đź“… Webinar - Delivering Security on Your Terms: An Intro to Self-Hosted

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đź“… Webinar - Delivering Security on Your Terms: An Intro to Self-Hosted

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My Databricks Authentication Token leaked! What should I do?

What is a Databricks Authentication Token and how it is used?

A Databricks Authentication Token is a secure credential used to authenticate and authorize access to Databricks resources and services.

Developers use the Databricks Authentication Token for the following main use cases:

  • Accessing Databricks REST API: The token is used to authenticate and authorize API requests made to the Databricks platform, allowing developers to interact programmatically with Databricks resources.
  • Configuring Databricks CLI: Developers can use the token to configure the Databricks Command Line Interface (CLI), enabling them to manage Databricks clusters, jobs, and other resources from the command line.
  • Integrating with CI/CD Pipelines: The token can be used in continuous integration and continuous deployment (CI/CD) pipelines to automate tasks such as deploying Databricks jobs or managing clusters as part of the development workflow.

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1. Code snippets to prevent Databricks Authentication Token hardcoding using environment variables

Using environment variables for storing sensitive information like Databricks Authentication Tokens in your code is a secure practice for the following reasons:

  • Environment variables are not hardcoded in the codebase, making it harder for attackers to access them through source code.
  • Environment variables are stored outside of the code repository, reducing the risk of exposure in case of a breach.
  • Environment variables can be easily managed and rotated without the need to modify the code, improving security maintenance.

How to secure your secrets using environment variables

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2. Code snippet to prevent Databricks Authentication Token hardcoding using AWS Secrets Manager

Using AWS Secrets Manager to manage Databricks Authentication Tokens is a secure way to handle sensitive data. Here are code snippets in five different programming languages that demonstrate how to retrieve the Databricks Authentication Token from AWS Secrets Manager.

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3. Code snippet to prevent Databricks Authentication Token hardcoding using HashiCorp Vault

Using HashiCorp Vault for managing Databricks Authentication Tokens is a great way to enhance security. Here are code snippets in five different programming languages for securely handling a Databricks Authentication Token using HashiCorp Vault.

Remember to replace the VAULT_ADDR and VAULT_TOKEN with your Vault server address and authentication token. The snippets assume that the Databricks Authentication Token is stored under the api_key field within Vault. The specifics of the Vault path and field names should be adjusted to match your Vault setup.

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4. Code snippet to prevent Databricks Authentication Token hardcoding using CyberArk Conjur

Using CyberArk Conjur to manage Databricks Authentication Token is a secure way to handle sensitive data. Here are code snippets in five different programming languages that demonstrate how to retrieve the Databricks Authentication Token from CyberArk Conjur.

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How to generate a Databricks Authentication Token?

To generate a Databricks Authentication Token, follow these steps:

  1. Log in to your Databricks account.
  2. Click on the user profile icon in the upper right corner.
  3. Select "User Settings" from the dropdown menu.
  4. Go to the "Access Tokens" tab.
  5. Click on the "Generate New Token" button.
  6. Enter a description for the token to help you identify it later.
  7. Set the expiration date for the token if needed.
  8. Click on the "Generate" button to create the token.
  9. Copy the generated token and securely store it for future use.

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My Databricks Authentication Token leaked, what are the possible reasons?

There are several reasons why a Databricks Authentication Token might have been leaked:

  • Improper storage: If the token is stored in an insecure location or in plain text, it can be easily accessed by unauthorized users.
  • Weak access controls: If the access controls for the token are not properly configured, malicious actors may be able to obtain the token through unauthorized means.
  • Code vulnerabilities: If there are vulnerabilities in the code that handles the token, such as injection attacks or insecure API endpoints, the token may be exposed.
  • Accidental exposure: Developers may inadvertently include the token in publicly accessible code repositories or share it in insecure communication channels.

What are the risks of leaking a Databricks Authentication Token

Leaking a Databricks Authentication Token can pose serious risks to the security of your application and data. It is important for developers to understand the potential consequences of such a breach:

  • Data Breach: An attacker who gains access to your Databricks Authentication Token can potentially access sensitive data stored in your Databricks account.
  • Unauthorized Access: With the token, an attacker can impersonate your application and gain unauthorized access to resources within your Databricks environment.
  • Data Manipulation: An attacker with access to your Databricks account can manipulate data, leading to potential data loss or corruption.
  • Financial Loss: If sensitive information or intellectual property is compromised due to a leaked token, it can result in financial losses for your organization.
  • Reputation Damage: A data breach or security incident resulting from a leaked token can damage your organization's reputation and erode customer trust.

It is crucial to follow best practices for secret management and detection to prevent the leakage of sensitive information such as Databricks Authentication Tokens. Educating yourself and your team on the importance of safeguarding these tokens is essential in maintaining the security of your applications and data.

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Databricks Authentication Token security best practices

  • Avoid embedding the secret directly in your code. Instead, use environment variables or secrets managers‍
  • Secure storage: store the Databricks Authentication Token in a secure location, such as a password manager or a secrets management service.
  • Regular rotation: periodically rotate the API key to minimize the risk of long-term exposure.
  • Restrict permissions: apply the principle of least privilege by only granting the key the minimum necessary permissions.
  • Monitor usage: regularly check the usage logs for any unusual activity or unauthorized access attempts.
  • Implement access controls: limit the number of users who have access to the secret and enforce strong authentication measures.
  • Use a secrets manager: utilize secret management tools like CyberArk or AWS Secrets Manager for enhanced security.

By adhering to the best practices, you can significantly reduce the risk associated with Databricks Authentication Token usage and improve the overall security of your Databricks Authentication Token implementations.

Exposing secrets on GitHub: What to do after leaking Credential and API keys

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Databricks Authentication Token leak remediation: what to do

What to do if you expose a secret: How to stay calm and respond to an incident [cheat sheet included]

How to check if Databricks Authentication Token was used by malicious actors

  • Review Access Logs: Check the access logs of your Databricks Authentication Token account for any unauthorized access or unusual activity. Pay particular attention to access from unfamiliar IP addresses (if you haven’t set up a specific allow list) or at odd hours.
  • Monitor Usage Patterns: Look for anomalies in the usage patterns, such as unexpected spikes in data access or transfer.
  • Check Active Connections and Operations: Review the list of active connections and recent operations on your database. Unusual or unauthorized operations might indicate malicious use.
  • Audit API Usage: If possible, audit the usage of your API key through any logging or monitoring services you have integrated with Databricks Authentication Token. This can give insights into any unauthorized use of your key.

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Steps to revoke the Databricks Authentication Token

Generate a new Databricks Authentication Token:

  • Log into your Databricks Authentication Token account.
  • Navigate to the API section and generate a new API key.

Update Services with the new key:

  • Replace the compromised key with the new key in all your services that use this API key.
  • Ensure all your applications and services are updated with the new key before deactivating the old one.

Deactivate the old Databricks Authentication Token:

  • Once the new key is in place and everything is functioning correctly, deactivate the old API key.
  • This can typically be done from the same section where you generated the new key.

Monitor after key rotation:

  • After deactivating the old key, monitor your systems closely to ensure that all services are running smoothly and that there are no unauthorized access attempts.

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How to understand which services will stop working

  • Inventory of services: keep an inventory of all services and applications that utilize your Databricks Authentication Token.
  • Communication and documentation: Ensure that your team is aware of which services are dependent on the key. Maintain documentation for quick reference.
  • Testing: before deactivating the old key, test your services with the new key in a staging environment. This helps in identifying any services that might face issues post rotation.
  • Fallback strategies: Have a fallback or emergency plan in case a critical service fails after the key rotation. This might include temporary measures or quick rollback procedures.

In summary, the remediation process involves identifying potential misuse, carefully rotating the key, and ensuring minimal disruption to services. Being proactive and having a well-documented process can greatly reduce the risks associated with a compromised API key.

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What about other secrets?

GitGuardian helps developers keep 350+ types of secrets out of source code. GitGuardian’s automated secrets detection and remediation solution secure every step of the development lifecycle, from code to cloud:

  • On developer workstations with git hooks (pre-commit and pre-push);
  • On code sharing platforms like GitHub, GitLab, and Bitbucket;
  • In CI environments (Circle CI, Travis CI, Jenkins CI, GitHub Actions, and many more);
  • In Docker images.

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Environment Variables
Environment Variables
Environment Variables

charge

nullable string

For card errors, the ID of the failed charge.

payment_method_type

nullable string

If the error is specific to the type of payment method, the payment method type that had a problem. This field is only populated for invoice-related errors.

doc_url

nullable string

A URL to more information about the error code reported.

request_log_url

nullable string

A URL to the request log entry in your dashboard.

charge

nullable string

If the error is specific to the type of payment method, the payment method type that had a problem. This field is only populated for invoice-related errors.

Hide
Show
child attributes

type

enum

For some errors that could be handled programmatically, a short string indicating the error code reported.

charge

nullable string

If the error is specific to the type of payment method, the payment method type that had a problem. This field is only populated for invoice-related errors.

Hide
Show
child attributes

type

enum

For some errors that could be handled programmatically, a short string indicating the error code reported.

payment_intent

nullable object

The PaymentIntent object for errors returned on a request involving a PaymentIntent.

setup_intent

nullable object

The SetupIntent object for errors returned on a request involving a SetupIntent.

Hide
Show
child attributes

type

enum

For some errors that could be handled programmatically, a short string indicating the error code reported.

Hide
Show
child attributes

type

enum

For some errors that could be handled programmatically, a short string indicating the error code reported.

CLIENT LIBRARIES

$ gem install stripe
$ pip install stripe
$ composer require stripe/stripe-php
MAVEN
<dependency>
  <groupId>com.stripe</groupId>
  <artifactId>stripe-java</artifactId>
  <version>24.16.0</version>
</dependency>

GRADLE
compile "com.stripe:stripe-java:24.16.0"
$ npm install --save stripe
$ go get github.com/stripe/stripe-go/v76
$ nuget install Stripe.net
SHOW
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