policies¶

The following methods allow for interaction with the Zscaler AI Guard Detection Policies API endpoints. Includes listing, creating, updating, and deleting detection policies, and retrieving a policy by ID or name.

Methods are accessible via aiguard.policies

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class PoliciesAPI¶

Bases: APIClient

A Client object for the AI Guard Detection Policies resource.

add_policy(**kwargs)¶

Creates a new detection policy.

Parameters:

name (str) – The name of the detection policy.
**kwargs – Optional keyword args.

Keyword Arguments:

version (str) – The version for this detection policy.
description (str) – Additional information about the detection policy.
input_detector_policies (str) – The input detector policies for this detection policy.
output_detector_policies (str) – The output detector policies for this detection policy.

Returns:

A tuple containing the newly added Policies instance, response, and error.

Return type:

tuple

Examples

Add a new detection policy with input and output detectors:

>>> added_policy, _, error = client.aiguard.policies.add_policy(
...     name="PolicyRule01",
...     inputDetectorPolicies=[
...         {
...             "detector": "toxicity",
...             "enabled": True,
...             "severity": "HIGH",
...             "configuration": {"action": "BLOCK", "threshold": 0.87},
...         },
...         {
...             "detector": "prompt_injection",
...             "enabled": True,
...             "severity": "CRITICAL",
...             "configuration": {"action": "BLOCK", "threshold": 0.75},
...         },
...     ],
...     outputDetectorPolicies=[
...         {
...             "detector": "pii",
...             "enabled": False,
...             "severity": "CRITICAL",
...             "configuration": {
...                 "entities": [
...                     {"action": "BLOCK", "entityType": "CREDIT_CARD"},
...                     {"action": "BLOCK", "entityType": "US_SSN"},
...                     {"action": "DETECT", "entityType": "EMAIL_ADDRESS"},
...                 ],
...                 "threshold": 0.5,
...                 "anonymization": "NONE",
...                 "defaultAction": "BLOCK",
...                 "replaceWithMaskedContent": False,
...             },
...         },
...     ],
... )
>>> if error:
...     print(f"Error adding detection policy: {error}")
...     return
... print(f"Detection policy added successfully: {added_policy.as_dict()}")

delete_policy(policy_id)¶

Deletes the specified detection policy.

Parameters:: policy_id (int) – The unique identifier for the detection policy.
Returns:: A tuple containing the response object and error (if any).
Return type:: tuple

Examples

Delete a detection policy:

>>> _, _, error = client.aiguard.policies.delete_policy(1013)
>>> if error:
...     print(f"Error deleting detection policy: {error}")
...     return
... print(f"Detection policy deleted successfully.")

get_policy(policy_id)¶

Fetches a specific detection policy by ID.

Parameters:: policy_id (int) – The unique identifier for the detection policy.
Returns:: A tuple containing (Policies instance, Response, error).
Return type:: tuple

Examples

Print a specific detection policy:

>>> fetched_policy, _, error = client.aiguard.policies.get_policy(1013)
>>> if error:
...     print(f"Error fetching detection policy by ID: {error}")
...     return
... print(f"Fetched detection policy by ID: {fetched_policy.as_dict()}")

get_policy_by_name(name)¶

Fetches a specific detection policy by name.

Parameters:: name (str) – The name of the detection policy.
Returns:: A tuple containing (Policies instance, Response, error).
Return type:: tuple

Examples

Print a specific detection policy by name:

>>> fetched_policy, _, error = client.aiguard.policies.get_policy_by_name('Policy01')
>>> if error:
...     print(f"Error fetching detection policy by name: {error}")
...     return
... print(f"Fetched detection policy by name: {fetched_policy.as_dict()}")

list_policies(query_params=None)¶

Lists the detection policies configured in your organization.

Parameters:: {dict} (query_params) – Map of query parameters for the request.
Returns:: A tuple containing (list of Policies instances, Response, error)
Return type:: tuple

Examples

List detection policies:

>>> policy_list, _, error = client.aiguard.policies.list_policies()
>>> if error:
...     print(f"Error listing detection policies: {error}")
...     return
... print(f"Total detection policies found: {len(policy_list)}")
... for policy in policy_list:
...     print(policy.as_dict())

Client-side filtering with JMESPath:

The response object supports client-side filtering and projection via resp.search(expression). See the JMESPath documentation for expression syntax.

update_policy(policy_id, **kwargs)¶

Updates information for the specified detection policy.

Parameters:

policy_id (int) – The unique identifier for the detection policy.

Keyword Arguments:

name (str) – The name of the detection policy.
version (str) – The version for this detection policy.
description (str) – Additional information about the detection policy.
input_detector_policies (str) – The input detector policies for this detection policy.
output_detector_policies (str) – The output detector policies for this detection policy.

Returns:

A tuple containing the updated Policies instance, response, and error.

Return type:

tuple

Examples

Update an existing detection policy. The update replaces the policy, so the detector lists are sent in full:

>>> updated_policy, _, error = client.aiguard.policies.update_policy(
...     policy_id=2916,
...     name="PolicyRule01",
...     inputDetectorPolicies=[
...         {
...             "detector": "toxicity",
...             "enabled": True,
...             "severity": "HIGH",
...             "configuration": {"action": "BLOCK", "threshold": 0.87},
...         },
...     ],
...     outputDetectorPolicies=[
...         {
...             "detector": "toxicity",
...             "enabled": True,
...             "severity": "CRITICAL",
...             "configuration": {"action": "BLOCK", "threshold": 0.87},
...         },
...     ],
... )
>>> if error:
...     print(f"Error updating detection policy: {error}")
...     return
... print(f"Detection policy updated successfully: {updated_policy.as_dict()}")