All Projects → ethyca → fidesops

ethyca / fidesops

Licence: Apache-2.0 License
Privacy as Code for DSAR Orchestration: Privacy Request automation to fulfill GDPR, CCPA, and LGPD data subject requests.

Programming Languages

python
139335 projects - #7 most used programming language

Projects that are alternatives of or similar to fidesops

Databunker
Secure storage for personal records built to comply with GDPR
Stars: ✭ 122 (+281.25%)
Mutual labels:  privacy, compliance, gdpr
Gdpr Checklist
The GDPR Checklist
Stars: ✭ 655 (+1946.88%)
Mutual labels:  privacy, compliance, gdpr
Gdpr Tracker
A crowdsourced directory tracking the compliance and security practices of cloud services and their subprocessors
Stars: ✭ 142 (+343.75%)
Mutual labels:  privacy, compliance, gdpr
Datadefender
Sensitive Data Management: Data Discovery and Anonymization toolkit
Stars: ✭ 79 (+146.88%)
Mutual labels:  privacy, compliance, gdpr
Opendsr
A common framework enabling companies to work together to protect consumers' privacy and data rights.
Stars: ✭ 295 (+821.88%)
Mutual labels:  privacy, compliance, gdpr
Data Processing Agreements
Collection of Data Processing Agreement (DPA) and GDPR compliance resources
Stars: ✭ 110 (+243.75%)
Mutual labels:  privacy, compliance, gdpr
kodex
A privacy and security engineering toolkit: Discover, understand, pseudonymize, anonymize, encrypt and securely share sensitive and personal data: Privacy and security as code.
Stars: ✭ 70 (+118.75%)
Mutual labels:  compliance, gdpr
Ml privacy meter
Machine Learning Privacy Meter: A tool to quantify the privacy risks of machine learning models with respect to inference attacks, notably membership inference attacks
Stars: ✭ 167 (+421.88%)
Mutual labels:  privacy, gdpr
Goaccess
GoAccess is a real-time web log analyzer and interactive viewer that runs in a terminal in *nix systems or through your browser.
Stars: ✭ 14,096 (+43950%)
Mutual labels:  privacy, gdpr
RHEL8-STIG
Ansible role for Red Hat 8 STIG Baseline
Stars: ✭ 73 (+128.13%)
Mutual labels:  compliance-as-code, compliance-automation
Amazon S3 Find And Forget
Amazon S3 Find and Forget is a solution to handle data erasure requests from data lakes stored on Amazon S3, for example, pursuant to the European General Data Protection Regulation (GDPR)
Stars: ✭ 115 (+259.38%)
Mutual labels:  privacy, gdpr
Awesome Iam
👤 Identity and Access Management Knowledge for Cloud Platforms
Stars: ✭ 186 (+481.25%)
Mutual labels:  privacy, gdpr
lunasec
LunaSec - Dependency Security Scanner that automatically notifies you about vulnerabilities like Log4Shell or node-ipc in your Pull Requests and Builds. Protect yourself in 30 seconds with the LunaTrace GitHub App: https://github.com/marketplace/lunatrace-by-lunasec/
Stars: ✭ 1,261 (+3840.63%)
Mutual labels:  compliance, gdpr
Trackless
Add a GDPR-friendly Google Analytics opt-in/opt-out button to your site
Stars: ✭ 127 (+296.88%)
Mutual labels:  privacy, gdpr
Cookiescanner
Cookie Scanner for GDPR compliance
Stars: ✭ 126 (+293.75%)
Mutual labels:  privacy, gdpr
prowler
Prowler is an Open Source Security tool for AWS, Azure and GCP to perform Cloud Security best practices assessments, audits, incident response, compliance, continuous monitoring, hardening and forensics readiness. It contains hundreds of controls covering CIS, PCI-DSS, ISO27001, GDPR, HIPAA, FFIEC, SOC2, AWS FTR, ENS and custom security frameworks.
Stars: ✭ 8,046 (+25043.75%)
Mutual labels:  compliance, gdpr
iabtcf-es
Official compliant tool suite for implementing the Transparency and Consent Framework (TCF) v2.0. The essential toolkit for CMPs.
Stars: ✭ 102 (+218.75%)
Mutual labels:  gdpr, gdpr-compliant
havengrc
☁️Haven GRC - easier governance, risk, and compliance 👨‍⚕️👮‍♀️🦸‍♀️🕵️‍♀️👩‍🔬
Stars: ✭ 83 (+159.38%)
Mutual labels:  compliance, gdpr
aws-security-hub-response-and-remediation
Pre-configured response & remediation playbooks for AWS Security Hub
Stars: ✭ 58 (+81.25%)
Mutual labels:  compliance-as-code, compliance-automation
Data Protection Mapping Project
Open Source Data Protection/Privacy Regulatory Mapping Project
Stars: ✭ 96 (+200%)
Mutual labels:  privacy, gdpr

Meet Fidesops: Privacy as Code for DSAR Orchestration

A part of the greater Fides ecosystem.

Latest Version License Code style: black Checked with mypy Twitter

Fidesops banner

Overview

Fidesops (fee-dez-äps, combination of the Latin term "Fidēs" + "operations") is an extensible, deployed engine that fulfills any privacy request (e.g. access request, erasure request) by connecting directly to your disparate databases.

Fidesops overview

🚀 Quick Start

If you're looking for a more detailed introduction to Fidesops, we recommend following our tutorial here.

Run the quickstart in your terminal to give Fidesops a test drive:

Install Docker: https://docs.docker.com/desktop/#download-and-install
Install Make: brew install make
git clone https://github.com/ethyca/fidesops.git
cd fidesops
make quickstart

This runs fidesops in docker along with the necessary data stores. It also spins up a test postgres database and a test mongo database to mimic your application. This quickstart will walk you through executing privacy requests against your system by making a series of API requests to fidesops.

Follow these five easy steps:

Step One: Set up basic configuration (press [enter] to make each API request)

  • Authenticate by creating an Access Token
  • Connect to your application's postgres and mongo databases with ConnectionConfigs
  • Describe the types of data you have and their relationships with Datasets
  • Dictate where to upload your results with StorageConfigs (a local folder for now)

Step Two: Define an Access Policy

Policies help describe what data you care about and how you want to manage it. In this example, you'll create an access Policy,example_request_policy, to get all data with the data category: user.provided.identifiable.

Step Three: Run a Privacy Request to Access Data

Finally, you can issue a Privacy Request using Policy example_request_policy across your test databases for [email protected]. The following response will be uploaded to a local folder (for demo purposes). We've collected identifiable user-provided information for Jane across tables in both the postgres and mongo databases.

{
    "mongo_test:flights": [
        {
            "passenger_information": {
                "full_name": "Jane Customer"
            }
        }
    ],
    "mongo_test:payment_card": [
        {
            "ccn": "987654321",
            "name": "Example Card 2",
            "code": "123"
        }
    ],
    "postgres_example_test_dataset:address": [
        {
            "zip": "54321",
            "street": "Example Place",
            "state": "TX",
            "city": "Example Mountain",
            "house": 1111
        }
    ],
    "mongo_test:customer_details": [
        {
            "birthday": "1990-02-28T00:00:00",
            "gender": "female",
            "children": [
                "Erica Example"
            ]
        }
    ],
    "postgres_example_test_dataset:customer": [
        {
            "email": "[email protected]",
            "name": "Jane Customer"
        }
    ],
    "postgres_example_test_dataset:payment_card": [
        {
            "ccn": 373719391,
            "name": "Example Card 3",
            "code": 222
        }
    ],
    "mongo_test:employee": [
        {
            "email": "[email protected]",
            "name": "Jane Employee"
        }
    ],
    "mongo_test:conversations": [
        {
            "thread": [
                {
                    "chat_name": "Jane C"
                }
            ]
        },
        {
            "thread": [
                {
                    "chat_name": "Jane C"
                },
                {
                    "chat_name": "Jane C"
                }
            ]
        }
    ]
}

Step Four: Create an Erasure Policy

Now you'll create another Policy, example_erasure_policy, that describes how to erase data with the same category, by replacing values with null.

Step Five: Issue a Privacy Request to erase data and verify

The last step is to issue a Privacy Request using example_erasure_policy to remove identifiable user-provided data related to "[email protected]". Then we'll re-run step #3 again to see what data is remaining for data category user.provided.identifiable:

{}

This returns an empty dictionary confirming Jane's fields with data category user.provided.identifiable have been removed.

You've learned how to use the Fidesops API to connect a database and a final storage location, define policies that describe how to handle user data, and execute access and erasure requests. But there's a lot more to discover, so we'd recommend following the tutorial to keep learning.

Documentation

For more information on getting started with Fidesops, how to configure and set up Fidesops, and more about the Fides ecosystem of open source projects:

Support

Join the conversation on:

Contributing

We welcome and encourage all types of contributions and improvements! Please see our contribution guide to opening issues for bugs, new features, and security or experience enhancements.

Read about the Fides community or dive into the development guides for information about contributions, documentation, code style, testing and more. Ethyca is committed to fostering a safe and collaborative environment, such that all interactions are governed by the Fides Code of Conduct.

⚖️ License

The Fides ecosystem of tools (Fidesops and Fidesctl) are licensed under the Apache Software License Version 2.0. Fides tools are built on Fideslang, the Fides language specification, which is licensed under CC by 4.

Fides is created and sponsored by Ethyca: a developer tools company building the trust infrastructure of the internet. If you have questions or need assistance getting started, let us know at [email protected]!

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].