During the authentication process an identity provider (IdP) will present keystone with a set of user attributes about the user that is authenticating. For example, in the SAML2 flow this comes to keystone in the form of a SAML document.
The attributes are typically processed by third-party software and are presented to keystone as environment variables. The original document from the IdP is generally not available to keystone. This is how the Shibboleth and Mellon implementations work.
The mapping format described in this document maps these environment variables to a local keystone user. The mapping may also define group membership for that user and projects the user can access.
An IdP has exactly one mapping specified per protocol. Mappings themselves can be used multiple times by different combinations of IdP and protocol.
A mapping looks as follows:
{
"rules": [
{
"local": [
{
<user>
[<group>]
[<project>]
}
],
"remote": [
{
<match>
[<condition>]
}
]
}
]
}
A mapping is selected by IdP and protocol. Then keystone takes the mapping and processes each rule sequentially stopping after the first matched rule. A rule is matched when all of its conditions are met.
First keystone evaluates each condition from the rule’s remote property to see if the rule is a match. If it is a match, keystone saves the data captured by each of the matches from the rule’s remote property in an ordered list. We call these matches direct mappings since they can be used in the next step.
After the rule is found using the rule’s conditions and a list of direct mappings is stored, keystone begins processing the rule’s local property. Each object in the local property is collapsed into a single JSON object. For example:
{
"local": [
{
"user": {...}
},
{
"projects": [...]
},
]
}
becomes:
{
"local": {
"user": {...}
"projects": [...]
},
}
when the same property exists in the local multiple times the first occurrence wins:
{
"local": [
{
"user": {#first#}
},
{
"projects": [...]
},
{
"user": {#second#}
},
]
}
becomes:
{
"local": {
"user": {#first#}
"projects": [...]
},
}
We take this JSON object and then recursively process it in order to apply the direct mappings. This is simply looking for the pattern {#} and substituting it with values from the direct mappings list. The index of the direct mapping starts at zero.
The mapping engine can be tested before creating a federated setup. It can be
tested with the keystone-manage mapping_engine
command:
$ keystone-manage mapping_engine --rules <file> --input <file>
Note
Although the rules file is formatted as JSON, the input file of assertion data is formatted as individual lines of key: value pairs, see keystone-manage mapping_engine –help for details.
Mappings support 5 different types of conditions:
empty
: The rule is matched to all claims containing the remote attribute type.
This condition does not need to be specified.
any_one_of
: The rule is matched only if any of the specified strings appear
in the remote attribute type. Condition result is boolean, not the argument that
is passed as input.
not_any_of
: The rule is not matched if any of the specified strings appear
in the remote attribute type. Condition result is boolean, not the argument that
is passed as input.
blacklist
: The rule allows all except a specified set of groups. Condition
result is the argument(s) passed as input minus what was matched in the
blacklist.
whitelist
: The rules allows a specified set of groups. Condition result is
the argument(s) passed as input and is/are also present in the whitelist.
Note
empty
, blacklist
and whitelist
are the only conditions that can
be used in direct mapping ({0}, {1}, etc.)
Multiple conditions can be combined to create a single rule.
The following are all examples of mapping rule types.
{
"rules": [
{
"local": [
{
"user": {
"name": "{0} {1}",
"email": "{2}"
},
"group": {
"name": "{3}",
"domain": {
"id": "0cd5e9"
}
}
}
],
"remote": [
{
"type": "FirstName"
},
{
"type": "LastName"
},
{
"type": "Email"
},
{
"type": "OIDC_GROUPS"
}
]
}
]
}
Note
The numbers in braces {} are indices, they map in order. For example:
- Mapping to user with the name matching the value in remote attribute FirstName
- Mapping to user with the name matching the value in remote attribute LastName
- Mapping to user with the email matching value in remote attribute Email
- Mapping to a group(s) with the name matching the value(s) in remote attribute OIDC_GROUPS
Groups can have multiple values. Each value must be separated by a ; Example: OIDC_GROUPS=developers;testers
In <other_condition>
shown below, please supply one of the following:
any_one_of
, or not_any_of
.
{
"rules": [
{
"local": [
{
"user": {
"name": "{0}"
},
"group": {
"id": "0cd5e9"
}
}
],
"remote": [
{
"type": "UserName"
},
{
"type": "HTTP_OIDC_GROUPIDS",
"<other_condition>": [
"HTTP_OIDC_EMAIL"
]
}
]
}
]
}
In <other_condition>
shown below, please supply one of the following:
blacklist
, or whitelist
.
{
"rules": [
{
"local": [
{
"user": {
"name": "{0}"
}
},
{
"groups": "{1}",
"domain": {
"id": "0cd5e9"
}
}
],
"remote": [
{
"type": "UserName"
},
{
"type": "HTTP_OIDC_GROUPIDS",
"<other_condition>": [
"me@example.com"
]
}
]
}
]
}
Note
If the user id and name are not specified in the mapping, the server tries to
directly map REMOTE_USER
environment variable. If this variable is also
unavailable the server returns an HTTP 401 Unauthorized error.
Group ids and names can be provided in the local section:
{
"local": [
{
"group": {
"id":"0cd5e9"
}
}
]
}
{
"local": [
{
"group": {
"name": "developer_group",
"domain": {
"id": "abc1234"
}
}
}
]
}
{
"local": [
{
"group": {
"name": "developer_group",
"domain": {
"name": "private_cloud"
}
}
}
]
}
If a mapping is valid you will receive the following output:
{
"group_ids": "[<group-ids>]",
"user":
{
"domain":
{
"id": "Federated" or "<local-domain-id>"
},
"type": "ephemeral" or "local",
"name": "<local-user-name>",
"id": "<local-user-id>"
},
"group_names":
[
{
"domain":
{
"name": "<domain-name>"
},
"name":
{
"name": "[<groups-names>]"
}
}
{
"domain":
{
"name": "<domain-name>"
},
"name":
{
"name": "[<groups-names>]"
}
}
]
}
The type
parameter specifies the type of user being mapped. The 2 possible
user types are local
and ephemeral
.“local“ is displayed if the user
has a domain specified. The user is treated as existing in the backend, hence
the server will fetch user details (id, name, roles, groups).“ephemeral“ is
displayed for a user that does not exist in the backend.
The id
parameter in the service domain specifies the domain a user belongs
to. Federated
will be displayed if no domain is specified in the local rule.
User is deemed ephemeral and becomes a member of service domain named Federated
.
If the domain is specified the local domain’s id will be displayed.
If the mapped user is local, mapping engine will discard further group
assigning and return set of roles configured for the user.
Note
Domain Federated
is a service domain - it cannot be listed, displayed,
added or deleted. There is no need to perform any operation on it prior to
federation configuration.
Regular expressions can be used in a mapping by specifying the regex
key, and
setting it to true
.
{
"rules": [
{
"local": [
{
"user": {
"name": "{0}"
},
"group": {
"id": "0cd5e9"
}
},
],
"remote": [
{
"type": "UserName"
},
{
"type": "HTTP_OIDC_GROUPIDS",
"any_one_of": [
".*@yeah.com$"
]
"regex": true
}
]
}
]
}
This allows any user with a claim containing a key with any value in
HTTP_OIDC_GROUPIDS
to be mapped to group with id 0cd5e9
.
Combinations of mappings conditions can also be done.
empty
, any_one_of
, and not_any_of
can all be used in the same rule,
but cannot be repeated within the same condition. any_one_of
and
not_any_of
are mutually exclusive within a condition’s scope. So are
whitelist
and blacklist
.
{
"rules": [
{
"local": [
{
"user": {
"name": "{0}"
},
"group": {
"id": "0cd5e9"
}
},
],
"remote": [
{
"type": "UserName"
},
{
"type": "cn=IBM_Canada_Lab",
"not_any_of": [
".*@naww.com$"
],
"regex": true
},
{
"type": "cn=IBM_USA_Lab",
"any_one_of": [
".*@yeah.com$"
]
"regex": true
}
]
}
]
}
As before group names and users can also be provided in the local section.
This allows any user with the following claim information to be mapped to group with id 0cd5e9.
{"UserName":"<any_name>@yeah.com"}
{"cn=IBM_USA_Lab":"<any_name>@yeah.com"}
{"cn=IBM_Canada_Lab":"<any_name>@yeah.com"}
The following claims will be mapped:
Multiple rules can also be utilized in a mapping.
{
"rules": [
{
"local": [
{
"user": {
"name": "{0}"
},
"group": {
"name": "non-contractors",
"domain": {
"id": "abc1234"
}
}
}
],
"remote": [
{
"type": "UserName"
},
{
"type": "orgPersonType",
"not_any_of": [
"Contractor",
"SubContractor"
]
}
]
},
{
"local": [
{
"user": {
"name": "{0}"
},
"group": {
"name": "contractors",
"domain": {
"id": "abc1234"
}
}
}
],
"remote": [
{
"type": "UserName"
},
{
"type": "orgPersonType",
"any_one_of": [
"Contractor",
"SubContractor"
]
}
]
}
]
}
The above assigns groups membership basing on orgPersonType
values:
Contractor
nor SubContractor
will belong to the non-contractors
group.Contractor or ``SubContractor
will belong to the contractors
group.Rules are additive, so permissions will only be granted for the rules that succeed. All the remote conditions of a rule must be valid.
When using multiple rules you can specify more than one effective user identification, but only the first match will be considered and the others ignored ordered from top to bottom.
Since rules are additive one can specify one user identification and this will also work. The best practice for multiple rules is to create a rule for just user and another rule for just groups. Below is rules example repeated but with global username mapping.
{
"rules": [{
"local": [{
"user": {
"id": "{0}"
}
}],
"remote": [{
"type": "UserType"
}]
},
{
"local": [{
"group": {
"name": "non-contractors",
"domain": {
"id": "abc1234"
}
}
}],
"remote": [{
"type": "orgPersonType",
"not_any_of": [
"Contractor",
"SubContractor"
]
}]
},
{
"local": [{
"group": {
"name": "contractors",
"domain": {
"id": "abc1234"
}
}
}],
"remote": [{
"type": "orgPersonType",
"any_one_of": [
"Contractor",
"SubContractor"
]
}]
}]
}
The mapping engine has the ability to aid in the auto-provisioning of resources when a federated user authenticates for the first time. This can be achieved using a specific mapping syntax that the mapping engine can parse and ultimately make decisions on.
For example, consider the following mapping:
{
"rules": [
{
"local": [
{
"user": {
"name": "{0}"
}
},
{
"projects": [
{
"name": "Production",
"roles": [
{
"name": "observer"
}
]
},
{
"name": "Staging",
"roles": [
{
"name": "member"
}
]
},
{
"name": "Project for {0}",
"roles": [
{
"name": "admin"
}
]
}
]
}
],
"remote": [
{
"type": "UserName"
}
]
}
]
}
The semantics of the remote
section have not changed. The difference
between this mapping and the other examples is the addition of a projects
section within the local
rules. The projects
list supplies a list
of projects that the federated user will be given access to. The projects
will be automatically created if they don’t exist when the user
authenticated and the mapping engine has applied values from the assertion
and mapped them into the local
rules.
In the above example, an authenticated federated user will be granted the
observer
role on the Production
project, member
role on the
Staging
project, and they will have admin
role on the Project for
jsmith
.
It is important to note the following constraints apply when auto-provisioning:
projects
section of the mapping must also contain a roles
section.Since the creation of roles typically requires policy changes across other
services in the deployment, it is expected that roles are created ahead of
time. Federated authentication should also be considered idempotent if the
attributes from the SAML assertion have not changed. In the example from above,
if the user’s name is still jsmith
, then no new projects will be
created as a result of authentication.
Mappings can be created that mix groups
and projects
within the
local
section. The mapping shown in the example above does not contain a
groups
section in the local
rules. This will result in the federated
user having direct role assignments on the projects in the projects
list.
The following example contains local
rules comprised of both projects
and groups
, which allow for direct role assignments and group memberships.
{
"rules": [
{
"local": [
{
"user": {
"name": "{0}"
}
},
{
"projects": [
{
"name": "Marketing",
"roles": [
{
"name": "member"
}
]
},
{
"name": "Development project for {0}",
"roles": [
{
"name": "admin"
}
]
}
]
},
{
"group": {
"name": "Finance",
"domain": {
"id": "6fe767"
}
}
}
],
"remote": [
{
"type": "UserName"
}
]
}
]
}
In the above example, a federated user will receive direct role assignments on
the Marketing
project, as well as a dedicated project specific to the
federated user’s name. In addition to that, they will also be placed in the
Finance
group and receive all role assignments that group has on projects
and domains.
keystone-to-keystone federation also utilizes mappings, but has some differences.
An attribute file (e.g. /etc/shibboleth/attribute-map.xml
in a Shibboleth
implementation) is used to add attributes to the mapping context. Attributes
look as follows:
<!-- example from a K2k Shibboleth implementation -->
<Attribute name="openstack_user" id="openstack_user"/>
<Attribute name="openstack_user_domain" id="openstack_user_domain"/>
The service provider must contain a mapping as shown below.
openstack_user
, and openstack_user_domain
match to the attribute
names we have in the Identity Provider. It will map any user with the name
user1
or admin
in the openstack_user
attribute and
openstack_domain
attribute default
to a group with id abc1234
.
{
"rules": [
{
"local": [
{
"group": {
"id": "abc1234"
}
}
],
"remote": [
{
"type": "openstack_user",
"any_one_of": [
"user1",
"admin"
]
},
{
"type":"openstack_user_domain",
"any_one_of": [
"Default"
]
}
]
}
]
}
The possible attributes that can be used in a mapping are openstack_user, openstack_user_domain, openstack_roles, openstack_project, and openstack_project_domain.
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