AbuselPDB
AbuseIPDB is a project helping make Web safer by providing a central blacklist for webmasters, system administrators, and other interested parties to report and find IP addresses that have been associated with malicious activity online.
Integrate the AbuselPDB API with the Python API
Setup the AbuselPDB API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate AbuselPDB and Python remarkably fast. Free for developers.
Popular AbuselPDB and Python Actions#
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Overview of AbuselPDB#
AbuseIPDB is a platform providing an API to report and check IP addresses to detect and prevent malicious activities. With the AbuseIPDB API on Pipedream, you can automate the process of monitoring, reporting, and acting upon incidents involving suspect IP addresses. This can mean auto-generating reports for suspicious traffic, cross-referencing with other security data sources, or triggering alerts in real-time for proactive defense measures.
Connect AbuselPDB#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
abuselpdb: {
type: "app",
app: "abuselpdb",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.abuseipdb.com/api/v2/check`,
headers: {
"Key": `${this.abuselpdb.$auth.api_key}`,
},
params: {
ipAddress: `{enter_ip_here}`,
maxAgeInDays: `90`,
},
})
},
})
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}}