Purple Sonar

Monitor your target accounts and identify new opportunities

Integrate the Purple Sonar API with the Go API

Setup the Purple Sonar API trigger to run a workflow which integrates with the Go API. Pipedream's integration platform allows you to integrate Purple Sonar and Go remarkably fast. Free for developers.

Run Go Code with the Go API

Run any Go code and use any Go package available with a simple import. Refer to the Pipedream Go docs to learn more.

 
Try it

Overview of Purple Sonar

The Purple Sonar API offers real-time threat intelligence and URL analysis, crucial for enhancing cybersecurity measures. By integrating with Pipedream, you can create workflows that automate the process of monitoring, analyzing, and responding to potential threats. Use cases include triaging alerts, enriching incident reports with additional data, or even proactively scanning URLs in company communications to pre-emptively block malicious links.

Connect Purple Sonar

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    sonar: {
      type: "app",
      app: "sonar",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api-public.purplesonar.com/api/v1/enrich/domain/google.com`,
      headers: {
        Authorization: `Bearer ${this.sonar.$auth.api_key}`,
      },
    })
  },
})

Overview of Go

You can execute custom Go scripts on-demand or in response to various triggers and integrate with thousands of apps supported by Pipedream. Writing with Go on Pipedream enables backend operations like data processing, automation, or invoking other APIs, all within the Pipedream ecosystem. By leveraging Go's performance and efficiency, you can design powerful and fast workflows to streamline complex tasks.

Connect Go

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package main

import (
	"fmt"

	pd "github.com/PipedreamHQ/pipedream-go"
)

func main() {
	// Access previous step data using pd.Steps
	fmt.Println(pd.Steps)

	// Export data using pd.Export
	data := make(map[string]interface{})
	data["name"] = "Luke"
	pd.Export("data", data)
}