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Spotlight Evaluation Logic
Operation ID | Description | ||||
---|---|---|---|---|---|
|
Search for evaluation logic in your environment by providing a FQL filter and paging details. Returns a set of evaluation logic entities which match the filter criteria. | ||||
|
Get details on evaluation logic items by providing one or more IDs. | ||||
|
Search for evaluation logic in your environment by providing a FQL filter and paging details. Returns a set of evaluation logic IDs which match the filter criteria. |
WARNING
client_id
andclient_secret
are keyword arguments that contain your CrowdStrike API credentials. Please note that all examples below do not hard code these values. (These values are ingested as strings.)CrowdStrike does not recommend hard coding API credentials or customer identifiers within source code.
Search for evaluation logic in your environment by providing a FQL filter and paging details. Returns a set of evaluation logic entities which match the filter criteria.
query_evaluation_logic_combined
Method | Route |
---|---|
/spotlight/combined/evaluation-logic/v1 |
- Produces: application/json
Name | Service | Uber | Type | Data type | Description |
---|---|---|---|---|---|
after |
|
|
query | string | A pagination token used with the limit parameter to manage pagination of results. On your first request, don't provide an after token. On subsequent requests, provide the after token from the previous response to continue from that place in the results. |
limit |
|
|
query | integer | Maximum number of entities to return. |
filter |
|
|
query | string | FQL query specifying the filter parameters. |
parameters |
|
|
query | dictionary | Full query string parameters payload in JSON format. |
sort |
|
|
query | string | Sort evaluation logic by their properties. |
from falconpy.spotlight_evaluation_logic import SpotlightEvaluationLogic
# Do not hardcode API credentials!
falcon = SpotlightEvaluationLogic(client_id=CLIENT_ID,
client_secret=CLIENT_SECRET
)
response = falcon.query_evaluation_logic_combined(after="string",
limit=integer,
filter="string",
sort="string"
)
print(response)
from falconpy import SpotlightEvaluationLogic
# Do not hardcode API credentials!
falcon = SpotlightEvaluationLogic(client_id=CLIENT_ID,
client_secret=CLIENT_SECRET
)
response = falcon.combinedQueryEvaluationLogic(after="string",
limit=integer,
filter="string",
sort="string"
)
print(response)
from falconpy import APIHarnessV2
# Do not hardcode API credentials!
falcon = APIHarnessV2(client_id=CLIENT_ID,
client_secret=CLIENT_SECRET
)
response = falcon.command("combinedQueryEvaluationLogic",
after="string",
limit=integer,
filter="string",
sort="string"
)
print(response)
Get details on evaluation logic items by providing one or more IDs.
get_evaluation_logic
Method | Route |
---|---|
/spotlight/entities/evaluation-logic/v1 |
- Produces: application/json
Name | Service | Uber | Type | Data type | Description |
---|---|---|---|---|---|
ids |
|
|
query | list of strings | One or more evaluation logic IDs. |
parameters |
|
|
query | dictionary | Full query string parameters payload in JSON format. |
from falconpy.spotlight_evaluation_logic import SpotlightEvaluationLogic
# Do not hardcode API credentials!
falcon = SpotlightEvaluationLogic(client_id=CLIENT_ID,
client_secret=CLIENT_SECRET
)
id_list = 'ID1,ID2,ID3' # Can also pass a list here: ['ID1', 'ID2', 'ID3']
response = falcon.get_evaluation_logic(ids=id_list)
print(response)
from falconpy import SpotlightEvaluationLogic
# Do not hardcode API credentials!
falcon = SpotlightEvaluationLogic(client_id=CLIENT_ID,
client_secret=CLIENT_SECRET
)
id_list = 'ID1,ID2,ID3' # Can also pass a list here: ['ID1', 'ID2', 'ID3']
response = falcon.getEvaluationLogic(ids=id_list)
print(response)
from falconpy import APIHarnessV2
# Do not hardcode API credentials!
falcon = APIHarnessV2(client_id=CLIENT_ID,
client_secret=CLIENT_SECRET
)
id_list = 'ID1,ID2,ID3' # Can also pass a list here: ['ID1', 'ID2', 'ID3']
response = falcon.command("getEvaluationLogic", ids=id_list)
print(response)
Search for evaluation logic in your environment by providing a FQL filter and paging details. Returns a set of evaluation logic IDs which match the filter criteria.
query_evaluation_logic
Method | Route |
---|---|
/spotlight/queries/evaluation-logic/v1 |
- Produces: application/json
Name | Service | Uber | Type | Data type | Description |
---|---|---|---|---|---|
after |
|
|
query | string | A pagination token used with the limit parameter to manage pagination of results. On your first request, don't provide an after token. On subsequent requests, provide the after token from the previous response to continue from that place in the results. |
limit |
|
|
query | integer | Maximum number of entities to return. |
filter |
|
|
query | string | FQL query specifying the filter parameters. |
parameters |
|
|
query | dictionary | Full query string parameters payload in JSON format. |
sort |
|
|
query | string | Sort evaluation logic by their properties. |
from falconpy.spotlight_evaluation_logic import SpotlightEvaluationLogic
# Do not hardcode API credentials!
falcon = SpotlightEvaluationLogic(client_id=CLIENT_ID,
client_secret=CLIENT_SECRET
)
response = falcon.query_evaluation_logic(after="string",
limit=integer,
filter="string",
sort="string"
)
print(response)
from falconpy import SpotlightEvaluationLogic
# Do not hardcode API credentials!
falcon = SpotlightEvaluationLogic(client_id=CLIENT_ID,
client_secret=CLIENT_SECRET
)
response = falcon.queryEvaluationLogic(after="string",
limit=integer,
filter="string",
sort="string"
)
print(response)
from falconpy import APIHarnessV2
# Do not hardcode API credentials!
falcon = APIHarnessV2(client_id=CLIENT_ID,
client_secret=CLIENT_SECRET
)
response = falcon.command("queryEvaluationLogic",
after="string",
limit=integer,
filter="string",
sort="string"
)
print(response)
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