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This script is a general tool for connecting to different SIEMs and sending information from Socket

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socket-issues-export

Purpose

This script provides a method to export the alerts from the Socket Health reports into other tools.

This tool supports the following connectors:

  • CSV
  • Google BigQuery
  • Panther SIEM
  • Elasticsearch
  • WebHook
  • Slack

Other SIEM Integrations

Some SIEM tools have different ways of getting the data into their system.

  • Splunk - App found here

Required Configuration

The connectors supported by this script have some shared configuration in order to pull the data from Socket.

Options

Option Required Format Description
api_key True string This is the Socket API Key created in the Socket dashboard. This should have the scoped permissions to access reports
report_id False Socket Report ID If this is provided then only the specified report ID will be processed
request_timeout False int This is the number of seconds to wait for an API request to complete before killing it and returning an error. Defaults to 30 seconds
default_branch_only False boolean If enabled only use the latest report from each repo's default branch
from_time False int Period in seconds to pull reports when not specifying a specific report_id. If not set defaults to 5 minutes
actions_override False list[str] List of acceptable values to override the security policy configuration of issues to include. I.E. error, warn, monitor, and ignore

Example

import os
from socketsync.core import Core

if __name__ == '__main__':
    socket_org = os.getenv("SOCKET_ORG") or exit(1)
    api_key = os.getenv("SOCKET_API_KEY") or exit(1)
    days_ago = os.getenv("DAYS_AGO") or exit(1)

    from_time = days_ago * 24 * 60 * 60 #Convert days to seconds

    core = Core(
        api_key=api_key,
        from_time=from_time,
        report_id=report_id,
        request_timeout=300
    )
    issue_data = core.get_issues()

Examples for each supported connector

CSV

The CSV Export function will output to a specified CSV file. Currently, it will overwrite the file if it already exists.

Initializing Options:

Option Required Default Description
file True None The name of the file to write the CSV results out to
columns False All Columns The names of the column headers and the order for the columns. Must match the property names for the issues. If not passed default columns are used
import os
from socketsync.core import Core
from socketsync.connectors.csv import CSV

if __name__ == '__main__':
    socket_org = os.getenv("SOCKET_ORG") or exit(1)
    api_key = os.getenv("SOCKET_API_KEY") or exit(1)
    days_ago = os.getenv("DAYS_AGO") or exit(1)
    report_id = os.getenv("SOCKET_REPORT_ID")

    from_time = days_ago * 24 * 60 * 60 #Convert days to seconds

    core = Core(
        api_key=api_key,
        from_time=from_time,
        report_id=report_id
    )
    issue_data = core.get_issues()

    csv_file = "CSV_FILE"
    csv = CSV(
        file=csv_file
    )
    csv.write_csv(issue_data)

Google BigQuery

The BigQuery connector will send data to the specified Table within BigQuery. Currently, in order to be authenticated you will need to do the following before running the code.

  1. Install the GCloud CLI
  2. In a terminal run gcloud auth login
  3. In a terminal run gcloud config set project $MY_PROJECT_ID

Initializing Options:

Option Required Default Description
table True None This is the table in the format of dataset.table that results will be added to
import os
from socketsync.core import Core
from socketsync.connectors.bigquery import BigQuery

if __name__ == '__main__':
    socket_org = os.getenv("SOCKET_ORG") or exit(1)
    api_key = os.getenv("SOCKET_API_KEY") or exit(1)
    days_ago = os.getenv("DAYS_AGO") or exit(1)
    report_id = os.getenv("SOCKET_REPORT_ID")

    from_time = days_ago * 24 * 60 * 60 #Convert days to seconds

    core = Core(
        api_key=api_key,
        from_time=from_time,
        report_id=report_id
    )
    issue_data = core.get_issues()
    bigquery_table = os.getenv('GOOGLE_TABLE') or exit(1)
    bigquery = BigQuery(bigquery_table)
    errors = bigquery.add_dataset(issue_data, streaming=True)

Panther

The Panther connector requires you to have an HTTP connector setup in the Panther UI. In this example I used a bearer token but this can be overriden by using custom headers if desired.

Configuration can be found here

Initializing Options:

Option Required Default Description
token False None Token to use if you are using Bearer token. Default method if custom headers are not passed to send
url True None Panther Webhook URL to POST data to
timeout False 10 Timeout in seconds for requests
import os
from socketsync.core import Core
from socketsync.connectors.panther import Panther

if __name__ == '__main__':
    socket_org = os.getenv("SOCKET_ORG") or exit(1)
    api_key = os.getenv("SOCKET_API_KEY") or exit(1)
    days_ago = os.getenv("DAYS_AGO") or exit(1)
    report_id = os.getenv("SOCKET_REPORT_ID")

    from_time = days_ago * 24 * 60 * 60 #Convert days to seconds

    core = Core(
        api_key=api_key,
        from_time=from_time,
        report_id=report_id
    )
    issue_data = core.get_issues()
    panther_url = os.getenv('PANTHER_URL') or exit(1)
    panther_token = os.getenv('PANTHER_TOKEN') or exit(1)
    panther = Panther(
        token=panther_token,
        url=panther_url
    )
    for issue in issue_data:
        issue_json = json.loads(str(issue))
        panther.send(str(issue))
        print(f"Processed issue id: {issue.id}")

Elasticsearch

The Elasticsearch connector should work with on prem or cloud hosted Elastic search configurations. The configuration when loading Elastic is the same as from the Elasticsearch documentation

import os
from socketsync.core import Core
from socketsync.connectors.elastic import Elastic

if __name__ == '__main__':
    socket_org = os.getenv("SOCKET_ORG") or exit(1)
    api_key = os.getenv("SOCKET_API_KEY") or exit(1)
    days_ago = os.getenv("DAYS_AGO") or exit(1)
    report_id = os.getenv("SOCKET_REPORT_ID")

    from_time = days_ago * 24 * 60 * 60 #Convert days to seconds

    core = Core(
        api_key=api_key,
        from_time=from_time,
        report_id=report_id
    )
    issue_data = core.get_issues()
    elastic_token = os.getenv('ELASTIC_TOKEN') or exit(1)
    elastic_cloud_id = os.getenv('ELASTIC_CLOUD_ID') or exit(1)
    elastic_index = os.getenv('ELASTIC_ID') or exit(1)
    es = Elastic(
        api_key=elastic_token,
        cloud_id=elastic_cloud_id
    )
    for issue in issue_data:
        es.add_document(issue, elastic_index)

WebHook

The WebHook integration is a simple wrapper for sending an HTTP(s) Request to the desired URL.

Initialize Options:

Option Required Default Description
url True None URL for the WebHook
headers False {'User-Agent': 'SocketPythonScript/0.0.1', "accept": "application/json", 'Content-Type': "application/json"} Default set of headers to use if not specified
auth_headers False None Dictionary of auth headers to use to authenticate to the WebHook
params False None Dictionary of query params to use if needed
timeout False 10 Time in seconds to timeout out a request
import os
from socketsync.core import Core
from socketsync.connectors.webhook import Webhook

if __name__ == '__main__':
    socket_org = os.getenv("SOCKET_ORG") or exit(1)
    api_key = os.getenv("SOCKET_API_KEY") or exit(1)
    days_ago = os.getenv("DAYS_AGO") or exit(1)
    report_id = os.getenv("SOCKET_REPORT_ID")

    from_time = days_ago * 24 * 60 * 60 #Convert days to seconds

    core = Core(
        api_key=api_key,
        from_time=from_time,
        report_id=report_id
    )
    issue_data = core.get_issues()
    webhook_url = os.getenv("WEBHOOK_URL") or exit(1)
    webhook_auth_headers = os.getenv("WEBHOOK_AUTH_HEADERS") or {
        'Authorization': 'Bearer EXAMPLE'
    }
    webhook = Webhook(webhook_url)
    for issue in issue_data:
        issue_json = json.loads(str(issue))
        webhook.send(issue_json)

Slack WebHook

The Slack WebHook integration is a simple wrapper for sending an HTTP(s) Request to the desired Slack Webhook URL.

Initialize Options:

Option Required Default Description
url True None URL for the WebHook
headers False {'User-Agent': 'SocketPythonScript/0.0.1', "accept": "application/json", 'Content-Type': "application/json"} Default set of headers to use if not specified
params False None Dictionary of query params to use if needed
timeout False 10 Time in seconds to timeout out a request
import os
from socketsync.core import Core
from socketsync.connectors.slack import Slack

if __name__ == '__main__':
    socket_org = os.getenv("SOCKET_ORG") or exit(1)
    api_key = os.getenv("SOCKET_API_KEY") or exit(1)
    days_ago = os.getenv("DAYS_AGO") or exit(1)
    report_id = os.getenv("SOCKET_REPORT_ID")

    from_time = days_ago * 24 * 60 * 60 #Convert days to seconds

    core = Core(
        api_key=api_key,
        from_time=from_time,
        report_id=report_id
    )
    issue_data = core.get_issues()
    slack_url = os.getenv("SLACK_WEBHOOK_URL") or exit(1)
    slack = Slack(slack_url)
    for issue in issue_data:
        issue_json = json.loads(str(issue))
        slack.send(issue_json)

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This script is a general tool for connecting to different SIEMs and sending information from Socket

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