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GitHub Awesome Privacy and Privacy Engineering Lists

A verified review of the leading GitHub Awesome lists for privacy and privacy engineering, checked in August 2026. Covers which lists are still actively maintained, which have gone dormant, and the privacy-enhancing technologies worth going to directly rather than through a curated list.
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GitHub’s “Awesome” lists are community-curated directories of tools and resources on a single topic. For privacy, they are among the fastest ways to find working software — and among the easiest ways to end up recommending something that quietly stopped being trustworthy two years ago.

This review separates the lists that are genuinely maintained from the ones that are not, and draws a distinction the category usually blurs: consumer privacy tooling and privacy engineering are not the same discipline. Both matter. They serve different people solving different problems.

All repositories below were verified in August 2026. Star counts and last-commit dates are accurate as of that check.

How to judge an Awesome list

A curated list is only as good as its last commit. Before trusting one, four things are worth checking.

Signal What to look for Why it matters
Maintenance cadence Commits within the last 3–6 months Privacy tools change ownership, funding, and jurisdiction. A stale list recommends services that no longer deserve it.
Scope discipline A clear inclusion rule Lists that accept every pull request become link dumps, not curation.
Licence CC0, MIT, or similar Determines whether you can reuse the content in internal documentation.
Delivery Searchable site, not just a README A 3,000-line README is unusable at the point of decision.

The last point separates the leaders from the rest. Both of the top consumer lists now ship a searchable web front end.

Consumer privacy lists

These catalogue privacy-respecting alternatives to mainstream services: messaging, email, browsers, search, cloud storage, note-taking. The audience is an individual hardening their own digital footprint, or a practitioner recommending tools to non-technical clients.

List Stars Last update Scope Verdict
Lissy93/awesome-privacy 9,740 Aug 2026 Software and services, with a searchable site at awesome-privacy.xyz Start here. Most actively maintained, best delivery.
pluja/awesome-privacy 19,522 Jul 2026 Broadest catalogue; explicit “avoid / instead use” framing Most comprehensive. Strong on the reasoning behind each recommendation.
paulaime/awesome-privacy 405 Jul 2026 Smaller, tighter selection Useful as a shortlist when the larger lists feel overwhelming.
vlvagerviwager/protect-your-privacy 70 Jul 2026 Written for non-technical readers; covers dark patterns Good for client education and awareness material.
KevinColemanInc/awesome-privacy 1,027 Jan 2024 Limiting personal data leaks Dormant. Historical interest only.
Narayana108/awesome-privacy 39 Jan 2023 Open-source privacy software Dormant. Superseded by the lists above.

The two dormant entries are retained here deliberately rather than deleted. If you encounter them elsewhere, you should know they are no longer maintained.

Privacy engineering lists

Privacy engineering is a distinct discipline: designing systems so that privacy properties hold by construction, rather than by policy. It covers threat modelling for privacy, de-identification, data flow mapping, and the privacy-enhancing technologies below. The community has produced far fewer curated lists here, and only one is currently maintained.

List Stars Last update Verdict
mplspunk/awesome-privacy-engineering 198 Aug 2026 The reference list. Covers standards, research, tooling, and career resources.
AbductiveReason/AwesomePrivacyEngineering 68 Aug 2023 Dormant. Some useful academic references, but not current.

The thinness of this category is itself informative. Privacy engineering is younger than consumer privacy advocacy, and much of its knowledge still lives in standards documents and conference papers rather than GitHub READMEs.

Privacy-enhancing technologies worth knowing directly

Curated lists point at these. If you are actually building, it is more efficient to go to the implementations. Each of the following is actively maintained.

Technique What it solves Reference implementation
Differential privacy Publishing statistics without revealing whether any individual was in the dataset google/differential-privacy, opendp/opendp
PII detection and redaction Finding and masking personal data in unstructured text, images, and records microsoft/presidio
Statistical anonymisation Applying k-anonymity, l-diversity and related models to structured data arx-deidentifier/arx
Federated and private ML Training on data that never leaves its owner’s infrastructure OpenMined/PySyft
Homomorphic encryption Computing on encrypted data without decrypting it jonaschn/awesome-he
Secure multi-party computation Joint computation across parties that trust each other with nothing rdragos/awesome-mpc

For a practitioner-focused view of the encryption layer specifically, see our companion piece on data encryption tools for privacy engineering.

Beyond GitHub, Privacy Guides is the strongest non-list resource in this space — an actively maintained, editorially reviewed site rather than a pull-request queue.

Where curated lists stop

A list tells you a tool exists. It does not tell you whether deploying it satisfies a legal obligation — and that gap is where most privacy programmes fail.

Differential privacy is a good illustration. Adding calibrated noise to a dataset does not automatically render it anonymous under the GDPR. Recital 26 turns on whether re-identification is reasonably likely by any means, accounting for cost, time, and available technology. That is a legal test applied to an engineering artefact, and answering it requires reading the epsilon parameter and the case law at the same time. The same applies to pseudonymisation under Article 4(5), to de-identified training data under the AI Act, and to transfer impact assessments where the technical measure is doing the compliance work.

No Awesome list resolves that. It needs someone who can evaluate the implementation and the obligation together.

That combination is what Up Secure exists to provide — see our work in privacy and security engineering and GDPR compliance.

Verification

Every repository linked above was checked against the GitHub API in August 2026 for availability, archive status, licence, and most recent commit. Lists marked dormant remain publicly accessible but have received no substantive updates for more than a year.

Working on exactly this?

Up Secure advises on the frameworks and engineering practices this library covers — from a first gap assessment to certification.

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