
"service:foobar:update": "role:member"
"service:foobar:delete": "role:admin"

Ruthless Testing¶

Policy enforcement implementations vary greatly across OpenStack services. Some enforce authorization near the top of the API while others push the logic deeper into the service. Differences and intricacies between services make testing imperative to adopt a uniform, consistent approach. Positive and negative protection testing helps us assert users with specific roles can, or cannot, access APIs. A protection test is similar to an API, or functional test, but purely focused on the authoritative outcome. In other words, protection testing is sufficient when we can assert that a user is or isn’t allowed to do or see something. For example, a user with a role assignment on project foo shouldn’t be able to list volumes in project bar. A user with a role on a project shouldn’t be able to modify entries in the service catalog. Users with a reader role on the system, a domain, or a project shouldn’t be able to make writable changes. You commonly see protection tests conclude with an assertion checking for a successful response code or an HTTP 403 Forbidden.

If your service has minimal or non-existent protection coverage, you should start by introducing tests that exercise the current default policies, whatever those are. This step serves three significant benefits.

First, it puts us in the shoes of our users from an authorization perspective, allowing us to see the surface of the API a user has access to with a given assignment. This information helps audit the API to make sure the user has all the authorization to do what they need, but nothing more. We should note inconsistencies here as feedback that we should fix, especially since operators are probably attempting to fix these inconsistencies through customized policy today.

Second, a collection of protection tests make sure we don’t have unwanted security-related regressions. Imagine making a policy change that introduced a regression and allowed a user to access an API and data they aren’t supposed to see. Conversely, imagine a patch that accidentally tightened restriction on an API that resulted in a broken workflow for users. Testing makes sure we catch cases like this early and handle them accordingly.

Finally, protection tests help us use test-driven development to evolve policy enforcement. We can make a change and assert the behavior using tests locally, allowing us to be proactive and not reactive in our authoritative business logic.

To get started, refer to the oslo.policy documentation that describes techniques for writing useful protection tests. This document also describes some historical context you might recognize in your service and how you should deal with it. You can also look at protection tests examples in other services, like keystone or cinder. Note that these examples test the three default roles provided from keystone (reader, member, and admin) against the three scopes keystone offers, allowing for nine different personas without operators creating roles specific to their deployment. We recommend testing these personas where applicable in your service:

• project reader

• project member

• project admin

• system reader

• system member

• system admin

• domain reader

• domain member

• domain admin

Auditing the API¶

After going through the API and adding protection tests, you should have a good idea of how each API is or isn’t exposed to end users with different role assignments. You might also have a list of areas where policies could be improved. For example, maybe you noticed an API in your service that consumes project-scoped tokens to protect a system-level resource. If your service has a bug tracker, you can use it to document these gaps. The keystone team went through this exercise and used bugs. Feel free to use these bug reports as a template for describing gaps in policy enforcement. For example, if your service has APIs for listing or getting resources, you could implement the reader role on that API.

Setting scope types¶

With testing in place and gaps documented, you can start refactoring. The first step is to start using oslo.policy for scope checking, which reduces complexity in your service by having a library do some lifting for you. For example, if you have an API that requires a project-scoped token, you can set the scope of the policy protecting that API accordingly. If an instance of RuleDefault has scope associated to it, oslo.policy checks that it matches the scope of the token used to make the request. This behavior is configurable, allowing operators to turn it on once all policies have a scope type and once operators have audited their assignments and educated their users on how to get the scope necessary to access an API. Once that happens, an operator can configure oslo.policy to reject requests made with the wrong scope. Otherwise, oslo.policy logs a warning for operators that describes the mismatched scope.

The oslo.policy library provides documentation for setting scope. You can also see keystone examples or placement examples of setting scope types on policies.

If you have difficulty deciding which scope an API or resource requires, try thinking about the intended user. Are they an operator managing the deployment? Then you might choose system. Are they an end user meant to operate only within a given project? Then project scope is likely what you need. Scopes aren’t mutually exclusive.

You may have APIs that require more than one scope. Keystone’s user and project APIs are good examples of resources that need different scopes. For example, a system administrator should be able to list all users in the system, but domain administrators should only be able to list users within their domain. If you have an API that falls into this category, you may be required to implicitly filter responses based on the scope type. If your service uses oslo.context and keystonemiddleware, you can query a RequestContext object about the token’s scope. There are keystone patches that show how to filter responses according to scope using oslo.context, in case you need inspiration.

If you still can’t seem to find a solution, don’t hesitate to send a note to the OpenStack Discuss mailing list tagged with [keystone] or ask in #openstack-keystone on IRC.

Rewriting check string¶

With oslo.policy able to check scope, you can start refactoring check strings where-ever necessary. For example, adding support for default roles or removing hard-coded is_admin: True checks. Remember that oslo.policy provides deprecation tooling that makes upgrades easier for operators. Specifically, upgrades are made easier by combining old defaults or overrides with the new defaults using a logical OR. We encourage you to use the available deprecation tooling when you change policy names or check strings. You can refer to examples that show you how to build descriptive rule objects using all the default roles from keystone and consuming scopes.

Communication¶

Communicating early and often is never a bad thing, especially when a change is going to impact operators. At this point, it’s crucial to emphasize the changes you’ve made to policy enforcement in your service. Release notes are an excellent way to signal changes to operators. You can find examples when keystone implemented support for default roles. Additionally, you might have operators or users ask questions about the various scopes or what they mean. Don’t hesitate to refer them to keystone’s scope documentation.

Service tokens¶

Service tokens are a feature where the auth_token middleware will also accept a service token in the X-Service-Token header. It does the same thing with the service token as the user token, but the results of the token are passed separately in environment variables for the service token (the service user, project, and roles). If the service knows about these then it can put this info in its “context” and use it for policy checks. For example, assuming there’s a special policy rule called service_role that works like the role rule except checks the service roles, you could have an oslo.policy rule like service_role:service and user_id:%(user_id)s such that a service token is required along with the user owning the object.