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Quick Scan

The Quick Scan service collection provides operations for submitting files for machine learning scanning and retrieving scan results. Get scan aggregations, check scan status, submit sample volumes for ML scanning, and query submitted scans using FQL filters.

LanguageLast Update
Pythonv1.6.5
PowerShell
Gov0.22.0
TypeScriptv0.6.0
Rustv0.7.1
Rubyv1.4.0

This service collection has code examples posted to the repository.



OperationDescription
GetScans
get_scans
Check the status of a volume scan.
GetScansAggregates
get_scans_aggregates
Get scans aggregations as specified via json in request body.
QuerySubmissionsMixin0
query_submissions
Find IDs for submitted scans by providing an FQL filter and paging details.
ScanSamples
scan_samples
Submit a volume of files for ml scanning.

Check the status of a volume scan.

Method GET
Route /scanner/entities/scans/v1
Scope Quick Scan (Falcon Intelligence): READ
PEP 8 get_scans
ids query · string or list of strings
ID of a submitted scan
parameters query · dictionary
Full query string parameters payload in JSON format. Not required when using other keywords.
from falconpy import QuickScan
falcon = QuickScan(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_scans(ids=id_list)
print(response)
[
{
"cid": "string",
"created_timestamp": "string",
"id": "string",
"samples": [],
"status": "string"
}
]


Get scans aggregations as specified via json in request body.

Method POST
Route /scanner/aggregates/scans/GET/v1
Scope Quick Scan (Falcon Intelligence): READ
PEP 8 get_scans_aggregates
body body · dictionary
Full body payload as JSON formatted dictionary.
date_ranges body · array
exclude body · string
extended_bounds body · object
field body · string
filter body · string
FQL syntax.
filters_spec body · object
from body · integer
include body · string
interval body · string
Available values (6)
yearmonthweek
dayhourminute
max_doc_count body · integer
min_doc_count body · integer
Minimum number of documents required to match.
missing body · string
name body · string
Scan name.
percents body · array
q body · string
FQL syntax.
ranges body · array
size body · integer
sort body · string
FQL syntax.
Available values (2)
_count
sort by document count
_term
sort by the string value alphabetically
sub_aggregates body · array
time_zone body · string
type body · string
String. This method does not support body payload validation.
Available values (10)
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 detections by the value of a specified field. For example, if field used is scenario, then detections will be bucketed by the various detection scenario names.
range
Buckets detections by specified (numeric) ranges of a specified field. For example, if doing a range aggregation on the max_severity field, the detects 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.
from falconpy import QuickScan
falcon = QuickScan(client_id=CLIENT_ID,
client_secret=CLIENT_SECRET
)
date_ranges = [
{
"from": "string",
"to": "string"
}
]
ranges = [
{
"From": 0,
"To": 0
}
]
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",
sub_aggregates=["string"],
time_zone="string",
type="string")
print(response)
{
"errors": [
{
"code": 0,
"id": "string",
"message": "string"
}
],
"meta": {
"pagination": {
"limit": 0,
"offset": 0,
"total": 0
},
"powered_by": "string",
"query_time": 0.0,
"trace_id": "string",
"writes": {
"resources_affected": 0
}
}
}


Find IDs for submitted scans by providing an FQL filter and paging details.

Method GET
Route /scanner/queries/scans/v1
Scope Quick Scan (Falcon Intelligence): READ
PEP 8 query_submissions
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).
offset query · string
The offset to start retrieving submissions from.
limit query · integer
Maximum number of volume IDs to return. Max: 5000.
sort query · string
Sort order: asc or desc.
parameters query · dictionary
Full query string parameters payload in JSON format. Not required when using other keywords.
from falconpy import QuickScan
falcon = QuickScan(client_id=CLIENT_ID,
client_secret=CLIENT_SECRET
)
response = falcon.query_submissions(filter="string",
limit=integer,
offset="string",
sort="string")
print(response)
[
"string"
]


Submit a volume of files for ml scanning.

Method POST
Route /scanner/entities/scans/v1
Scope Quick Scan (Falcon Intelligence): WRITE
PEP 8 scan_samples
body body · dictionary
Full body payload as JSON formatted dictionary.
samples body · array
SHA256(s) of the samples to scan. Must have been previously submitted using SampleUploadV3 (SampleUploads class)
from falconpy import QuickScan
falcon = QuickScan(client_id=CLIENT_ID,
client_secret=CLIENT_SECRET
)
id_list = 'ID1,ID2,ID3' # Can also pass a list here: ['ID1', 'ID2', 'ID3']
response = falcon.scan_samples(samples=id_list)
print(response)
[
"string"
]