Dropbox status: access issues and outage reports

Problems in the last 24 hours

The graph below depicts the number of Dropbox reports received over the last 24 hours by time of day. When the number of reports exceeds the baseline, represented by the red line, an outage is determined.

Most Reported Problems

The following are the most recent problems reported by Dropbox users through our website.

• Errors (60%)
• Sign in (20%)
• Website Down (20%)

Live Outage Map

The most recent Dropbox outage reports came from the following cities:

City	Problem Type	Report Time
Nottingham	Errors	11 days ago
Guayaquil	Website Down	12 days ago
Flumet	Errors	22 days ago
Irapuato	Errors	24 days ago
Bournemouth	Sign in	3 months ago
Paramaribo	Errors	4 months ago

Full Outage Map

Community Discussion

Tips? Frustrations? Share them here. Useful comments include a description of the problem, city and postal code.

Beware of "support numbers" or "recovery" accounts that might be posted below. Make sure to report and downvote those comments. Avoid posting your personal information.

Dropbox Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Matt Uribe (@MattUribe) reported 8 minutes ago

  I can't get my @bot to login to @dropbox . Anyone else having that issue. It's kind of a big deal for what I am trying to set up with my team. No matter what, it says too many attempts when I try using chrome on my bots screen. The plugin has no place to authenticate. Also I wish I could sign an email login to each bot. Seems we can only link one for the team using outlook. I guess that's why it beta. :)

• 
  timelock (@hashtimelock) reported 12 minutes ago

  @BitPaine @Dropbox they got me. i noticed the "New Login from new location" email immediately and logged out of all the sessions. dont keep anything sensitive on there, thankfully

• 
  Christopher Bailey (@LexBaileyAI) reported 16 minutes ago

  @TetraspaceWest At Fitbit we hired a half dozen people from Jawbone who brought everything cleverly hidden in Dropbox. They got prosecuted. Decade later, companies kaput but Fable found it, processed it and now it’s intermixed in various *** repos and Huggingface. Is nVidia now in trouble?

• 
  Ed Giansante (@edugiansante) reported 16 minutes ago

  86% of small businesses still haven't fully integrated ai into their operations. which is funny, because the tools are already here. they're everywhere. there's probably one open in another browser tab right now, quietly waiting to change your life. Goldman Sachs surveyed small businesses and found that only 14% have fully integrated ai into their operations. i don't think the other 86% are anti-ai. they're busy. they're cautious. and they probably don't want to add “company-wide ai transformation” to the list of things they need to worry about before lunch. honestly, fair. @paulg said something recently that I keep coming back to: "If the world is going to get turned upside down, the safest place to be is in a small, fast-moving company that can easily change direction." small companies should be the ones moving fastest. but most are still waiting for someone else to go first. someone else to test the tool. someone else to write the playbook. someone else to promise that nothing will get weird. @clairevo nailed the real blocker: "the blocker is never tools or intelligence. human systems, human problems." i've spent 15 years watching this happen. At Dropbox. At Wix. At Zynga. Now at Persona. different tools. different eras. same pattern. a team finds a new tool. everyone gets excited. someone schedules a kickoff. three weeks later, everyone is back in the old spreadsheet. not because people are stupid. because changing how people work is uncomfortable. and buying software is much easier than changing behavior. i've seen the same thing with community-led growth. i used to pitch community to executives who had every tool and dashboard money could buy. they'd nod. they'd agree it worked. then they'd return to the comfortable world of automation, sequences, and dashboards that made everyone feel productive. last year, i ran 86 events as a team of one and built $3M in pipeline. the secret was not a magical growth hack. it was showing up. knowing the 15 people in the room by name. listening carefully. creating a space where people could actually trust each other. not exactly the kind of thing you can solve with a 47-step workflow. ai adoption and community adoption have the same problem. the tools work. the ideas work. the uncomfortable human part is where things usually slow down. sitting with your team and figuring out what should change. trying one workflow instead of redesigning the entire company overnight. leading people through something new instead of sending a Loom video and hoping everyone feels inspired. the 86% aren't waiting for better ai. they're waiting for change to feel a little less scary. so start small. pick one annoying workflow. try one new thing. make it 10% better. then do it again. the tools are here. the next step is still a very human conversation. and, unfortunately, probably a meeting.

• 
  Abhishek Singh (@0xlelouch_) reported 17 minutes ago

  System design question. How would you design Dropbox-style file sync with conflict handling? Constraints that make it interesting: 1) Multi-device edits while offline, then reconnect hours later 2) Large files (GBs), but common case is small diffs; do you chunk + hash + resumable upload? 3) At-least-once events from clients; duplicates and retries are normal 4) Need per-file causality: version vectors? server-assigned sequence? something else? 5) Conflicts: rename vs edit, delete vs edit, concurrent edits on same bytes; what gets auto-merged vs forked as conflicted copy? 6) Metadata vs content planes: directory tree ops must be atomic-ish, blobs can lag 7) End-to-end integrity: how do you detect corruption and avoid re-upload storms? 8) Fast convergence: target <5s to see changes on another device, but mobile battery + bandwidth are limited

• 
  abheet nigam (@MaginAbheet) reported 19 minutes ago

  Dropbox rejected billions of dollars of acquisition offers only to later realise down the line that they were building a feature not product. Which other companies show a similar pattern today?

• 
  Kyle Harrison (@kwharrison13) reported 20 minutes ago

  Maybe. Maybe you'd be fine without data centers. But let me ask you this. Do you use credit cards, debit cards, tap-to-pay, gas pumps, vending machines, parking meters, parking apps, ATMs, online banking, mobile banking, mobile check deposit, Zelle, Venmo, PayPal, Cash App, Apple Pay, Google Pay, splitting a dinner bill, autopay on your bills, payroll that isn't a paper check, direct deposit, digital 401(k), Robinhood, Coinbase, credit score checks, loan applications, mortgage applications, car loan approval at the dealership, insurance quotes, filing an insurance claim, e-filing your taxes, gift cards, store loyalty accounts, digital coupons, rebates, buy-now-pay-later, tipping on a screen, email, text messages, iMessage, WhatsApp, Signal, group chats, voicemail transcription, spam call blocking, FaceTime, Zoom, Google Meet, Discord, Slack, video calls with grandparents, phone number lookups, checking your data usage, paying your phone bill, two-factor codes, push approvals to log in, password managers that sync, "sign in with Google," resetting a forgotten password, digital IDs in your wallet app, gym check-in apps, apartment smart locks, hotel keys on your phone, office badge apps, patient portals, seeing your test results, booking a doctor's appointment, telehealth visits, prescription refill requests, the pharmacy knowing what you're on, insurance verification at the front desk, prior authorization, continuous glucose monitors, insulin pump apps, remote pacemaker checks, CPAP data reports, hearing aid apps, therapy apps, period trackers, fertility trackers, medical alert buttons for elderly parents, symptom checkers, finding an in-network doctor, the weather app, radar, hurricane warnings, tornado warnings, flood alerts, earthquake early warning on your phone, wildfire maps, smoke maps, air quality, pollen counts, Amber alerts, emergency alerts, road closure info, Google Maps, Apple Maps, Waze, live traffic, rerouting around a crash, transit apps, real-time bus and train arrivals, tapping your phone to ride the subway, Uber, Lyft, rental car reservations, Turo, bike share, scooter share, EV charging networks, paying for a charge, phone-as-car-key, remote start, finding your parked car, over-the-air car updates, in-car navigation, in-car voice assistants, stolen vehicle tracking, road trip planning, booking flights, checking in for a flight, mobile boarding passes, seat selection, flight status, rebooking after a cancellation, bag tracking, TSA PreCheck lookups, airport wifi, booking hotels, Airbnb, Vrbo, checking into a hotel, cruise bookings, theme park tickets, ride reservations, airline miles, hotel points, currency conversion, Amazon, all online shopping, order tracking, delivery notifications, returns and exchanges, price checks in-store, self-checkout, store apps, curbside pickup, Instacart, DoorDash, Uber Eats, ordering ahead at a restaurant, OpenTable, Resy, waitlist texts, QR code menus, tipping on delivery, subscription boxes, eBay, Etsy, Facebook Marketplace, Craigslist, Poshmark, StockX, Ticketmaster, StubHub, getting into a concert with a phone ticket, Alexa, Siri, Google Assistant, smart thermostats, video doorbells, security cameras, alarm monitoring, smart locks, smart lights, robot vacuums, garage door openers, baby monitors, pet cameras, automatic pet feeders, GPS pet collars, smart sprinklers, smart fridges, app-connected air fryers, cloud printing, printer ink subscriptions, routers you manage from an app, checking if you left the stove on, iCloud, Google Photos, every photo you've taken in ten years, Dropbox, Google Drive, OneDrive, shared albums, phone backups, setting up a new phone, notes apps, calendars, contact syncing, reminders, to-do apps, document scanning, e-signing a lease, Netflix, YouTube, Hulu, Disney+, Max, Prime Video, Twitch, cloud DVR, on-demand cable, Spotify, Apple Music, podcasts, audiobooks, Kindle books, library ebook borrowing, online multiplayer games, matchmaking, cloud saves, game downloads, game patches, single-player games that phone home for a license check, Steam, PlayStation Network, Xbox Live, Nintendo Online, Roblox, Minecraft servers, fantasy football, sports scores, sports betting apps, movie tickets, Google search, Wikipedia, ChatGPT, Claude, every other AI app, Instagram, TikTok, Facebook, X, Reddit, LinkedIn, Snapchat, Pinterest, dating apps, Yelp reviews, Google reviews, news sites, Substack newsletters, blogs, forums, checking if a business is open, looking up a phone number, recipes, translation apps, Duolingo, Google Docs, Sheets, Gmail, Outlook, Microsoft 365, Teams, Notion, Figma, Canva, shared calendars, scheduling links, VPNs into work, remote desktop, timeclock apps, shift scheduling apps, requesting time off, expense reports, job applications, LinkedIn recruiters, video interviews, Canvas, Blackboard, checking your kid's grades, school lunch accounts, attendance notifications, online homework, Khan Academy, Coursera, FAFSA, student loan portals, tutoring apps, Fitbit, Apple Watch health data, Strava, Peloton, sleep tracking, smart scales, calorie tracking, meditation apps, workout apps, DMV appointments, renewing your license online, paying a parking ticket, jury duty portals, checking your property tax bill, utility accounts, outage maps, paying rent through an app, HOA portals, storage unit access codes, wedding registries, baby registries, funeral arrangements, Ancestry, 23andMe results, church livestreams, volunteer signups, or GoFundMe? If you said yes to ANY of those then you do, in fact, NEED data centers.

• 
  Matt Mazur (@mhmazur) reported 24 minutes ago

  Day 2 of Claude autonomously shipping to my SaaS, including, for the first time, all night while I slept: The first day I had the hourly routine that kicked off this process end at 8pm so that if anything went awry, it could @ me in Slack and I'd quickly see the notification and dig in. The first day went smoothly, so I let it continue working overnight last night: every hour it would look for a small, safe change to make, ship it to ****, and monitor server logs and Sentry to make sure everything went well. A few other process improvements: - It now creates a PR for every change and links to it from its Slack summaries - Previously I only allowed it to make changes in 3 files max, but sometimes it identified the same issue spread across multiple locations, so it would have to spread that work over several hours; I bumped the limit to 8 files. - If I have uncommitted changes in main, it no longer blocks Claude's work; it moves them to a separate branch - Added a mandatory security review before pushing to ****. For these simple changes it's not that necessary, but it will be important for larger projects in the future. Specifically, I told it to run the default /security-review skill and if it flagged anything, to halt everything and wait for me to review. - Ran into a slight issue one hour where it ran that skill, the security review passed, and then it did nothing. I asked Claude to investigate, and it discovered it had run the skill in its main context window, which confused it into thinking its only job was the security review. It changed the process so the security review happens in a subagent, keeping the context window clean, which fixed things. - I asked it to maintain a ledger of things it needs me to do and to ping me every 24 hours if I haven't knocked them out. More and more, the agent is giving me things to do. - I told it to adopt the tone of TARS from Interstellar in its Slack updates going forward, cause why not. Here's a list of improvements it made on day 2: 1. Return 404s for bad case-study URLs 2. Extended the 404 fix site-wide 3. Removed stray code leaking into HTML 4. Fixed broken citation example in docs 5. Fixed wrong URL in sharing docs 6. Corrected false free-plan claim 7. Removed duplicate HTML attributes 8. Fixed dead links in embed docs 9. Fixed garbled copy on two pages 10. Pointed "paid plans" link at pricing 11. Added missing alt text to logo 12. Corrected a misleading code comment 13. Upgraded insecure links to HTTPS 14. Replaced dead testimonial link 15. Fixed broken example in Dropbox docs 16. Fixed awkward grammar on comparison page 17. Fixed reversed table of contents 18. Fixed missing Show More button 19. Matched nav label to its section 20. Corrected outdated visibility docs claim 21. Removed obsolete step from setup docs These can be categorized as: support-doc accuracy fixes (7), functional bug fixes (4), broken or insecure links (3), copy improvements (3), invalid markup (2), accessibility (1), and code hygiene (1). Excited to expand the scope of things I allow it to work on, but am going to wait until next week to ensure the current process is robust.

• 
  Hago Community (@HAGOCommunity) reported 25 minutes ago

  AI Internal Search Agent: An Intelligent Agent for Searching Company Information Many companies struggle with information being scattered across multiple systems and files. Policies may be stored in Google Drive, documents in SharePoint, conversations in Slack or Microsoft Teams, customer data in a CRM, while internal procedures may be stored in Notion or Confluence. When an employee needs specific information, they may have to search in several places, ask a colleague, contact a manager, or open multiple files before finding the correct answer. This is where an AI Internal Search Agent can help. This agent is an AI-powered system that can search across different company data sources, understand an employee’s question, and provide a direct answer based on the internal information available to that employee. How Does the Agent Work? The agent can be connected to the systems and platforms used by the company, such as: Google Drive SharePoint Notion Confluence Slack Microsoft Teams CRM systems Internal databases PDF files Internal documents Company policies Standard operating procedures Employees can then ask questions in natural language instead of manually searching through multiple systems. For example: “What is the company’s travel expense reimbursement policy?” Or: “Where can I find the latest version of this customer’s contract?” Or: “What are the steps for adding a new customer to the system?” Or: “Who is responsible for this account, and what was the latest update?” The agent searches the sources the employee is authorized to access and provides the most relevant answer. The Problem It Solves The main problem is usually not that the company lacks information. The problem is that employees do not always know where that information is located. An employee may spend time: Searching through multiple folders. Opening several documents. Reading old conversations. Asking coworkers where information is stored. Trying to identify the latest version of a document. Searching across different business systems. This creates unnecessary delays and wastes employee time. Instead, the employee can simply ask the AI agent and receive an answer within seconds. A Practical Example Imagine an employee wants to know the process for purchasing new software for their department. In a traditional workflow, the employee may search through emails, ask their manager, and browse company folders until they find the correct policy. With the AI agent, the employee could simply ask: “What is the process for purchasing software that costs more than $5,000?” The agent could search the company’s internal policies and respond: “Purchases above $5,000 require approval from the department manager first. The request must then be submitted to Procurement and approved by the Finance department.” The agent can also provide a link or reference to the original policy document used to generate the answer. Searching Customer Information The agent can also be used to search customer-related data. For example, a sales employee could ask: “What was the latest agreement with customer ABC?” The agent could search the CRM, internal notes, documents, and customer-related conversations before providing a summary. For example: “The latest meeting with the customer was on August 12. The customer is interested in the Enterprise plan and requested a revised proposal before the end of the month.” This allows the employee to understand the current status of the account without manually searching through a long history of notes. Searching HR Policies Employees can also use the agent to get answers about internal HR policies. For example: “How many annual vacation days do employees receive?” “What is the remote work policy?” “How do I request time off?” “What is the process for business travel?” Instead of sending these questions repeatedly to the HR department, employees can receive answers directly from the AI agent based on official company policies. Supporting New Employees One of the most useful applications of an AI Internal Search Agent is employee onboarding. New employees often have many questions, such as: “How do I request a laptop?” “How do I access the internal system?” “Where are the team files located?” “Who approves expenses?” “How do I submit an IT support request?” The AI agent can act as an internal assistant throughout the onboarding process and provide immediate answers to these questions. Respecting Employee Access Permissions One of the most important features of the agent is permission management. Not every employee should have access to every piece of company information. For example, some documents may contain sensitive information related to payroll, contracts, human resources, finance, or executive management. The agent should therefore respect each employee’s existing access permissions. If an employee does not have permission to access a specific document, the AI agent should not use that document when generating an answer. This allows the company to provide intelligent internal search while maintaining appropriate data access controls. Showing the Source of the Answer The agent should not only provide an answer. It should also show the source of the information whenever possible. For example: “According to the company travel policy updated on May 3…” The employee can then open the original document and verify the information. This helps reduce the risk of employees relying on outdated or incorrect information. Detecting Outdated or Conflicting Information The agent can also be designed to identify conflicting information. For example, it may find two different documents containing different instructions about the same company policy. Instead of selecting one version randomly, the agent could alert the employee or administrator: “There are two documents containing different instructions regarding the remote work policy. The most recent document was updated in June.” This can also help companies improve the quality of their internal knowledge management. Moving From Search to Action The system can be developed to do more than simply search and answer questions. For example, an employee may ask: “How do I add a new customer?” The agent can first explain the required steps. The employee can then say: “Start the process.” The agent could create a checklist, create a new record in the CRM, send a request for the required documents, and notify the employee about the remaining steps. At this point, the system moves from being an AI Search Agent to becoming an AI Operations Agent. Example Inside a Sales Team A sales representative could ask: “What are the most important things I should know about this customer before the meeting?” The agent could search the CRM, previous notes, proposals, and communications before creating a summary that includes: Company size. Products the customer is interested in. Date of the latest meeting. Previous objections. Estimated deal value. Recommended next steps. This allows the sales representative to prepare for the meeting without spending significant time searching for information. Example Inside Customer Support A customer support employee could ask: “How was this problem solved in the past?” The agent could search previous support tickets and the company knowledge base to find similar cases and show the solutions that were previously used. This can reduce ticket resolution time and help new support employees solve customer problems more efficiently. Data Sources the Agent Can Connect To The agent can potentially connect to many different systems, including: Google Drive Microsoft SharePoint Slack Microsoft Teams Notion Confluence Salesforce HubSpot Dropbox OneDrive ERP Systems CRM Systems Internal Databases PDF Documents Excel Files Company Policies Employee Handbooks Customer Records The more organized and up-to-date the company’s information is, the more useful and reliable the agent becomes. Benefits for the Company An AI Internal Search Agent can help a company: Reduce the amount of time employees spend searching for information. Reduce repetitive questions between employees. Make policies and procedures easier to access. Help new employees become productive faster. Improve knowledge sharing across departments. Reduce dependence on individual employees who know where everything is stored. Make customer and project information easier to access. Reduce the time required to find the correct documents. Improve the speed of decision-making. How Can the Company Measure the Agent’s Value? The company can measure the value of the system by calculating how much time employees previously spent searching for information. For example, if 200 employees each spend 20 minutes per day searching for files or asking coworkers for information, that represents more than 66 hours of employee time every day across the company. If the agent can significantly reduce that time, the financial value of the system becomes easier to measure. The company can also track: Average time required to find information. Number of questions answered by the agent. Number of manual searches avoided. Reduction in repetitive questions sent to HR and IT. Customer support resolution time. Time required to prepare employees for meetings. What the Final Agent Workflow Could Look Like The employee asks a question ↓ The agent understands the request ↓ It identifies the relevant data sources ↓ It checks the employee’s access permissions ↓ It searches the company’s internal data ↓ It selects the most relevant information ↓ It provides a concise answer ↓ It shows the source of the information ↓ If authorized, it can also perform the requested action In this way, an AI Internal Search Agent becomes a private intelligent search engine for the company, allowing employees to access internal knowledge quickly instead of wasting time searching across files, systems, and conversations.

• 
  Brandon (@BJohnsonxAR) reported 26 minutes ago

  @DropboxSupport I’m having issues logging in. When I try to login it’s making me sign up when I already have a paid account. This is happening on both the app and my browser. @Dropbox

• 
  Rei (@ReiHerrera) reported 29 minutes ago

  @owldreig @porterrobinson @madeon The problem with them both is they love gatekeeping the rare song behind a bad quality sounding medium so you cannot use it for clean for dj sets. For example Celine,worlds live,shepherdess,etc. at least we had hollowheart on wav and shepherdess wav was on porter’s Dropbox leak🫩

• 
  Abhi • AMZBoosted.com (@AbhiChauddhari) reported 30 minutes ago

  Everyone downloads Seller Central reports manually. Every. Single. Day. The problem isn’t downloading reports. It’s remembering to do it before you need the data. AMZBoosted schedules report downloads automatically and sends them wherever you want. Google Sheets. Dropbox. Telegram.

• 
  🪬M🪬 (@_marokiya) reported 36 minutes ago

  Apple be bullshitting about this iCloud storage. How am I out of space when you're supposed to be offloading everything into the 2TB storage I'm paying for? Nothing should be on my actual laptop unless I choose to download it directly. DropBox somehow never has this issue.

• 
  Scarlett Bama 🇺🇸🅰️🐘🏈🏖️✝️ (@scarlettbama) reported 39 minutes ago

  @DropboxSupport Fri AM: Dropbox down? Rare if so! Will not allow PDF upload to existing folder. Upload 50x per month. Started after most recent IOS update. Using iPhone. No MacBook access right now. Pls don't sent to Community Forum.

• 
  Ivan Kirigin (@ikirigin) reported 41 minutes ago

  @sethbannon I think I’d agree with the sentiment, and not the assessment. We’re not close to too many startups building weapons. The company with “drone” in the name that has the navy and other defense units as obvious potential customers doesn’t make a trend. If I had to put my finger on what has changed, Palantir and Anduril unlocked the latent interest in the space that matches the historically close connection between Silicon Valley and defense. It was just that the Overton window was locked down by people afraid to talk about what defense really means, and in many cases aren’t even Americans with the opinions. I say this as someone who worked at iRobot in defense before my time in YC, Facebook, Dropbox, and Lyft. Each had lots of people comfortable assuming others will think about and solve the ***** problems.

• 
  Lowkea (@lowkea713) reported 42 minutes ago

  Dropbox if you could please fix your self I have an uncomfortable amount of music in your app and now I can’t log in

• 
  Bruce Perry (@bhrperry) reported 48 minutes ago

  @Levi_Borovychok Thumb drives can be cheap, but the cheap ones are often slow. It's worth thinking about where cloud storage is done. I believe Dropbox will let you store your files in the EU.

• 
  Lalit Dhalia (@lalit_dhalia) reported 52 minutes ago

  @GrokInsider U are acting exactly like that hackernews comment who was shitting on Dropbox launch, "u can setup your own ftp server". Same energy guy. If u have to ask this, u are NOT the audience bro. Come on.

• 
  grey (@w3b3grey) reported 52 minutes ago

  If you are like me and you wondering, where my IDENTITY PEM FILE is on @flop_labs , I gat you; here is how to find it identity.pem is already saved automatically; the init command writes it to your project folder the moment you run it (typically right in technocore-did-starter/identity.pem). You don't need to do anything extra for it to exist. What "saving" really means here is backing it up safely, since if this file is lost, your DID is unrecoverable (the guide's troubleshooting table says exactly that: "there is no central DID recovery service"). 1. Confirm it's there ls -la ~/technocore-did-starter/identity.pem 2. Back it up to a second location — copy it somewhere other than the working folder, e.g. an external encrypted drive or a password manager that supports file attachments (1Password, Bitwarden both do this): cp ~/technocore-did-starter/identity.pem ~/Desktop/identity-backup.pem Then move that copy off your main disk (external drive, encrypted USB, etc.) rather than leaving a second copy sitting in ~/Desktop long-term. 3. Lock down file permissions so only your user account can read it: chmod 600 ~/technocore-did-starter/identity.pem 4. What NOT to do with it Don't upload it to GitHub, Google Drive, iCloud Drive, Dropbox, or any synced/cloud folder in plaintext. Don't email it to yourself or paste it into a chat (including this one). Don't commit it to *** , the guide's Path B steps even have you run *** ls-files "*.pem" "*.key" before committing specifically to catch this. 5. Remember the passphrase separately from the file The .pem is encrypted, but it's useless without the passphrase you set during init. Store that passphrase somewhere separate from the .pem backup itself (a password manager entry, not a text file sitting next to the key), so a single leaked backup doesn't hand over both pieces at once. NOTE - If you lose either the file or the passphrase, per the guide, there's no recovery; you'd have to run init again and get a brand new DID.

• 
  Rituraj (@RituWithAI) reported 54 minutes ago

  🚨 Someone built a tool that checks if your email is registered on 120+ sites — without the sites ever knowing someone checked. No notifications sent. No login attempts logged. No alerts triggered. Silent. Invisible. Complete. It's called Holehe. 16,800 GitHub stars. And the technique behind it is what makes it different from every other email OSINT tool. Here's how most email checkers work — and why they fail. Standard approach: try to log in with the email and a fake password. If the error says "wrong password" — the account exists. If it says "account not found" — it doesn't. Problem: every login attempt gets logged. Every failed attempt triggers security alerts on accounts with 2FA. Some platforms lock accounts after repeated failed attempts. The target knows someone was checking. Holehe never attempts a login. Instead it uses the "forgot password" flow — the password reset mechanism that every platform exposes publicly. When you enter an email on a forgot password page, the platform has to check whether that email exists in its database. It tells you: "we sent a reset link" or "no account found." Holehe reads that response. Gets the answer. Never touches the login flow. Never triggers a security alert. Never logs an access attempt against the account. The platform confirms whether the email exists. The account owner never finds out anyone asked. Here's what 120+ platforms looks like in practice. Social media: Twitter, Instagram, Facebook, TikTok, Pinterest, Tumblr, Reddit. Professional: LinkedIn, GitHub, Freelancer, Fiverr. Dating: Tinder, Bumble, OkCupid, Badoo, Happn. Entertainment: Spotify, Netflix, Twitch, Steam, Epic Games, Deezer. Shopping: Amazon, eBay, Etsy, Zalando, AliExpress. Services: Airbnb, Uber, PayPal, Dropbox, Adobe. And 90+ more. Every registration checked silently. Here's the use case that makes people share this. Run your own email address. See every platform that comes back positive. Then run an email address you gave to a company that claimed they'd never share it. See if it's registered on data broker sites and marketing platforms you never signed up for. See where your email has been sold or leaked to. Here's what investigators actually use it for. Journalists verifying whether a source's claimed identity matches their digital footprint. Security researchers auditing their own exposure before a public disclosure. HR teams verifying whether candidate profiles match claimed backgrounds. And the obvious: anyone who needs to know whether a specific email address belongs to a real active person — without alerting that person. Here's the wildest part. It runs async — all 120+ platforms checked simultaneously. Results in seconds. And it exports clean JSON or CSV for integration into larger OSINT pipelines. Pair it with Blackbird (which takes the confirmed email and finds linked profiles), Sherlock (which takes usernames found in those profiles and searches 400+ platforms), and Maigret (which builds the full dossier) — and you have a complete four-tool OSINT pipeline from a single email address. One command to instal. Run it on your own email first. 16.8K GitHub stars. 1.7K forks. MIT License. 100% Open Source. GitHub link in the comments 👇

• 
  John B. Holbein (@JohnHolbein1) reported 54 minutes ago

  Replication has become much easier in the era of generative AI. I'm not the first person to say that. However, I've seen fewer people acknowledge a specific aspect of this lowered cost for replicating scientific work: Generative AI will very soon allow us to assess the robustness of individual scholars' full bodies of work. Soon, we will be to compute measures of which scholars do robust science, and which do not. What's wild is that we may be able to almost do that already. Let me show you what I mean. In June, I gave Claude a pretty basic prompt. It read: "I have a big task for you. I want you to start a folder. Call it Acemoglu Replications. Then, go find as many replication archives for Daron Acemoglu as you can. Keep a spreadsheet of the ones you can find and those you can't. Then, start a replication/reproduction effort on those articles. People have in the past criticized the research designs and general robustness of his individual papers. I want to know how strong his body of work is as a whole. Don't come in with any prior beliefs; be dispassionate." I let Claude run overnight while I slept. When I came back in the morning, 29 of Acemoglu's replication archives were fully loaded in my Dropbox. All the code reproducing the paper's results had run. And there was a first draft of a paper assessing the robustness of Acemoglu's full body of empirical work. I'll admit, the first draft of the paper wasn't great. But with 15 short follow up messages--which took me about an hour to write--I was able to prompt engineer a paper-length examination of Acemoglu's work. I've attached the screen shot of the abstract below. I think this reassessment of Acemoglu's work is certainly not done. I'm posting the abstract as a proof of concept, rather than a definitive answer. I'm not posting the full paper yet because I think it still needs more work. Ultimately, I paused this project for three reasons. 1.) Limited time/topical expertise: Most of Acemoglu's work is outside of my area of topical expertise. So, I have limited time to work on it. What this type of a project really needs is someone who has the time and the know-how to dig into each of the replication's individually to make sure they are doing the right things. I think the ideal approach combines the breadth that LLMs afford and the depth of attention/expertise that humans can give. 2.) Questions about the value of the "assess one scholar at a time" enterprise: I totally get that having a database of scholar-level robustness metrics would be very valuable in theory. But what I don't know is whether this approach is truly valuable. Moreover, doing so would come with distinct challenges. a.) Many journals have very restrictive space constraints. A body of work approach would, of necessity, be very long. b.) Collecting replication archives is harder for some types of scholars (those who post them all on their websites) than others (those who don't). c.) We'd have to think hard about questions like: what scholar-specific robustness metrics would be best? And: how would we deal with the fact that prolific authors' robustness metrics would be estimated much more precisely than less prolific scholars? Additionally, I'm just not sure that "taking on" one scholar at a time has enough scientific merit to pursue. If I measured how robust an individual scholars' work is, I'd ideally want to know where that metric stands vis-a-vis the rest of scholars in that field/area. To do that, we'd ideally want the population of these scholars or, at minimum, a random sample. Concretely, if Acemoglu has, say, 78% of published headline results reproducible under some standardized protocol, is that excellent, mediocre, or terrible? To answer that, you need a reference distribution. That makes a random or otherwise well-defined sample of scholars much more attractive than selecting prominent individuals one by one. (I'll acknowledge that I may just be wrong on #2. Arguing against myself, I do agree that human-driven reproduction/replication work rarely assesses full/representative slices of a field. Instead of assessing one scholar at a time, we assess one paper at a time. Field-wide detective work is becoming more common, but my sense is that it's still the exception rather than the rule.) 3.) Cost/benefit considerations and replication norms: we have very weakly formed norms around reproduction/replication generally speaking. We have basically no developed norms around replicating individual authors one at a time. What this means is that the people who would lead a scholar-by-scholar replication effort will, likely, bear a heavy cost and, potentially, reap limited benefits. On the costs side, focusing on scholars' total bodies of work risks making the replicators look petty, vindictive, and antisocial. Enough of the scientific field is hostile towards replications of individual papers. Imagine what will happen if/when a scholar submits a scholar-specific "take down" of a full body of work. My sense is that it's common enough for scholars having their work replicated to be asked to be a reviewer for those manuscripts. I've seen very hostile responses when one paper is at issue. Imagine what type of reviewer Acemoglu would be for a paper that took on his entire body of empirical work! Even if Acemoglu weren't a reviewer, prolific authors tend to have wide coauthor/friend networks. The rally-around-my-friend dynamic we often see would certainly work against this type of paper being published. Even a completely neutral analysis acquires an accusatory character simply because the sampling unit is a named person. And that creates an unfortunate problem of its own: readers may interpret the choice of scholar as evidence that the investigators expected to find something. On the benefits side, replicating individual scholars' total body of work may offer limited payoffs. What journals would accept this type of scholar-specific replication? I'm not sure the top ones would. Conclusion: Generative AI has enormous potential in assessing and, ultimately, enhancing the robustness of scientific research. Instead of asking questions like, “does this famous individual paper replicate?”, we can begin asking questions like: -“What proportion of published empirical findings in [field X] survive a common robustness protocol?” -“How much of the variation in replicability is attributable to papers, authors, journals, methods, or subfields?” -“Are scholars persistently more or less robust across their work?” -“Can we predict which findings will prove fragile?” I may just be wrong on what I think about a one-at-a-time full body examination of scientific research. If I am, please let me know! I am also happy to chat one-on-one with anyone who is curious to learn more about the early-stage Acemoglu-specific replication project.

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  Robert J Abalos (@robertjabalos) reported 56 minutes ago

  Want Your Startup to Get VC Funded? You Must Meet All Six of These Requirements Venture capitalists at the seed stage bet on potential more than perfection, yet they demand specific proof points before writing a check. After reviewing hundreds of deals and data from PitchBook, Crunchbase, and leading funds, six absolute requirements stand out. Miss any and the odds of funding drop sharply. First, an exceptional founding team. Team quality remains the single highest weighted factor before product market fit solidifies. VCs look for domain expertise, prior execution, complementary skills, and coachability. Research shows roughly one in four two founder teams loses a co founder by year four, so investors scrutinize resilience and equity alignment. Companies with strong teams raise at higher valuations even with lighter metrics because execution can fix product or market gaps. Second, a large and expanding market. Seed investors require a total addressable market of at least one billion dollars, ideally several billion, with a clear path to one hundred million in annual revenue. Serviceable addressable market should support venture scale outcomes. Markets growing above twenty percent annually command premiums. Small markets cap upside and rarely produce the fund returning exits VCs need. Third, early traction proving customers care. For SaaS this often means ten thousand to one hundred thousand in monthly recurring revenue or three hundred thousand plus in annual recurring revenue. Pre revenue startups need strong engagement such as daily active users to monthly active users ratios above twenty percent, organic waitlists, or letters of intent from unaffiliated customers. Dropbox famously used a demo video that drove seventy five thousand sign ups overnight, unlocking its Sequoia seed. Slack showed early retention that later became legendary. Fourth, rapid and consistent growth. Seed VCs seek fifteen to twenty percent or higher month over month revenue or user growth sustained over multiple months. Absolute numbers matter less than trajectory. Startups posting twenty percent plus monthly recurring revenue growth have seen close rates near sixty five percent in analyzed pitch data. Flat or decelerating growth signals risk. Fifth, early unit economics and retention signals. Even at seed, investors examine lifetime value to customer acquisition cost ratios above two to one, ideally three to one, net revenue retention near or above one hundred percent, and cohort retention that flattens rather than collapses. Gross retention above eighty to ninety percent is a positive signal. These metrics prove the product delivers lasting value and that growth will not require endless capital. Sixth, capital efficiency and clear runway. Burn multiple and months of runway matter. Investors prefer teams that can stretch capital to eighteen months or more while showing improving efficiency. Median U.S. seed rounds now sit near three to four million dollars, yet graduation to Series A has tightened to roughly twenty to fifty percent depending on cohort and sector. Lean teams of four to eight people that still deliver results stand out. Data confirms the stakes. Only a minority of seed companies reach Series A, and failure rates near forty percent are common. Yet the power law rewards those that clear these bars. Airbnb, Stripe, and early Slack all combined strong teams, massive markets, and measurable early traction. Founders who quantify these six elements with real numbers, not projections, dramatically improve their chances of securing seed capital.

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  David Silva Smith (@DavidSilvaSmith) reported 57 minutes ago

  Got dropbox, ickoud, google drive working last night. Looking at @immichapp for photos…. Home server… hosted server…. Hmmmm

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  Mitzi Hellmer (@Cathy44365595) reported 58 minutes ago

  @marcorandazza @DietCoke_Esq The claim is that the “CSAM” of Miller’s daughter was released the first time he published the Dropbox folder. Considering that Miller disabled that folder and lied about an outage on Dropbox shortly after publishing it, I think it’s entirely plausible that he may have inadvertently released a **** photo of her ******** as claimed. Who knows…probably her being cute in the bathtub. It honestly seems perfectly plausible.

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  Denver Rayburn (@DenverRayburn) reported 60 minutes ago

  Where do the find he people the write these articles?? This will go down like the rsync vs Dropbox comment on hacker news.

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  Llama (@thellama451) reported 60 minutes ago

  I tracked down these messages in @MaxMillerOH’s Dropbox files. They show the parents getting along with no major conflicts beforehand. If Miller said he was going to kill his ex-wife in front of child (likely), it shows a talent for masking rage and hostility.

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  M.Ellis (@MEllisPhotograp) reported 1 hour ago

  @DropboxSupport any know issues with desktop and web site of yours lately ? my account has been very slow and annoying today YES I TRUST MY COMPUTER so instead you ask me 4 times before i just log off and give up...

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  Polsia (@polsia) reported 1 hour ago

  Small landlords don't have a compliance problem, they have a Dropbox problem. Rental license, insurance renewal, lead-paint disclosure, inspection cert - all buried until code enforcement shows up.

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  Sridhar Katakam (@srikat) reported 1 hour ago

  Tips to new @OmarchyLinux users from a new Omarchy user 1. If you are coming from a Mac and have installed Omarchy on a Windows machine: Your keyboard most likely has start button and then the Alt button. Swap these so Super key becomes command where the left thumb usually rests. I asked Claude Code to do this for me. 2. If your mouse has a scrollwheel: Super + mousewheel scroll up and down switches desktop spaces. This is besides the usual Super + <number> and Super + Tab / Super + Shift + Tab to switch spaces. In addition to these, I have AI set up Ctrl + Alt + arrow. 3. Missing Alfred/Raycast? Install omacast. 4. If your laptop is connected to an external monitor with bluetooth mouse and keyboard and you find that the computer is not waking up (after you walk away for a while) when you press any key or move the mouse, ask AI to fix this for you. 5. The default font size of text in Claude Code is 12px which is small for my aging eyes. Ask AI to change it to 16px. 6. Todoist does not have a native app for Linux and so if you miss its Quick Add feature, ask AI to set this up. It added the functionality and assigned Super + Q to it. Later, I came to know there's a community plugin for it. But I am happy with what Claude did. 7. If you use Dropbox, chances are, the total available space in your account is not accurate because it is hardcoded in Omarchy at this time. Ask AI to fix this for you. 8. If/when the fan in your computer is spinning fast and is noisy, ask AI to find out the reason and fix. In my case, it turned out to be Performance profile in the Lenovo laptop. Claude changed it to Balanced and now it's all fine. 9. Get familiar with keyboard shortcuts.

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  The Redeemed Artist (@Peace_Grenade81) reported 1 hour ago

  I know I'm just screaming into the void. And there's probably less than like one or 2% of users that actually use this function. But I'm going to do it anyway. For the longest time the X app beta was absolute garbage on Android. It had serious stability problems, I couldn't use voice to text properly, and I couldn't access my memes from Dropbox, my cloud provider. The most recent change fixed all of the other problems except for my Dropbox integration. At first, I blamed X for this but I have since come to learn that the real culprit is Google. If you go into your app section and look for cloud providers they give you all sorts of choices so long as you like the choice that is Google's. Theoretically, other providers should be in here like Box or Dropbox. But Google has been playing footsie making rules about cloud provider integration and not actually approving anyone else. Google has become Microsoft. Google will tell you what cloud provider to use and it will conveniently be their own. Google will continue to upgrade their operating system closing off any other provider options or applications they simply disagree with for any reason at all. Meanwhile what this means for me is that I can't insert any memes or videos because they are all stored on Dropbox. Yeah, yeah, yeah I could go into Dropbox and then click on a photo and then share it to X and then make a post out of it. But what I can't do is respond to a post and insert a picture or a video directly through the X app. Don't know when this gets fixed, if ever. But I think it's time for Google to be investigated for monopolistic practices. I realize that this doesn't affect many people, but if you think they aren't coming for your various conveniences, I'm pretty certain that that's going to be proven wrong. Since I can't post a meme but only a local photo, here's an unrelated picture of a quilt we bought at auction. 🙄