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Quick Scan
Joshua Hiller edited this page Dec 11, 2021
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21 revisions
Operation ID | Description | ||||
---|---|---|---|---|---|
|
Get scans aggregations as specified via json in request body. | ||||
|
Check the status of a volume scan. Time required for analysis increases with the number of samples in a volume but usually it should take less than 1 minute | ||||
|
Submit a volume of files for ml scanning. Time required for analysis increases with the number of samples in a volume but usually it should take less than 1 minute | ||||
|
Find IDs for submitted scans by providing a FQL filter and paging details. Returns a set of volume IDs that match your criteria. |
Get scans aggregations as specified via json in request body.
get_scans_aggregates
- Consumes: application/json
- Produces: application/json
Name | Service | Uber | Type | Data type | Description |
---|---|---|---|---|---|
body |
|
|
body | string | Full body payload in JSON format. |
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" } ] |
field |
|
|
body | string | The field on which to compute the aggregation. |
filter |
|
|
body | string | FQL syntax formatted string to use to filter the results. |
interval |
|
|
body | string | Time interval for date histogram aggregations. Valid values include:
|
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.
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:
|
from falconpy import QuickScan
falcon = QuickScan(client_id="API_CLIENT_ID_HERE",
client_secret="API_CLIENT_SECRET_HERE"
)
date_ranges = [
{
"from": "2021-05-15T14:55:21.892315096Z",
"to": "2021-05-17T13:42:16.493180643Z"
}
]
ranges = [
{
"From": 1,
"To": 100
}
]
response = falcon.get_scans_aggregates(date_ranges=date_ranges,
field="string",
filter="string",
interval="string",
min_doc_count=integer,
missing="string",
name="string",
q="string",
ranges=ranges,
size=integer,
sort="string",
time_zone="string",
type="string"
)
print(response)
from falconpy import QuickScan
falcon = QuickScan(client_id="API_CLIENT_ID_HERE",
client_secret="API_CLIENT_SECRET_HERE"
)
date_ranges = [
{
"from": "2021-05-15T14:55:21.892315096Z",
"to": "2021-05-17T13:42:16.493180643Z"
}
]
ranges = [
{
"From": 1,
"To": 100
}
]
response = falcon.GetScansAggregates(date_ranges=date_ranges,
field="string",
filter="string",
interval="string",
min_doc_count=integer,
missing="string",
name="string",
q="string",
ranges=ranges,
size=integer,
sort="string",
time_zone="string",
type="string"
)
print(response)
from falconpy import APIHarness
falcon = APIHarness(client_id="API_CLIENT_ID_HERE",
client_secret="API_CLIENT_SECRET_HERE"
)
date_ranges = [
{
"from": "2021-05-15T14:55:21.892315096Z",
"to": "2021-05-17T13:42:16.493180643Z"
}
]
ranges = [
{
"From": 1,
"To": 100
}
]
BODY = {
"date_ranges": date_ranges,
"field": "string",
"filter": "string",
"interval": "string",
"min_doc_count": 0,
"missing": "string",
"name": "string",
"q": "string",
"ranges": ranges,
"size": 0,
"sort": "string",
"time_zone": "string",
"type": "string"
}
response = falcon.command("GetScansAggregates", body=BODY)
print(response)
Check the status of a volume scan. Time required for analysis increases with the number of samples in a volume but usually it should take less than 1 minute
get_scans
- Produces: application/json
Name | Service | Uber | Type | Data type | Description |
---|---|---|---|---|---|
ids |
|
|
query | string or list of strings | ID of a submitted scan to retrieve. |
parameters |
|
|
query | string | Full query string parameters payload in JSON format. |
from falconpy import QuickScan
falcon = QuickScan(client_id="API_CLIENT_ID_HERE",
client_secret="API_CLIENT_SECRET_HERE"
)
id_list = 'ID1,ID2,ID3' # Can also pass a list here: ['ID1', 'ID2', 'ID3']
response = falcon.get_scans(ids=id_list)
print(response)
from falconpy import QuickScan
falcon = QuickScan(client_id="API_CLIENT_ID_HERE",
client_secret="API_CLIENT_SECRET_HERE"
)
id_list = 'ID1,ID2,ID3' # Can also pass a list here: ['ID1', 'ID2', 'ID3']
response = falcon.GetScans(ids=id_list)
print(response)
from falconpy import APIHarness
falcon = APIHarness(client_id="API_CLIENT_ID_HERE",
client_secret="API_CLIENT_SECRET_HERE"
)
id_list = 'ID1,ID2,ID3' # Can also pass a list here: ['ID1', 'ID2', 'ID3']
response = falcon.command("GetScans", ids=id_list)
print(response)
Submit a volume of files for ml scanning. Time required for analysis increases with the number of samples in a volume but usually it should take less than 1 minute
scan_samples
- Produces: application/json
Name | Service | Uber | Type | Data type | Description |
---|---|---|---|---|---|
body |
|
|
body | string | Full body payload in JSON format. |
samples |
|
|
body | string or list of strings | Submit a batch of SHA256s for ml scanning. The samples must have been previously uploaded through UploadSampleV3. |
from falconpy import QuickScan
falcon = QuickScan(client_id="API_CLIENT_ID_HERE",
client_secret="API_CLIENT_SECRET_HERE"
)
sample_list = "SHA1,SHA2,SHA3" # Can also pass a list here: ['SHA1', 'SHA2', 'SHA3']
response = falcon.scan_samples(samples=sample_list)
print(response)
from falconpy import QuickScan
falcon = QuickScan(client_id="API_CLIENT_ID_HERE",
client_secret="API_CLIENT_SECRET_HERE"
)
sample_list = "SHA1,SHA2,SHA3" # Can also pass a list here: ['SHA1', 'SHA2', 'SHA3']
response = falcon.ScanSamples(samples=sample_list)
print(response)
from falconpy import APIHarness
falcon = APIHarness(client_id="API_CLIENT_ID_HERE",
client_secret="API_CLIENT_SECRET_HERE"
)
sample_list = ['SHA1', 'SHA2', 'SHA3']
BODY = {
"samples": sample_list
}
response = falcon.command("ScanSamples", body=BODY)
print(response)
Find IDs for submitted scans by providing a FQL filter and paging details. Returns a set of volume IDs that match your criteria.
query_submissions
- Produces: application/json
Name | Service | Uber | Type | Data type | Description |
---|---|---|---|---|---|
filter |
|
|
query | string | Optional filter and sort criteria in the form of an FQL query. Additional information about FQL queries can also be found in here (Customer login required). |
limit |
|
|
query | integer | Maximum number of volume IDs to return. Max: 5000. |
offset |
|
|
query | string | The offset to start retrieving submissions from. |
sort |
|
|
query | string | Sort order: asc or desc . |
parameters |
|
|
query | string | Full query string parameters payload in JSON format. |
from falconpy import QuickScan
falcon = QuickScan(client_id="API_CLIENT_ID_HERE",
client_secret="API_CLIENT_SECRET_HERE"
)
response = falcon.query_submissions(filter="string",
offset="string",
limit=integer,
sort="string"
)
print(response)
from falconpy import QuickScan
falcon = QuickScan(client_id="API_CLIENT_ID_HERE",
client_secret="API_CLIENT_SECRET_HERE"
)
response = falcon.QuerySubmissionsMixin0(filter="string",
offset="string",
limit=integer,
sort="string"
)
print(response)
from falconpy import APIHarness
falcon = APIHarness(client_id="API_CLIENT_ID_HERE",
client_secret="API_CLIENT_SECRET_HERE"
)
response = falcon.command("QuerySubmissionsMixin0",
filter="string",
offset="string",
limit=integer,
sort="string"
)
print(response)
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