Integrate the Verdict as a Service API with the Python API

Setup the Verdict as a Service API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Verdict as a Service and Python remarkably fast. Free for developers.

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Popular Verdict as a Service and Python Actions#

Request Verdict For A File with the Verdict as a Service API

Scans a file for malware and other threats. See the docs here

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Run Python Code with the Python API

Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.

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Overview of Verdict as a Service#

Verdict as a Service (VaaS) API provides a powerful interface for automating the analysis of files and URLs for potential threats. Leveraging the capabilities of Pipedream, users can create sophisticated workflows that trigger actions based on the results of the threat analysis. From email attachments to submitted URLs, VaaS can be integrated into a variety of security and data processing pipelines to ensure safety and compliance.

Connect Verdict as a Service#

import Vaas from "gdata-vaas";

export default defineComponent({
  props: {
    verdict_as_a_service: {
      type: "app",
      app: "verdict_as_a_service",
    }
  },
  async run({steps, $}) {
// create vaas client
    const vaas = await createVaasWithClientCredentialsGrant(
      CLIENT_ID,
      CLIENT_SECRET,
      TOKEN_URL,
      VAAS_URL
    );
    // request verdict for file
    const verdict = await vaas.forFile(response.data);
    if (verdict === "Malicious") {
      console.log("This was malware.");
    }
  },
})

Overview of Python#

Develop, run and deploy your Python code in Pipedream workflows. Integrate seamlessly between no-code steps, with connected accounts, or integrate Data Stores and manipulate files within a workflow.

This includes installing PyPI packages, within your code without having to manage a requirements.txt file or running pip.

Below is an example of using Python to access data from the trigger of the workflow, and sharing it with subsequent workflow steps:

Connect Python#

def handler(pd: "pipedream"):
  # Reference data from previous steps
  print(pd.steps["trigger"]["context"]["id"])
  # Return data for use in future steps
  return {"foo": {"test":True}}

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