@paloaltonetworks/pan-cortex-data-lake v0.1.5

pan-cortex-data-lake-nodejs

This Palo Alto Networks Cloud NodeJS library was created to assist developers with programmatically interacting with the Palo Alto Networks Cortex Data Lake API's.

Installation

Incorporate the pan-cortex-data-lake NodeJS package in your project with the following bash command:

npm i @paloaltonetworks/pan-cortex-data-lake

You can also install the package from its GITHUB repo

npm i git://github.com/PaloAltoNetworks/pan-cortex-data-lake-nodejs

You can now import the package into your NodeJS code.

const cortex = require('@paloaltonetworks/pan-cortex-data-lake');

Source code is written in TypeScript and the build process productes type definition files which means you can leverage strongly type and code auto-complete features.

import * as cortex from '@paloaltonetworks/pan-cortex-data-lake'

Authorization

There are two options to get your application authorized to access customer data using the Cortex Data Lake API:

• Getting a client certificate (platform applications)
• Publishing your application in Cortex hub and using the code grant OAuth2 flow

Use the QueryServiceClient.factory() to create an object instance in any of the previous cases:

Example of a mTLS object instance

async init() {
    const mtlsCert = readFileSync(CERTIFICATE_FILE);
    const mtlsKey = readFileSync(KEY_FILE);
    const qsc = await QueryServiceClient.factory({ cert: mtlsCert, key: mtlsKey });
}

Example using OAuth2 credentials (JWT)

async function init() {
    const credentials = {
        getToken: () => Promise.resolve(ACCESS_TOKEN),
        getEntryPoint: () => 'api.us.cdl.paloaltonetworks.com'
    };
    const qsc = cortex.QueryServiceClient.factory({
        cortexDefCredentials: credentials
    });
}

Take a look to the complementary repo pan-cortex-hub-nodejs with a collection of compatible credential objects as well as full secret repositories (CortexCredentialProvider) and building blocks for a SaaS component to interface with Cortex hub.

Getting started with QueryService

Using stream readable interface

function main() {
    const queryStream = qsc.stream("SELECT * from `" + INSTANCE_ID + ".firewall.traffic` LIMIT 10");
    return new Promise((res, rej) => {
        queryStream.on('error', rej);
        queryStream.on('end', res);
        // each object emitted corresponds to a page of results (any[])
        queryStream.on('data', console.log);
    })
}

Using async iterable interface (introduced in ES2018)

async function main() {
    for await (const page of qsc.iterator("SELECT * from `" + INSTANCE_ID + ".firewall.traffic` LIMIT 10")) {
        console.log(page);
    }
}

Code snippets

Review the folder /examples for quick starting code

Running the integration tests

1. Optional: run npm run build:test to build the mocha integration test (/test directory)
   1. set the CORTEX_TEST_GOODCERT environmental variable to the path to load good client-side certificates. The test suite will try to load a file named process.env[CORTEX_TEST_GOODCERT]+'.cert' and a file named process.env[CORTEX_TEST_GOODCERT]+'.key'
   2. set the environmental variables CORTEX_TEST_BASEFQDN and CORTEX_TEST_TENANTID to map to the Apollo 2.0 environment and tenant you'll be testing
   3. Run npm run test to execute the integration tests