Using the Cao Hunting service collection

Uber class support Service class support Documentation Version Page Updated

Operation ID

Description

AggregateIntelligenceQueries
PEP8	aggregate_queries

Aggregate intelligence queries.

GetArchiveExport
PEP8	create_export_archive

Creates an Archive Export.

GetIntelligenceQueries
PEP8	get_queries

Retrieves a list of Intelligence queries.

SearchIntelligenceQueries
PEP8	search_queries

Search intelligence queries that match the provided conditions.

Passing credentials

WARNING

client_id and client_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.

AggregateIntelligenceQueries

Aggregate intelligence queries.

PEP8 method name

aggregate_queries

Endpoint

Method	Route
	`/hunting/aggregates/intelligence-queries/v1`

Required Scope

cao-hunting:read

Content-Type

Consumes: application/json
Produces: application/json

Keyword Arguments

Name	Type	Data type	Description
body	body	dictionary	Full body payload as a dictionary. Not required when using other keywords.
date_ranges	body	list of dictionaries	Applies to date_range aggregations. Example: [ { "from": "2016-05-28T09:00:31Z", "to": "2016-05-30T09:00:31Z" }, { "from": "2016-06-01T09:00:31Z", "to": "2016-06-10T09:00:31Z" } ]
exclude	body	string	Elements to exclude.
extended_bounds	body	dictionary	Extended aggregate boundaries. Contains `max` and `min` values as strings. Example: { "max": "string", "min": "string" }
field	body	string	The field on which to compute the aggregation.
filter	body	string	FQL syntax formatted string to use to filter the results.
from	body	integer	Starting position.
include	body	string	Elements to include.
interval	body	string	Time interval for date histogram aggregations. Valid values include: `year` `month` `week` `day` `hour` `minute`
max_doc_count	body	integer	Only return buckets if values are less than or equal to the value here.
min_doc_count	body	integer	Only return buckets if values are greater than or equal to the value here.
missing	body	string	Missing is the value to be used when the aggregation field is missing from the object. In other words, the missing parameter defines how documents that are missing a value should be treated. By default they will be ignored, but it is also possible to treat them as if they had a value.
name	body	string	Name of the aggregate query, as chosen by the user. Used to identify the results returned to you.
q	body	string	Full text search across all metadata fields.
ranges	body	list of dictionaries	Applies to range aggregations. Ranges values will depend on field. For example, if `max_severity` is used, ranges might look like: [ { "From": 0, "To": 70 }, { "From": 70, "To": 100 } ]
size	body	integer	The max number of term buckets to be returned.
sub_aggregates	body	list of dictionaries	A nested aggregation, such as: [ { "name": "max_first_behavior", "type": "max", "field": "first_behavior" } ] There is a maximum of 3 nested aggregations per request.
sort	body	string	FQL syntax string to sort bucket results. `_count` - sort by document count `_term` - sort by the string value alphabetically Supports `asc` and `desc` using `\|` format. Example: `_count\|desc`
time_zone	body	string	Time zone for bucket results.
type	body	string	Type of aggregation. Valid values include: `date_histogram` - Aggregates counts on a specified time interval. Requires use of “interval” field. `date_range` - Aggregates counts on custom defined date range buckets. Can include multiple ranges. (Similar to time series, but the bucket sizes are variable). Date formats to follow ISO 8601. `terms` - Buckets alerts by the value of a specified field. For example, if field used is scenario, then alerts will be bucketed by the various alert scenario names. `range` - Buckets alerts by specified (numeric) ranges of a specified field. For example, if doing a range aggregation on the max_severity field, the alerts will be counted by the specified ranges of severity. `cardinality` - Returns the count of distinct values in a specified field. `max` - Returns the maximum value of a specified field. `min` - Returns the minimum value of a specified field. `avg` - Returns the average value of the specified field. `sum` - Returns the total sum of all values for the specified field. `percentiles` - Returns the following percentiles for the specified field: `1`, `5`, `25`, `50`, `75`, `95`, `99`.

Usage

Service class example (PEP8 syntax)

from falconpy import CAOHunting

falcon = CAOHunting(client_id=CLIENT_ID,
                    client_secret=CLIENT_SECRET
                    )

date_range = {
    "from": "string",
    "to": "string"
}
bounds = {
    "max": "string",
    "min": "string"
}
search_range = {
    "From": integer,
    "To": integer
}

response = falcon.aggregate_queries(date_ranges=[date_range],
                                    exclude="string",
                                    extended_bounds=bounds,
                                    field="string",
                                    filter="string",
                                    from=integer,
                                    include="string",
                                    interval="string",
                                    max_doc_count=integer,
                                    min_doc_count=integer,
                                    missing="string",
                                    name="string",
                                    q="string",
                                    ranges=[search_range],
                                    size=integer,
                                    sort="string",
                                    time_zone="string",
                                    type="string"
                                    )
print(response)

Service class example (Operation ID syntax)

from falconpy import CAOHunting

falcon = CAOHunting(client_id=CLIENT_ID,
                    client_secret=CLIENT_SECRET
                    )

date_range = {
    "from": "string",
    "to": "string"
}
bounds = {
    "max": "string",
    "min": "string"
}
search_range = {
    "From": integer,
    "To": integer
}

response = falcon.AggregateIntelligenceQueries(date_ranges=[date_range],
                                               exclude="string",
                                               extended_bounds=bounds,
                                               field="string",
                                               filter="string",
                                               from=integer,
                                               include="string",
                                               interval="string",
                                               max_doc_count=integer,
                                               min_doc_count=integer,
                                               missing="string",
                                               name="string",
                                               q="string",
                                               ranges=[search_range],
                                               size=integer,
                                               sort="string",
                                               time_zone="string",
                                               type="string"
                                               )
print(response)

Uber class example

from falconpy import APIHarnessV2

falcon = APIHarnessV2(client_id=CLIENT_ID,
                      client_secret=CLIENT_SECRET
                      )

body_payload = [
    {
        "date_ranges": [
            {
                "from": "string",
                "to": "string"
            }
        ],
        "exclude": "string",
        "extended_bounds": {
            "max": "string",
            "min": "string"
        }
        "field": "string",
        "filter": "string",
        "from": integer,
        "include": "string",
        "interval": "string",
        "max_doc_count": integer,
        "min_doc_count": integer,
        "missing": "string",
        "name": "string",
        "q": "string",
        "ranges": [
            {
                "From": integer,
                "To": integer
            }
        ],
        "size": integer,
        "sort": "string",
        "sub_aggregates": [
            null
        ],
        "time_zone": "string",
        "type": "string"
    }
]

response = falcon.command("AggregateIntelligenceQueries", body=body_payload)

print(response)

GetArchiveExport

Creates an Archive Export.

PEP8 method name

create_export_archive

Endpoint

Method	Route
	`/hunting/entities/archive-exports/v1`

Required Scope

cao-hunting:read

Content-Type

Produces: application/octet-stream

Keyword Arguments

Name	Type	Data type	Description
archive_type	query	string	The Archive Type can be one of 'zip' and 'gzip'. Defaults to 'zip'.
filter	query	string	The FQL Filter.
language	query	string	The Query Language. Accepted Values: `cql` `snort` `suricata` `yara`
parameters	query	dictionary	Full query string parameters payload in JSON format. Not required when using other keywords.

Usage

Service class example (PEP8 syntax)

from falconpy import CAOHunting

falcon = CAOHunting(client_id=CLIENT_ID,
                    client_secret=CLIENT_SECRET
                    )

save_file = "some_file.ext"
with open(save_file, "wb") as file_output:
    file_output.write(falcon.create_export_archive(language="string",
                                        filter="string",
                                        archive_type="string"
                                        ))

Service class example (Operation ID syntax)

from falconpy import CAOHunting

falcon = CAOHunting(client_id=CLIENT_ID,
                    client_secret=CLIENT_SECRET
                    )

save_file = "some_file.ext"
with open(save_file, "wb") as file_output:
    file_output.write(falcon.GetArchiveExport(language="string",
                                              filter="string",
                                              archive_type="string"
                                              ))

Uber class example

from falconpy import APIHarnessV2

falcon = APIHarnessV2(client_id=CLIENT_ID,
                      client_secret=CLIENT_SECRET
                      )

save_file = "some_file.ext"
with open(save_file, "wb") as file_output:
    file_output.write(falcon.command("GetArchiveExport",
                                     language="string",
                                      filter="string",
                                      archive_type="string"
                                      ))

GetIntelligenceQueries

Retrieves a list of Intelligence queries.

PEP8 method name

get_queries

Endpoint

Method	Route
	`/hunting/entities/intelligence-queries/v1`

Required Scope

cao-hunting:read

Content-Type

Produces: application/json

Keyword Arguments

Name	Service	Uber	Type	Data type	Description
ids			query	array (string)	Intelligence queries IDs.
parameters			query	dictionary	Full query string parameters payload in JSON format. Not required when using other keywords.

Usage

Service class example (PEP8 syntax)

from falconpy import CAOHunting

falcon = CAOHunting(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_queries(ids=id_list)

print(response)

Service class example (Operation ID syntax)

from falconpy import CAOHunting

falcon = CAOHunting(client_id=CLIENT_ID,
                    client_secret=CLIENT_SECRET
                    )

id_list = 'ID1,ID2,ID3'  # Can also pass a list here: ['ID1', 'ID2', 'ID3']

response = falcon.GetIntelligenceQueries(ids=id_list)

print(response)

Uber class example

from falconpy import APIHarnessV2

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("GetIntelligenceQueries", ids=id_list)

print(response)

SearchIntelligenceQueries

Search intelligence queries that match the provided conditions.

PEP8 method name

search_queries

Endpoint

Method	Route
	`/hunting/queries/intelligence-queries/v1`

Required Scope

cao-hunting:read

Content-Type

Produces: application/json

Keyword Arguments

Name	Type	Data type	Description
filter	query	string	FQL query specifying the filter parameters.
limit	query	integer	Number of IDs to return.
offset	query	string	Starting index of result set from which to return IDs.
parameters	query	dictionary	Full query string parameters payload in JSON format. Not required when using other keywords.
q	query	string	Match phrase_prefix query criteria; included fields: _all (all filter string fields indexed).
sort	query	string	Order by fields.

Usage

Service class example (PEP8 syntax)

from falconpy import CAOHunting

falcon = CAOHunting(client_id=CLIENT_ID,
                    client_secret=CLIENT_SECRET
                    )

response = falcon.search_queries(offset="string",
                                 limit=integer,
                                 sort="string",
                                 filter="string",
                                 q="string"
                                 )
print(response)

Service class example (Operation ID syntax)

from falconpy import CAOHunting

falcon = CAOHunting(client_id=CLIENT_ID,
                    client_secret=CLIENT_SECRET
                    )

response = falcon.SearchIntelligenceQueries(offset="string",
                                            limit=integer,
                                            sort="string",
                                            filter="string",
                                            q="string"
                                            )
print(response)

Uber class example

from falconpy import APIHarnessV2

falcon = APIHarnessV2(client_id=CLIENT_ID,
                      client_secret=CLIENT_SECRET
                      )

response = falcon.command("SearchIntelligenceQueries",
                          offset="string",
                          limit=integer,
                          sort="string",
                          filter="string",
                          q="string"
                          )
print(response)

CAO Hunting - CrowdStrike/falconpy GitHub Wiki

Using the Cao Hunting service collection

Table of Contents

Passing credentials

AggregateIntelligenceQueries

PEP8 method name

Endpoint

Required Scope

Content-Type

Keyword Arguments

Usage

Service class example (PEP8 syntax)

Service class example (Operation ID syntax)

Uber class example

GetArchiveExport

PEP8 method name

Endpoint

Required Scope

Content-Type

Keyword Arguments

Usage

Service class example (PEP8 syntax)

Service class example (Operation ID syntax)

Uber class example

GetIntelligenceQueries

PEP8 method name

Endpoint

Required Scope

Content-Type

Keyword Arguments

Usage

Service class example (PEP8 syntax)

Service class example (Operation ID syntax)

Uber class example

SearchIntelligenceQueries

PEP8 method name

Endpoint

Required Scope

Content-Type

Keyword Arguments

Usage

Service class example (PEP8 syntax)

Service class example (Operation ID syntax)

Uber class example

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