标签：#Privacy

A U.S. citizen has asked a court to throw out the government's claim that he gave over a passcode to border authorities that wiped his phone's data, opening up fresh questions about a person's constitutional rights at the U.S. border.

Many online image converters require users to upload their files to a remote server before processing. For ordinary images this may be acceptable, but for personal photos, screenshots and documents, privacy becomes an important concern. I built a lightweight online image converter that processes images directly in the browser. It currently supports: JPG PNG WebP HEIC GIF SVG BMP TIFF Why browser-based processing? The main goal was to make image conversion simple, fast and privacy-friendly. Because the conversion happens locally: Images are not uploaded to a server Users do not need to create an account There is no installation process Network upload time is avoided Private files remain on the user’s device The basic workflow is simple: Select an image Choose an output format Convert the file Download the result Challenges Browser-based image conversion still has some limitations. Different browsers support image formats differently, especially formats such as HEIC and TIFF. Large images may also consume more device memory during processing. Some format features may not be preserved after conversion. For example, transparency may be lost when converting to JPG, and animated images may become static depending on the selected output format. These limitations need to be handled through clear prompts and error messages.

Introduction Polymarket , and on-chain prediction markets like it, kept bothering me for one reason. Polymarket |世界最大の予測市場™ Polymarketは世界最大の予測市場であり、さまざまなトピックにわたって将来のイベントを取引することで、最新情報を入手し、知識から利益を得ることができます。 polymarket.com Who bet on what is visible in near real time. The moment a whale places a big bet on one outcome, everyone watching piles in behind them, and the odds move accordingly. That's not manipulation — it's just what happens with a public ledger. But it doesn't satisfy the simple wish to not reveal your prediction before everyone else does. So: could you build a prediction market that keeps your pick hidden until voting closes? To find out, I built Hidden League Forecast on Midnight , a privacy-focused blockchain. It's an MVP where you just guess the winner of a fictional soccer league (the World Cup just ended, so soccer was on my mind). Note What's a prediction market? A mechanism that expresses predictions about future events as prices. Think "which team will win the World Cup match," for example. If you want to learn more about prediction markets, this resource (Japanese) is a great start: https://zenn.dev/barabara/books/prediction-markets-structure The backend is written in Compact , Midnight's smart contract language. Note It combines the commit-reveal pattern with zero-knowledge proofs so that "the content of your prediction stays hidden, while only the aggregate stake becomes public." In this article, I'll walk through the contract code, showing what stays hidden and what becomes public at each step. Note This app runs on testnet. Demo Video After connecting Lace Wallet, you see your Shielded Address and balance. From here you can deploy a new market or enter an existing contract address to join one. The Overall Flow What's actually happening is simple. OPEN → REVEAL → AWAITING RESULT → RESOLVED → CLAIM Connect Lace Wallet, then deploy a market or join an existing one Pick one of 4 teams (Amber Foxes / Cedar Owls / Harbor Whales / Meadow Bears) and

In October 2017, researcher Mathy Vanhoef published an attack that broke WPA2, the encryption that had protected almost every Wi-Fi network on the planet for over a decade. The surprise was how it worked. KRACK did not guess your Wi-Fi password or brute-force any key. It tricked your device into installing a key it had already used, and that single mistake unraveled the encryption. WPA2 replaced the badly broken WEP standard in 2004 and quickly became the baseline for wireless security. For thirteen years it held up well. The passphrase-based version most homes use (WPA2-Personal) was vulnerable to offline password guessing if you chose a weak passphrase, but the protocol itself was considered sound. KRACK, short for Key Reinstallation Attack, was different. It targeted a flaw in the WPA2 standard itself, which meant every correct implementation was affected. The four-way handshake, briefly When a device joins a WPA2 network, the client and the access point run a four-message exchange called the four-way handshake. Both sides already share a secret (derived from the passphrase or from an enterprise authentication server). The handshake uses that shared secret to agree on a fresh session key, the Pairwise Transient Key, that will actually encrypt the traffic for this session. The important part is message three. The access point sends message three to tell the client the key is ready, and the client responds with message four and installs the key. Once installed, that key encrypts frames using a counter, called a nonce or packet number, that increments with every frame. The security of the encryption depends on one rule: a given key must never encrypt two different frames with the same nonce. The reinstallation trick Wi-Fi is a lossy medium. Messages get dropped. So the standard says that if the access point does not receive message four, it retransmits message three. When the client receives a retransmitted message three, it reinstalls the same key and, critically,

MSG’s sprawling surveillance system can monitor guests down to the second. Its owners made an exception for the pop star’s rehearsal dinner.

Letting a stranger contact a car owner without giving them the number There is a small, very common problem in Indian cities that turns out to be a surprisingly good systems design exercise. A car is parked badly. It is blocking a gate, a driveway, another car. Someone needs the owner to move it, right now. The traditional fix is a phone number written on a sticker on the windscreen. That works. It also means a stranger — any stranger, forever — has the owner's personal number. Why the sticker is worse than it looks Once a number is visible on a windscreen, a few things follow: It gets scraped. Numbers on vehicles end up in marketing lists. It cannot be revoked. Change your number and every sticker you own is now wrong. It has no context. A 2am call could be a genuine emergency or someone who saw the number three months ago. It is a safety issue for some owners in a way it is not for others. A number attached to a vehicle, at a known parking spot, at predictable times, is more information than most people realise they are publishing. So the requirement is oddly specific: a stranger must be able to reach the owner, immediately, without ever learning how to reach them again. That constraint is what makes this interesting. The naive version, and why it fails First instinct: put a QR code on the vehicle that opens a page with a "call owner" button, and put the number behind the button. This solves nothing. The number is still in the page source. Anyone who wants it can get it, and now you have added a scan step for the honest majority while stopping none of the dishonest minority. Second instinct: put a contact form behind the QR. The stranger types a message, the owner gets a notification. Better on privacy, useless in practice. The person needs the car moved in the next ninety seconds. They are not filling in a form and waiting for an email. If the fast path is not there, they go back to writing an angry note. The real requirement is synchronous contact with asynchron

The next time you’re locked out of your Google account, you can use your face as part of the account recovery process.

Sending a photo feels simple. You choose an image, tap Send, and a few seconds later it appears on someone else's phone. Behind that simple action, however, several things may happen that most people never notice. It Starts on Your Device The photo already exists on your phone before you send it. Depending on your device settings, it may also be part of your gallery or included in local or cloud backups. Before the Photo Is Sent Most messaging apps prepare the image before sending it. They may reduce the file size, create a preview, or optimize it so it can be delivered faster. These steps happen automatically in the background. Sending the Photo If the app supports end-to-end encryption, the photo is encrypted before it leaves your device. This helps protect the image while it is traveling across the internet. After that, the message is routed through the app's delivery infrastructure until it reaches the recipient. After It Arrives Once the recipient opens the photo, it exists on their device. Depending on the app and their settings, it may also be saved to the phone's gallery or included in future backups. At this point, the recipient can also take a screenshot or forward the image to someone else. Encryption protects the photo while it is being transmitted, but it cannot control what happens after the recipient has access to it. Final Thoughts When we send a photo, we often think only about the moment we press Send. In reality, there can be several stages between your device and the recipient, and in some cases, multiple copies of the same image may exist over time. Understanding this process is an important part of understanding digital privacy. While researching these privacy challenges, I started building VeilComm to explore how private communication could give users more control over their data—not just while it's being transmitted, but throughout its entire lifecycle.

Federal lawyers say anti-mask laws would endanger immigration agents, citing an ICE face-recognition art project that doesn’t actually work.

The new U.K. government scrapped a digital ID program that millions of British people opposed, in place of a tax cut to tackle the cost of living.

It’s a lot : According to information obtained by The Tech , MIT is spending over $3 million on more than 500 AI surveillance cameras in academic buildings, residence halls, and outdoor areas along Memorial Drive. Installation of the new cameras, along with the wiring and infrastructure that will support them, began November 2025 and will likely continue until September 2026. Technical specifications for the cameras suggest that they will be capable of collecting real-time face and object classification data, including detection of motion, loitering, crowds, face masks, and camera tampering. Individuals can also be automatically classified on the basis of clothing color, gender, and age, up to a distance of 35 feet (11 meters) from the camera. According to a statement from MIT spokesperson Kimberly Allen, any collected data is “retained up to 30 days,” unless an exception is granted...

Every time I needed to check whether my microphone actually worked before a call, or whether a key on a used keyboard was dead, I ended up on some sketchy "free online tester" that wanted an account, showed six ad banners, and — the worst part — happily streamed my webcam to a server I knew nothing about. So I built the thing I actually wanted: TestOnDevice — 118+ device tests that run 100% in the browser. No installs, no account, and nothing you record ever leaves your machine. Here's what I learned building it. The core constraint: the network is off-limits The single rule that shaped the whole project: no device data touches a server. No webcam frames, no audio buffers, no keystrokes, no sensor readings. That constraint turned out to be freeing rather than limiting, because modern browser APIs are genuinely powerful. Almost every "device test" is just a Web API plus a bit of rendering: What you're testing The API doing the work Microphone / speakers MediaDevices.getUserMedia , Web Audio ( AnalyserNode ) Webcam getUserMedia , <video> , MediaStreamTrack.getSettings() Keyboard keydown / keyup , KeyboardEvent.code Mouse / touch / stylus Pointer Events, PointerEvent.pressure Gamepads Gamepad API MIDI keyboards Web MIDI API Display ( dead pixels , refresh rate ) Fullscreen + requestAnimationFrame Motion / orientation DeviceOrientationEvent , DeviceMotionEvent A live mic meter, entirely local The microphone test is a good example of how little you need. Grab a stream, wire it into an AnalyserNode , and compute RMS on each frame for a level meter — no recording, no upload: const stream = await navigator . mediaDevices . getUserMedia ({ audio : true }); const ctx = new AudioContext (); const analyser = ctx . createAnalyser (); ctx . createMediaStreamSource ( stream ). connect ( analyser ); const data = new Uint8Array ( analyser . frequencyBinCount ); function tick () { analyser . getByteTimeDomainData ( data ); let sum = 0 ; for ( const v of data ) { const x = ( v - 128 )

A video from Gamers Nexus explains how, after connecting a new LG UltraGear monitor to a PC running Windows 11 for the first time, Windows Update is silently installing LG driver updates and the LG Monitor App Installer, without so much as a permission pop-up or notification. The app doesn't appear to include special controls […]

InfoQ has opened enrollment for three five-week online certification cohorts starting in August, each led by a senior practitioner applying QCon talk frameworks to participants' own work: architecture with Luca Mezzalira, engineering leadership with Michelle Brush, and AI security and privacy with Katharine Jarmul. By Artenisa Chatziou

A new toolkit for attorneys in Massachusetts targets the technologies police use—and conceal—to build criminal cases, from facial recognition to AI-written police reports.

A helpful comment on my EXIF test suggested using a metadata scrubber. That is useful for ordinary still images, but a mobile upload contract must define every asset it sends. An iOS Live Photo can include both a photo resource and a paired video resource. The failure case is simple: the JPEG derivative has no GPS EXIF, while metadata or an original file associated with the paired video survives in the upload or retry path. Build the resource inventory first: let resources = PHAssetResource . assetResources ( for : asset ) for resource in resources { print ( resource . type , resource . originalFilename ) } Then make privacy assertions per output, not per UI selection: Artifact Required check still derivative no EXIF GPS/location fields paired video derivative no location metadata upload manifest only derived filenames retry queue no path to original resources temporary directory deleted after success or cancellation My lifecycle test would start an upload, force the app into the background after the still image is prepared, kill it while the paired video is processing, and relaunch. Recovery must either regenerate both safe derivatives or delete the incomplete pair. It must never mix a scrubbed still with an original video. Apple’s PHAssetResource API exposes the resources associated with a Photos asset. That enumeration should become evidence in the test: fail when an unexpected resource type is present rather than silently uploading it. Also verify what reaches the server. Device-side inspection alone misses multipart manifests, queued originals, and server-generated previews. Download the stored pair in a test environment and run the same metadata assertions again. A “remove location” button needs a precise scope. For Live Photos, the user reasonably expects it to cover the complete paired asset and every retry copy—not just the JPEG they can see.

Removing EXIF GPS protects one privacy boundary. It does not prove that an uploaded JPEG contains only a JPEG. A useful hostile fixture is a valid image followed by bytes for another format. Many decoders stop at JPEG’s end marker and display the picture successfully, while downstream scanners, content sniffers, or accidental downloads may interpret the trailing payload differently. Build a fixture set rather than trusting extensions: clean.jpg valid JPEG exif-gps.jpg valid JPEG with location jpeg-plus-zip.jpg JPEG followed by ZIP bytes jpeg-plus-html.jpg JPEG followed by HTML truncated.jpg missing end marker oversized-dimensions.jpg small file, dangerous decode cost My upload gate has independent layers: Store the original in a non-public quarantine location. Enforce byte-size and decoded-dimension limits. Decode with a maintained image library. Re-encode pixels into a new file, discarding metadata and trailing bytes. Verify the output’s signature, dimensions, and complete parse. Publish only the derived object under a server-generated name. A boundary check can detect bytes after the end marker, but re-encoding is the stronger transformation because it creates a new representation from decoded pixels. Keep the original inaccessible and delete it according to a tested lifecycle. assert ( outputSize <= limit ); assert ( decoded . width * decoded . height <= pixelBudget ); assert ( parseConsumesEntireFile ( output )); assert ( noLocationMetadata ( output )); The OWASP File Upload Cheat Sheet recommends defense in depth: allowlisted types, generated filenames, size limits, storage separation, and content validation. No single MIME header or metadata scrubber replaces that chain. The important privacy lesson is broader than EXIF: inspect every representation that survives the upload pipeline, and publish only a constrained derivative.

Syncthing keeps files synchronized across devices you control, making it one of the most practical tools for a self-hosted knowledge infrastructure that avoids cloud lock-in. Unlike cloud storage platforms, Syncthing uses a peer-to-peer model where each device holds its own copy of synced folders and exchanges changes directly with trusted peers. There is no central server that owns your data, no subscription account, and no vendor lock-in. The project is open-source and community-driven, with more details at syncthing.net . This architecture makes Syncthing especially useful for knowledge workers who manage markdown notes, research documents, PDFs, and project files across a desktop, laptop, home server, and possibly a phone. The tool is simple in concept but requires careful setup to avoid common pitfalls like treating sync as backup or syncing folders that should remain isolated. What Syncthing Is and Is Not Syncthing synchronizes files between two or more devices. Each device maintains its own copy of a folder, and changes propagate between trusted peers. Discovery and relay services may help devices find each other across networks, but the storage model remains local-first. The Syncthing documentation covers installation and configuration in detail. The calm but important opinion is this: Syncthing is excellent when treated as sync infrastructure. It becomes dangerous when treated as backup. It is not a cloud drive. It is not a complete backup system. It is not a collaboration suite. It is a private, peer-to-peer file synchronization tool. Why Syncthing Matters for Knowledge Management Knowledge management is not only about note-taking. It is also about where knowledge lives, how it moves, and whether it remains accessible over time — see the knowledge management guide for the broader picture of tools, methods, and self-hosted platforms this fits into. A useful personal or team knowledge system often contains: markdown notes PDFs and papers diagrams and screens

I’ve read the word “encrypted” on more apps than I can count, and most of the time it tells you almost nothing. Here’s what it really means, the way I’d explain it to a friend. Every app you use will tell you your data is encrypted. It’s on the login screen, the pricing page, the little padlock in the corner of the browser. And because it’s on everything, it’s stopped meaning much. I’ve spent more time on that one word than I’d care to admit, building a notes app where it actually has to be true, so here’s how I think about it. No maths. No padlock pictures. Underneath, encryption is an old and simple idea. You take a message, turn it into nonsense nobody can read, and make sure only the right person can turn it back. That’s the lot. Everything after that is detail about how good the nonsense is, and who’s allowed to undo it. The whole thing in one sentence Encryption takes something readable and mixes it into a mess that means nothing on its own. A matching key turns the mess back into the original. No key, and the mess stays a mess. The readable version is called plain-text. The mixed version is called cipher-text. That’s the entire vocabulary you need to know. Encryption turns plain-text into cipher-text, decryption is turning it back. A note is just text until you scramble it Say you’ve got a note on your phone, “dentist Thursday, 3pm”. Stored as it is, anyone who gets at the file reads it straight off. A thief with your unlocked phone. An app you handed too many permissions to. A company keeping a copy on its servers. All of them see “dentist Thursday, 3pm”. Encrypt it and that same note might sit on the disk as 9f2ac1b0e7..., a run of characters that means nothing. The appointment is still in there, in the sense that the right key brings it back, but on its own it tells a snoop nothing. Not the time, not the day, not that it was ever about a dentist. People reach for a padlock to explain this and I’ve never liked it. A padlock just stops you getting to the thi

A newly renewed, $25 million-per-year contract with a subsidiary of Thompson Reuters further expands the power of ICE under the Trump administration.