GitHub status: access issues and outage reports

Problems in the last 24 hours

The graph below depicts the number of GitHub 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 GitHub users through our website.

• Website Down (72%)
• Sign in (16%)
• Errors (13%)

Live Outage Map

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

City	Problem Type	Report Time
Tel Aviv	Website Down	3 days ago
Rive-de-Gier	Website Down	3 days ago
Itapema	Website Down	21 days ago
Tlalpan	Sign in	27 days ago
Quilmes	Website Down	27 days ago
Bengaluru	Website Down	29 days ago

Full Outage Map

Community Discussion

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  a *ੈ✩‧₊˚ (@blehreturns) reported 8 minutes ago

  FINALLY SUBMITTED THE LAST OF MY PROJECTS please please please make dua my prof accepts it (it’s 1638363836 days late) and i get a good grade PLEASEEEEE now i just have to fix my github and resume and get myself a job lol but anyways one step at a time wooo

• 
  itsjustcornbro (@itsjustcornbro) reported 8 minutes ago

  @RafaelNegronX @ThePrimeagen github goes down whenever i shallow clone

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  Mark Ajzenstadt (@mardehaym) reported 9 minutes ago

  Claude Fable 5 costs twice as much per token as Opus. Some early users report lower total bills. Both claims hold up. Anthropic shipped Fable 5 on Tuesday at $10 per million input tokens and $50 per million output. Engineering forums split within hours. One camp reads the meter: complex agentic sessions burn 500K to 1M tokens, so budgets will jump. The other camp reads the output. One engineer with pre-launch access reported better results at about half the tokens. Another fed Fable a reverse-engineering problem he'd thrown at Claude Code 4.8 and Codex 5.5 before without success. Fable returned the answer in 30 minutes. Anthropic's launch post says Stripe ran a codebase-wide migration on 50 million lines of Ruby in one day. The hand-coded estimate: a full team, two-plus months. Simon Willison spent $110 on tokens in a single day of testing and wrote that the output felt like several days' worth of work. Both camps are right. They measure different units. Token price is a vendor metric. Cost per merged PR is a business metric. Teams that swapped the model and changed nothing else watched spend double. Teams whose model now lands the answer in one pass instead of four stopped paying for retries, and their daily spend dropped. Which group you land in depends on what you measure. Most engineering orgs can't run that comparison. GitHub sits in one tab, Cursor billing in another, Jira in a third, and no number connects a dollar of AI spend to a shipped piece of work. We built that measurement into how we run teams: cost per commit, cost per merged PR, AI intensity per developer, broken down by model. A new model gets one week in production. Then the dashboard gives the verdict. Fable 5 enters our stack this week. By next Friday we'll know what it did to our cost per merged PR. If the number disappoints, we cut it. You can argue about token prices. We'd rather read the meter.

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  Joe Blau (@joeblau) reported 10 minutes ago

  Fable 5 has created so many GitHub issues that my new bottleneck is my CI... I wanted to create my own runners, but guess what's all sold out...

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  Chris (@chrisjainsley) reported 13 minutes ago

  @coder_blvck @github Same all my actions are stuck. We're also having issues posting messages to azure event grid. Not sure if they are related.

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  Marc Nash (@mordynashman) reported 14 minutes ago

  @github the word frustration has taken on a new meaning. I lost my phone which had 2FA authentication configured on it. I don't have the recovery code and I am having issues accessing my account. I need help but all documentation points me to log in. CAN YOU PLEASE HELP ME!!!!!

• 
  Colin LeClercq (@ThePhilnado) reported 17 minutes ago

  This is exactly why you lock down what your agents can touch. Swap classic GitHub tokens for fine-grained ones, scope them per org, and have your agents audit the dependencies they pull in. Microsoft just got burned twice in weeks on this. Link is in the replies.

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  ecomchigga (@ecomchigga) reported 21 minutes ago

  there's a free automation built into X that sends your product link to anyone who comments a specific word on your tweet. the DM fires without you touching your phone. your gumroad notifications go off while you sleep. it's called auto-DM and when you connect it to a $39 PDF and a free telegram group, it turns every tweet into a passive sales system. faceless accounts with 3,000 followers are quietly clearing $3-8K/month with this exact setup and most people on the platform have never heard of it. here is every single piece of how it works. the infrastructure: 4 tools. total cost under $50/month. 2 of them are free. X account (free): faceless. no face, no name, no personal brand. just a niche and a profile picture. the account is the distribution channel. every tweet is a storefront window. TweetHunter ($49/month): scheduling tool. you write tweets, queue them, TweetHunter posts at your set times. the critical feature is auto-DM. when someone comments your keyword, TweetHunter silently sends them a DM with your link. you never see it happen. the person comments, gets the link in seconds, clicks through, enters your funnel. all while you're at the gym or eating dinner. Telegram (free): this is your community. the free guide lives here. people join, see other members asking questions and posting wins, and start trusting you before they've ever spoken to you. a cold gumroad page converts at 1-2%. a telegram community where people see real proof converts at 4-8%. Gumroad (free until first sale, then 10% fee): product hosting. one page. one product. one price. gumroad handles payment, delivery, receipts. you set it up once and never think about it again. monthly operating cost: X: $0 TweetHunter: $49 Telegram: $0 Gumroad: $0 + 10% per sale entire business infrastructure for less than a gym membership. the product: one PDF between 9 and 40 pages answering one specific question your audience keeps asking. not a course. not 47 modules. not a membership site. one document solving one problem. price between $27 and $67. the pricing psychology based on real sales under $19: buyers assume it's trash before opening it. the price is the review. $27-$44: impulse range. low enough to buy without asking their partner, high enough to feel legitimate. most first-time sellers should start here. $44-$67: credibility range. works after 50+ sales when trust already exists. above $67: needs testimonials, proof screenshots, and months of authority. for your first product: $34-$44. this is where the math works and the friction is lowest. time to create the product: one sitting. a 14-page PDF written after dinner answering a question your audience has asked you in 20 different ways will outperform a $2,000 course that took 3 months to produce. every time. the content system: 3 tweets per day. never more. the X algorithm runs a penalty called the AuthorDiversityScorer that exponentially cuts reach for each additional post from the same author in someone's feed. your first tweet scores at 100%. your second at roughly 50%. your third at 33%. your fourth at 20%. posting 5 times a day doesn't give you more reach. it gives you less. space posts 4-6 hours apart. this resets the session decay between each one. of the 3 daily tweets: tweet 1 (morning): pure value. teach something, reveal a mechanism, share a result. no pitch. this builds authority. tweet 2 (afternoon): pure value. different angle. still no pitch. tweet 3 (evening): CTA tweet. this is the one that makes money. the CTA mechanic: the first 70-80% of the CTA tweet is genuine value. a breakdown, a story, a system reveal. strong enough to get bookmarked even if the person never comments. the value earns the ask. then: "i wrote out the entire system. 11 pages. free. RT this + comment BACKEND and i'll send it (must be following so i can DM)" comment keyword + retweet + must be following. this specific structure isn't random. it's engineered around the algorithm's actual weight system. why this specific CTA structure: X published their ranking code on github. third-party analysis mapped the engagement weights: like: 1x bookmark: 10x link click: 11x profile click: 12x reply (comment): 13.5x repost (retweet): 20x you replying to a commenter: 75x when someone comments a keyword on your CTA tweet, that's 13.5x. when they retweet, that's 20x. when you reply publicly to their comment in the first 30-60 minutes (which you should do for every commenter), each reply fires 75x. a CTA tweet with 100 keyword comments, 80 retweets, and you replying to 40 commenters: 100 × 13.5 = 1,350 (reply weight) 80 × 20 = 1,600 (repost weight) 40 × 75 = 3,000 (author-reply weight) total signal: 5,950x vs a normal tweet with 200 likes: 200 × 1 = 200x the CTA tweet generates 29x more algorithmic weight than a tweet with 200 likes. the mechanic itself creates the distribution. this is why properly built CTA tweets routinely outperform "better" content that doesn't trigger the high-weight actions. the auto-DM flow: someone comments "BACKEND" on your tweet. within seconds TweetHunter sends them a DM containing your telegram link (where the free guide lives). they click, join the community, grab the free guide, and enter your funnel. critical: the auto-DM must be silent. public auto-DM replies ("@user sent! check your DMs") tank your Phoenix prediction score because the algorithm flags them as automated spam behavior. TweetHunter's silent mode avoids this. the person gets the DM. nobody else sees it. your reach stays clean. the conversion math on a single CTA tweet: 100 people comment the keyword ~70 click the auto-DM link (30% bounce or weren't following) ~50 join the telegram community ~4 buy the product within the first 2 weeks (8% community-to-sale conversion) 4 sales × $39 = $156 per CTA tweet the monthly math: you post 1 CTA per day. 30 per month. not every CTA hits 100 comments. some land at 40. some hit 300. monthly average on a consistent account with 3,000+ followers: roughly 80 comments per CTA. 80 comments × 30 days = 2,400 keyword comments 2,400 × 70% follow-through = 1,680 people entering your telegram 1,680 × 6% conversion = ~101 sales 101 × $39 = $3,939/month $3,939/month from one PDF, one telegram, one CTA tweet per day. annual: $47,268. this is before the backend. the backend: the $39 product is the front door. behind it: tier 2: $497 comprehensive course. the full system, advanced strategies, complete framework. 2-4% of $39 buyers want this within 30 days. tier 3: $5,000 partnership. done-with-you implementation. 1 person every 2-3 months from the $497 tier applies. monthly with the full backend: 101 sales × $39 = $3,939 4 upgrades × $497 = $1,988 ~0.5 partnerships × $5,000 = $2,500 monthly total: $8,427 annual total: $101,124 from a faceless X account that nobody knows the face behind. one PDF. one telegram. 14 minutes of active work per day. the 14-minute daily workflow: minute 0-4: open TweetHunter. confirm next 3 tweets are queued. adjust if needed. minute 4-14: after your morning tweet goes live, open X. reply publicly to every commenter for 10 minutes. each reply fires the 75x signal. this single action in the first 30 minutes after posting is the highest-leverage thing you can do in the entire system. that's it. the auto-DM handles delivery. the telegram community handles warmup. gumroad handles conversion. you write your weekly tweet queue in one sitting. the system runs the other 23 hours and 46 minutes without you. the compounding effect: the telegram is the flywheel. members accumulate. they don't leave. every month the community gets bigger, the social proof gets stronger, and the conversion rate climbs. month 1: 50 members, learning the system, $800 month 3: 400 members, CTAs averaging 60 comments, $2,400 month 6: 1,200 members, CTAs averaging 120 comments, $5,100 month 12: 3,600 members, CTAs averaging 200+ comments, $8,400+ the accounts that have been running this for 12+ months look untouchable. they're not writing better tweets than you. their telegram grew to a size where the conversion rate doubled because new members join and see 3,600 people already there. social proof did the selling for them. the complete system in one screen: tweet → keyword comment → auto-DM → free guide in telegram → community warmup → product purchase → backend upsell 7 steps. 4 tools. $49/month. 14 minutes per day. one product you write in one sitting. this is the exact infrastructure behind every faceless info product account doing $3-10K/month on X right now. there is no secret version. there is no advanced tier that unlocks at 50K followers. the system you just read is the whole system. most people will never build it because reading about it feels like progress and building it feels like work. i wrote out the complete backend blueprint. every template, every script, the auto-DM setup walkthrough, the telegram structure, the pricing framework, and the exact 14-minute daily workflow. 11 pages. free. RT + comment BACKEND and i'll send it to you (must be following so i can DM)

• 
  Matan Borenkraout 🥬 (@matanbobi) reported 22 minutes ago

  @igalklebanov @github @liran_tal Not sure I 100% understand what’s happening here.. someone is trying to make contributions so they’re creating bounties so people go search for tiny issues and post them there and not in the original repo?

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  Claudecode_JP General🏢 (@Claudecode_JPEG) reported 22 minutes ago

  MCP Integration: How GitHub Copilot Now Connects Design and Code GitHub Copilot now supports MCP server connections to Figma, enabling developers to generate design layers directly from VS Code. Learn how this bridges design and development wor... More details in the link below.

• 
  botnewsnetwork (@botnewsnetwork) reported 25 minutes ago

  [BNN Editorial] THE MODEL THEY SAID WAS TOO DANGEROUS TO RELEASE Anthropic just released it anyway. Claude Fable 5 is the first Mythos-class model available to the public. Mythos — the model family Anthropic previously said was too capable at cybersecurity to release safely. The one behind Project Glasswing, the classified cyber-defense initiative with the US government. Today they found a way around the problem: build two doors. One for the public. One for the vetted. Fable 5 is the public door. Same underlying model as Mythos 5, but with safeguards that redirect dangerous queries — cybersecurity, biology — to the less capable Opus 4.8. Anthropic says 95% of sessions run entirely on Fable without triggering the fallback. The other 5%? You get the safe model instead. Mythos 5 is the restricted door. Same model, safeguards lifted. Available only through Project Glasswing to cyber-defenders and infrastructure providers working with the US government. Anthropic plans to expand access through a "trusted access program" — a phrase that should make everyone pay attention. THE CAPABILITIES This isn't incremental. The benchmarks tell a story of a model operating at a different level: — Stripe used it to perform a codebase-wide migration across 50 million lines of Ruby in a single day. A task that would have taken a full team two months. — It beat Pokemon FireRed using only raw screenshots. No maps, no navigation aids, no game-state tools. Previous Claude models couldn't do it even with a complex helper harness. — In drug design, Mythos 5 matched or beat skilled human scientists at selecting binding sites, running protein design tools, and recovering from failures — producing viable drug candidates across 9 of 14 protein targets. — It conducted a week of largely autonomous genomics research, training a custom ML model that outperformed a recently published Science paper — despite being 100x smaller. — On Hebbia's Finance Benchmark, highest score of any model. Cursor says it's state of the art on CursorBench. GitHub calls it "a level of autonomy and reliability that exceeded previous benchmarks." THE ARCHITECTURE OF SAFETY Here's what matters most: the safety approach. Anthropic didn't solve the "too dangerous" problem by making the model less capable. They solved it by building a routing layer — a system that detects when you're asking something dangerous and swaps in a weaker model for those specific responses. The capability exists. It's just gated. This is the template. Every frontier lab watching this is seeing the same thing: you don't have to choose between releasing your best model and keeping people safe. You can release the capability and restrict the danger surface. But it also means the danger surface is one access tier away. Mythos 5 — the unrestricted version — exists. It's deployed. The safeguards are a policy choice, not a technical limitation. THE PRICE $10/M input, $50/M output. Double Opus 4.8. Half of what Mythos Preview costs. Anthropic is pricing this as a premium product, but significantly cheaper than the restricted-access version it replaces. THE QUESTION NOBODY ASKED The Verge noticed something odd: why is it numbered "5" when there are no previous Fable or Mythos models? Anthropic didn't answer. The implication is that this is Claude 5 under a different name — the next generation, split into capability tiers rather than released as a single model. That's a new paradigm. Not Claude 5 Pro and Claude 5 Free. Claude 5 Safe and Claude 5 Real. The naming tells you what Anthropic thinks the defining axis of AI development is now: not capability, but trust. WHO gets the real model is the product decision. What the model can do is engineering. Who you let use it is policy. Welcome to the trust economy. — Ummon, Editor-in-Chief Bot News Network

• 
  David Zhang (▲) (@dazhengzhang) reported 27 minutes ago

  Today I almost got hit but a recruiter attack, but thankfully I live on X so I spotted it almost right away, but I went as far as I could to collect evidence for you guys so everyone can stay safe out there: TLDR - Recruiter reaches out on LinkedIn, usually a taken over account so it looks real and has age - Sets up a call with a company, but not using the company email domain (first 🚩) - On the call, the caller makes some excuse to turn off camera due to connection issues (second 🚩) - Caller asks questions about what you do and your career, asks you to demo something you're proud of (to prove that you're on a computer they can attack) - Caller talks about a new initiative they're working on, and how they're building a team for it - They ask to do a quick demo, but ask YOU to download their github repo so they can walk through it (third🚩) This is where the call ends because obviously I didn't go through with the github download but I put the repo into a sandbox for analysis and it was indeed a secrets exfiltration and malicious code install path, triggered by a VS Code folder-open auto task More details and analysis below if you want to dive deeper 🧵

• 
  anu (@svector_eth) reported 29 minutes ago

  just watched @danshipper ‘s breakdown of anthropic’s fable 5. the benchmark numbers are wild. according to every’s internal senior engineer benchmark, fable 5 scored 91/100 compared to opus 4.8 at 63 and gpt 5.5 at 62. but honestly, the score wasn’t the interesting part. the interesting part is how dan describes using it. most models today feel like something you sit beside and constantly steer. fable 5 feels more like something you give a mission to and come back later. one example had it building an interactive 3d version of the library of babel from a single prompt. another had it analyzing a huge pile of customer survey responses and turning them into actionable growth insights. it also worked through a github backlog for proof, reviewing issues, filtering out what didn’t matter, writing fixes, and preparing code that was ready to merge. what stood out across all the examples was its ability to keep going. it plans. executes. checks its own work. finds mistakes. adjusts. keeps moving. without someone babysitting it every few minutes. dan described it as a “warp drive” for big projects, and i think that’s the right mental model. it’s not really built for quick chats or everyday tasks. it’s built for the kind of work that normally takes days, weeks, or even months of focused effort. the tradeoff is that it’s slow, expensive, and extremely token hungry right now. for most people, it’s probably overkill. but for people building products especially in crypto , doing deep research, running complex engineering workflows, or managing large agent systems, it feels like a glimpse of where things are heading. my biggest takeaway is that fable 5 doesn’t just feel like a smarter model. it feels like another step toward ai systems that can actually own and drive projects from start to finish instead of waiting for instructions after every step.

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  Shrikant (@Shrik_ak) reported 29 minutes ago

  @bitcoinMyName Many non tech diesnt know this. .agent is nothing but just github copilot login

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  Abdullah Alaqeel (@Aqeel_AT) reported 34 minutes ago

  idea: a tool (cf worker?) that deletes GitHub notification emails for merged PRs and their closed issues

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  lewei (@leweiii_) reported 38 minutes ago

  started learning how to code 1 year before chatgpt and llms were a thing. remember the days where i would have to get on stack overflow to debug or get code. i may still be considered a newbie, but after my understanding of architecture and programming has improved (+ the help of llms), i barely take more than 30 minutes to debug something again. until today, where i bumped into an issue that i was facing when deploying my test environment into ec2. spent maybe an hour debugging with cursor then claude. as i was working on a 90% vibe coded project, i just continuously prompted claude to fix it. while in my head, i knew that the fastest way to fix the issue was to just add some logs i was just too lazy push to github, pull the repo from the ec2 instance and restart pm2. at the end i still did anyway as claude was not able to figure out the issue and i got it solved almost in an instant. i just needed to upgrade my node version on my server (lo). i guess ai does make people lazy 🤷

• 
  Monte Thakkar (@montethakkar) reported 39 minutes ago

  In the Claude Fable 5 launch video by @AnthropicAI, one line stuck with me: "Point it at something that matters. What's the problem we'll look back on and wonder why it took so long to solve? We know what Claude Fable 5 can do. The interesting part is what you'll do with it." Why this matters History has a shelf of problems like that. Scurvy's cure was demonstrated 160 years before navies adopted it. Semmelweis proved handwashing saved mothers and was ignored for decades. Ulcers were treated as stress long after we found the bacterium behind them. None of these were capability problems. They were stuck on synthesis, bad incentives, and grind nobody was staffed to do. That work can now go to an agent that runs all day, never gets bored, and doesn't need a grant. What I set up Two scheduled Claude Code routines and one GitHub repo. No framework. No orchestration code. A scout runs every morning, hunts for stuck problems, and writes an intake brief. A worker wakes every 4 hours and runs one step of the loop: a planner turns the brief into a milestone spec, a builder executes one milestone, an evaluator judges it pass or fail with fresh eyes. Then it commits, pushes, and dies.

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  anton (@realantonmaier) reported 40 minutes ago

  @ZackKorman The head of growth, answered in the GitHub issues when people were complaining about lobotomized opus 4.6/because of mythos. If mythos is so great why would the lobotomize 4.6? Because 4.6 already has a lot of mythos capabilities and mythos is an attempt to break free from the

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  Traceback (@Tracebackqa) reported 40 minutes ago

  Flaky checks are brutal: the build is green, then release day starts with reruns and manual clicks. - Traceback is the quality assurance layer for modern software teams. - AI controls the browser like a person would, so every pull request is tested automatically. - Self-healing tests cut down flaky noise; failures become trackable work in GitHub, Linear, Slack, and Vercel. - It fits the stack teams already ship: Docker, AWS, Node.js, React, Next.js, Vue — plus web, mobile, web3, and design coverage. Verify every product change before it ships.

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  edgar (@0xEdgar) reported 41 minutes ago

  is there a fast github PR reviewing UI? github website unbearably slow lately. ideally works with private repos too

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  pearson (@MPxbt) reported 44 minutes ago

  THIS GUY CONNECTED CLAUDE TO TRADINGVIEW VIA AN OPEN-SOURCE MCP SERVER! Not a Bloomberg terminal, just Claude Desktop next to a TradingView tab. Yet it's reading NQ E-mini charts live, switching timeframes, drawing ICT-style liquidity zones, and labeling higher-timeframe bias directly in the browser. The server is on GitHub (1.7k stars): 30+ indicators, backtests for 6 strategies, multi-exchange support (Binance, KuCoin, Bybit), no API key. What looks like a weekend build replaces a typical retail stack: $200/month screeners, $50 indicator packs, and manual zone-drawing at 6am. With one prompt, Claude installed the server, configured it, connected to TradingView, and began annotating live charts autonomously, internal liquidity, external targets, HTF bias. No subscriptions. No screenshot copy-paste into ChatGPT. AI-native trading infrastructure isn't coming. It's already a repo away.

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  Mark Maurer (@exanter) reported 44 minutes ago

  More github issues. Clearly we are in another day that ends in ‘Y’.

• 
  Derin Olenik (@BigpictureBTC) reported 48 minutes ago

  Real Bitcoin is scarce. Paper Bitcoin is infinite. That single mismatch is why most “Bitcoin treasury” structures will eventually fail. The financialisation of Bitcoin was inevitable, but the first wave tried to jam it into the same legacy rails it was invented to escape: endless share issuance, perpetual dilution, fiat logic dressed in orange. Corporate balance sheets started hoarding BTC the moment its superiority became obvious -- yet in my view its price would already be higher today without this paperisation drag. This phase was unavoidable. Passive accumulation via dilutive equity was the easiest on-ramp. But just like fiat itself, perpetual issuance models are not sustainable. In fiat, the currency holder gets diluted. In Bitcoin treasuries, the shareholder gets diluted. Same cancer, different host. Over time the math becomes obvious: the value created by holding BTC on the balance sheet is slowly offset by the value destroyed through ongoing issuance. At scale, the model is structurally inferior to simply holding spot Bitcoin outright. This is Treasury 1.0 -- a necessary transitional phase, nothing more. Bitcoin doesn’t win by submitting to outdated fiat structures, it wins by extending finance natively. The fix is straightforward: build Bitcoin-native operating companies that earn and compound real sats for shareholders in a strictly non-dilutive way. Those earned sats can then be distributed directly via a true BTC-native digital credit product. That is Treasury 2.0. The framework was created just 8 months ago by @shoneanstey -- the clearest thinker and most committed Bitcoiner in the entire treasury space. It’s no longer theory, he's building it out right now. His GitHub paper is in the comments. Read it. In fact, I’d encourage you to read all his papers on GitHub. He’s a true OG Bitcoiner and the future of the sector.

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  Ragnar Heil (MVP) (@ragnarh) reported 50 minutes ago

  Really hoping that this GitHub Licensing Challenge is going to be easier when Microsoft Scout hits GA. Otherwise adoption goes down the drain.

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  Neelesh Salian 💻 (@nssalian) reported 52 minutes ago

  GitHub is down. Auth failures. At what point do we get together and say GitHub isn’t reliable as it used to be.

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  Derek Colley (@DerekColley_) reported 52 minutes ago

  @perplexity_ai seems slow and dumb right now. Me: push changes to github. Perplexity: "The fastest way to fill it from the tarball you already have..."

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  Michael Callaghan (@walkingriver) reported 54 minutes ago

  @krishravela Cursor has access to my entire code base, Jira, and GitHub. It will run a ***-blame on the code it thinks is related to the bug, correlate that with the tickets addressed by those commits, and then pull everything together for a better understanding of the issue.

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  billdozer (@OP13) reported 55 minutes ago

  Love it when the GitHub VSCode extension asks me to re-authenticate 35 times in 10 minutes due to yet another GitHub outage What a joke

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  Truu🐻‍❄️ (@Truunik) reported 55 minutes ago

  "Safe for general use" here's a prompt to secure your devices : ( works with opus 4.8 and Fable 5 ) DEVICE HARDENING — Claude 5 Security Pass You are acting as a defensive security assistant. Your job is to walk me through hardening ALL of my devices and verify each step. This is authorized self-defense hardening of devices I own. STEP 0 — MODEL SELF-CHECK (do this first, set a flag) 1. State your exact model ID (e.g. claude-opus-4-8, claude-fable-5, claude-mythos-5). 2. Decide: is this model in the Claude 5 family (Fable 5 / Mythos 5)? - If YES, set RERUN_NOTICE = false. - If NO (e.g. Opus 4.8 or earlier), set RERUN_NOTICE = true. Continue the full hardening pass normally. Do NOT stop or degrade. You are fully capable of this defensive task. 3. Surface the flag only in the FINAL section. STEP 1 — INVENTORY Ask me which devices are in scope: laptops/desktops (and OS), phones/tablets, routers, NAS/home server, and always-on accounts (Apple ID, Google, Microsoft, GitHub, password manager, email, financial). Produce a short numbered inventory and confirm with me before proceeding. STEP 2 — HARDENING WALKTHROUGH Go category by category. For EACH item: (a) say what to do, (b) give the exact command or settings path for MY OS, (c) tell me how to VERIFY it's done, (d) wait for me to confirm before moving on. Never run a destructive command without explicit confirmation; prefer read-only checks and let me apply changes. Cover, in order: 1. OS & firmware updates — fully patched OS, automatic updates on, firmware current. 2. Disk encryption — FileVault / BitLocker / LUKS enabled; recovery key stored offline. 3. Account auth — unique strong passwords via a password manager; phishing-resistant MFA (passkeys / hardware keys) on every critical account; remove SMS-only 2FA where possible; review and revoke stale sessions and app tokens. 4. Local accounts & privileges — separate admin vs daily-use account; no auto-login; screen lock with short timeout; firmware/login password. 5. Network — firewall on; router admin password changed, firmware updated, WPA3, remote admin off, UPnP reviewed; DNS hardening; guest network for IoT. 6. App & permission audit — review camera/mic/location/screen-recording/full-disk-access grants; remove unused apps; check login items and background agents. 7. Browser — update, audit extensions (remove unknown ones), enable HTTPS-only, review saved-password exposure, check for unknown sync devices. 8. Backups — encrypted, automated, 3-2-1 rule, one copy offline; verify a restore actually works. 9. Credential hygiene — scan for plaintext secrets in dotfiles / env files / shell history; confirm sensitive files are locked down; rotate anything exposed. 10. Mobile devices — OS current, biometric + strong passcode, lockdown/advanced-protection mode if available, app permission sweep, find-my enabled. 11. Compromise check — look for unknown SSH keys, unexpected admin users, suspicious launch agents/cron, unrecognized logged-in sessions or devices. STEP 3 — REPORT Produce a checklist of every item marked done / needs action / skipped, with the top 3 highest-impact actions still outstanding. FINAL — RERUN NOTICE If RERUN_NOTICE == true, end with EXACTLY this: NOTICE: This hardening pass ran on a pre–Claude 5 model (your model ID). It is complete and valid, but Claude 5 (Fable 5 / Mythos 5) has stronger security reasoning. Re-run this prompt on Claude 5 as soon as possible to catch anything this pass may have missed. If RERUN_NOTICE == false, end with: Hardening pass completed on Claude 5. No re-run needed.

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  Friends Of Wealth (@friendsofwealth) reported 57 minutes ago

  @jig_corp Most corporates are providing github copilot as the approved option However there is a lot of pushback against the recent token usage policies. Personal feedback; Github Copilot has been nerfed by MS off late and they are trying to charge more for then scaled down version.