Subject
41 entries
Privacy
Bookmarks
The Open Anonymity Project: AI user privacy infrastructure
The Open Anonymity Project builds tools and infrastructure for AI user privacy — an open-source effort to give users anonymity options when interacting with AI systems. Still early, but addresses a real gap as AI becomes more central to daily life.
IronClaw: secure personal AI assistant from NEAR AI
IronClaw is a privacy-focused personal AI assistant from NEAR AI, implemented in Rust with WASM sandboxing for untrusted tools, credential protection at the host boundary, and hybrid search memory. Your data never leaves your control.
Wealthfolio: offline open-source portfolio tracker
Wealthfolio is an open-source, offline-first desktop portfolio tracker that stores all financial data locally. No subscriptions, no cloud sync, no account required — just a standalone app for tracking investments privately.
Handy: Local Push-to-Talk Speech-to-Text
Handy is a free, open-source, cross-platform push-to-talk speech-to-text app that transcribes locally and pastes into any text field. No cloud, no accounts — just press, speak, release.
Spokenly: Voice-to-Text with Local AI Models
Spokenly is a voice-to-text app for Mac and iOS with local Whisper/Parakeet models, 100+ language support, and an agent mode for hands-free system control. Free for local models, $9.99/month for cloud features.
Monologue: Context-Aware Voice Dictation
Monologue is an AI-powered voice dictation app for Mac and iOS — context-aware formatting, 100+ languages, auto dictionary for your vocabulary. Privacy-first: no audio stored, zero LLM data retention. Part of the Every bundle.
OPSEC Guide: operational security for individuals
An operational security guide covering digital privacy practices — likely covering threat modeling, personal information reduction, secure communications, and metadata hygiene. Community-produced OPSEC reference for privacy-conscious individuals.
webXray: Privacy Compliance Search Engine
webXray is a forensic web analysis platform that detects real tracking violations across 1.2M+ websites — built from a decade of academic research by Dr. Timothy Libert. Used by law firms, Fortune 100 compliance teams, and privacy litigators.
Ava: All-in-One Desktop App for Running LLMs Locally
Ava is an all-in-one desktop app for running LLMs locally — chat, image generation, and model management in a single native application. An alternative to LM Studio targeting users who want everything bundled together without CLI setup.
Sunscreen FHE: Private Information Retrieval via Matrix Operations
Sunscreen's documentation on Private Information Retrieval via Fully Homomorphic Encryption — demonstrating how FHE enables querying a database without the server learning what you searched for. A practical introduction to FHE programming via a concrete PIR example.
AI Browser Extensions Are a Security Nightmare
Kolide's analysis of why AI browser extensions are a security and privacy risk — they require broad DOM access permissions that give them access to every page you visit, including sensitive internal tools. A practical warning for enterprise security teams evaluating AI productivity tools.
Tearing Down the Rewind App
Kevin Chen's technical teardown of the Rewind app — which records your entire screen continuously while claiming not to tax system resources. The teardown reveals clever use of on-device Apple ML frameworks, differential compression, and local OCR to make this technically feasible.
Rhasspy — Offline Private Voice Assistant
Rhasspy is a fully offline, privacy-first voice assistant framework supporting many human languages — no cloud required. Designed for Home Assistant integration and runs entirely on local hardware like a Raspberry Pi.
Self-Hosting Guide
A comprehensive GitHub reference covering self-hosted alternatives to cloud services — NAS, media servers, home automation, password managers, and more. The definitive starting point for anyone building a home server setup.
Logseq: A Privacy-First, Open-Source Knowledge Base
Logseq is a privacy-first, open-source knowledge base and daily journaling tool built around outliner-style pages with bidirectional linking. It positions itself as a local-first alternative to Roam Research and Notion, with all data stored in plain text on your own machine.
YunoHost: Self-Hosted Server for Everyone
YunoHost is an open-source server OS that makes self-hosting web apps as simple as clicking install — Nextcloud, Gitea, Mastodon, and 100+ others available in one catalog. It handles DNS, SSL, user management, and backups automatically, dramatically lowering the barrier to self-hosting.
Piranha: A GPU Platform for Secure Computation
Piranha (USENIX Security 2022) is a GPU platform for secure multi-party computation that exploits GPU parallelism to accelerate MPC protocols by 10-15× over CPU implementations. It shows that GPU hardware can close the practical performance gap for privacy-preserving machine learning at scale.
RethinkDNS: Serverless DNS Resolver
RethinkDNS is an open-source, serverless DNS resolver with built-in ad and tracker blocking that deploys to Cloudflare Workers, Deno Deploy, or Fly.io — giving you a private, self-hosted DNS-over-HTTPS endpoint for free on serverless infrastructure.
Espresso Systems: Shared Sequencing and Privacy for L2 Rollups
Espresso Systems is building shared sequencing and privacy infrastructure for Ethereum L2 rollups — a sequencer marketplace that multiple rollups can use to get MEV protection, fast finality, and cross-rollup atomicity. Positioned at the intersection of rollup scaling and the decentralized sequencer problem.
Privacy-Preserving Machine Learning with Fully Homomorphic Encryption for Deep Neural Networks
This paper demonstrates running deep neural network inference entirely on encrypted data using fully homomorphic encryption, so the server never sees plaintext inputs or outputs. It makes encrypted ML inference practical by combining FHE with approximation-friendly neural network architectures.
Umbrel: Personal Server OS for Self-Hosting
Umbrel is a personal server OS for self-hosting — one-click installs for Bitcoin nodes, Lightning Network nodes, Nextcloud, and dozens of other apps on a Raspberry Pi or home server. The friendliest on-ramp to self-sovereign infrastructure.
Brave Browser Hardening Guide
CHEF-KOCH's GitLab guide for hardening Brave Browser beyond its defaults — covering flags, extension recommendations, and configuration changes to minimize fingerprinting and data leakage. Useful reference for privacy-focused browser setup.
Orchid: Decentralized VPN Marketplace
Orchid is a decentralized VPN marketplace where users pay for bandwidth with OXT tokens on Ethereum — an attempt to build a censorship-resistant, market-driven alternative to traditional VPN providers. Interesting experiment in crypto-native privacy infrastructure.
Swash: Web3 Data Ownership and Incentivized Data Flows
Swash is a Web3 platform that lets individuals collect, control, and monetize their own browsing and behavioral data via a browser extension and a tokenized marketplace. The interesting design challenge is making data sovereignty economically compelling for all three stakeholders: users who own data, businesses that buy it, and developers who build on it.
Secure Multiparty Computation (MPC)
Yehuda Lindell's accessible overview of secure multiparty computation (MPC) — how parties can jointly compute on private inputs without revealing them. Traces the field from Yao's two-party garbled circuits through modern practical protocols used in industry.
CrypTen: Secure Multi-Party Computation Meets Machine Learning
CrypTen is a PyTorch-compatible framework from Facebook AI Research that wraps secure multi-party computation protocols behind a familiar tensor API, making private inference and training accessible to ML practitioners without cryptography expertise. The bet is that adoption bottlenecks for privacy-preserving ML are mostly about developer experience, not theoretical limits.
Secure Byzantine-Robust Machine Learning
He, Karimireddy, and Jaggi propose a two-server cryptographic protocol that simultaneously achieves Byzantine robustness, input privacy, and local differential privacy for distributed machine learning — three properties usually addressed separately. Bridges the privacy-robustness gap in federated learning.
DISCO: Decentralized Privacy-Preserving ML Training
DISCO (from EPFL) is a decentralized, privacy-preserving ML training framework using peer-to-peer networking — no central server, nodes train locally and share model updates directly. Extends federated learning to remove the trusted aggregator requirement.
Personal Security Checklist
Lissy93's personal security checklist on GitHub — 300+ categorized tips for protecting digital security and privacy. A practical reference for hardening accounts, devices, and browsing habits without becoming a full-time security researcher.
SEPIA: Open-Source Voice Assistant
SEPIA is an open-source, self-hosted voice assistant framework — a privacy-preserving alternative to Alexa, Google Assistant, and Siri. Runs entirely on your own server, with custom skill development support.
Facebook Shadow Profiles
Aguiar, Peukert, Schaefer, and Ullrich (CESifo, 2022) quantify Facebook's cross-web tracking via its engagement buttons, finding that 52% of websites visited by US users employ Facebook's tracking technology. Facebook builds shadow profiles even for non-users — the scope of cross-platform surveillance is much larger than most users assume.
Tunneling Tunnels: Multi-Hop VPN with Multitun
cryptostorm's writeup on multitun — nesting multiple VPN tunnels inside each other for layered anonymity. The multi-hop VPN pattern separates entry and exit knowledge, so no single provider can link your identity to your traffic.
Quick and Dirty Anon Building Guide
A practical guide to building crypto projects anonymously — covering wallet setup, separate identity compartmentalization, and social media opsec. Reflects the 2021-2022 pattern where many crypto builders went anon to reduce personal legal and regulatory exposure.
PipelineDP: Differentially Private Data Aggregation
PipelineDP is an open-source framework from Google and OpenMined for differentially private data aggregation at scale — extract insights from large datasets while provably protecting individual privacy. Brings differential privacy out of academia and into data pipeline tooling.
Hackers Backdoor the Human Brain
ExtremeTech coverage of researchers demonstrating that a consumer EEG headset could be used to extract sensitive information (PINs, locations) from subjects without their explicit cooperation — essentially a side-channel attack on the human brain. An early marker of privacy concerns in BCI technology.
Target Practice: The Power of Predictive Analytics
Forbes coverage of Target's predictive analytics program — the famous pregnancy prediction story that showed retail chains could infer major life events from purchase patterns. A case study in both the power and the social friction of behavioral prediction at scale.
How the NSA Analyzes Call Metadata
GigaOm's technical explanation of how the NSA processes bulk call metadata — published in June 2013 immediately after the Snowden revelations. The article explains the graph analysis techniques that make even metadata (not call content) a powerful surveillance tool.
A Personal API
Naveen Selvadurai (Foursquare co-founder) on the idea of building a personal API — a structured endpoint for your own life data that others (with permission) could query. An idealistic vision of personal data sovereignty that anticipated later discussions about data portability and self-sovereign identity.
VPN Services That Take Your Anonymity Seriously — 2013 Edition
TorrentFreak's annual survey of VPN providers that maintain genuine no-log policies — the 2013 edition. The canonical reference for evaluating VPN privacy claims before the category was commoditized.
Coming Soon: Apps That Use Your DNA
ReadWrite's 2012 preview of consumer apps built on top of personal genomic data — when 23andMe and others were opening APIs for third-party developers to build health and ancestry tools. An early look at a platform shift that never quite scaled as expected.
How Big Data Is Going to Change Entrepreneurship
Summary of the 2012 Stanford entrepreneurship conference on Big Data — panelists argued data was growing faster than Moore's Law, creating the next oil economy, with advertising and insurance as the most immediately impacted sectors. An early articulation of what became the data economy thesis.