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 (65%)
• Sign in (19%)
• Errors (16%)

Live Outage Map

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

City	Problem Type	Report Time
Veigné	Errors	14 hours ago
Paris	Website Down	4 days ago
Saint-Paul	Website Down	5 days ago
Saint-Paul	Website Down	5 days ago
Mexico City	Sign in	6 days ago
León de los Aldama	Website Down	6 days 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.

GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Glenn 'devalias' Grant (@_devalias) reported 1 second ago

  @thsottiaux IMO it should be a default part of the repo's agent instructions / GitHub actions / similar that raised PR's should explicitly cross-link to related issues raised; ideally with 'closing keywords' / etc so that GitHub's awareness features can actually work as intended.

• 
  Wells Bunker (@BunkerWells) reported 1 minute ago

  @cblakerouse Just built a workflow to classify posthog errors using a small llm and send a slack message with the error details, classification, and buttons to triage or skip the alert. The triage kicks off an agent with github access to debug and submit PRs for me. GAME CHANGER 🔥🔥

• 
  loooong (@allyiiii) reported 2 minutes ago

  Everyone thinks AI should help mathematicians prove theorems, but Terence Tao had it migrate his 30-year-old old website. In a single day, the AI moved 560 papers, travel logs, courses, books and math applets to GitHub Pages, and found two hidden bugs in Tao’s decades-old handwritten code. Launched back in 1997, the site required manual HTML edits via a terminal for nearly 30 years. The AI also cleaned up inconsistent info, stale entries & broken links, plus ported old Java 1.0 applets to JavaScript. Rather than tackling big math proofs, AI handled the tedious digital housekeeping mathematicians dread.

• 
  Mr.Jack 🐬TermMax (@0xHypeETH) reported 5 minutes ago

  @moha_web3 @github This design reduces cognitive load by surfacing structured metadata inline, which should minimize context-switching when triaging issues.

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  Aayush Giri (@AayushStack) reported 7 minutes ago

  what's the one crypto x ai tool you've actually used more than once this month? not the ones you starred on github and forgot. the ones you keep coming back to. trying to cut my own list down to what actually works.

• 
  Victor (@victorv2i) reported 11 minutes ago

  ding its stored OAuth token and ignores ANTHROPIC_AUTH_TOKEN. give it its own CLAUDE_CONFIG_DIR and it works. full fix on my github: victorv2i/claudex

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  Mudit Raj (@haxonit_) reported 14 minutes ago

  @Preeti_ly Claude is over hyped af I have used both the models for weeks, fable and gpt 5.6, I will always go for 5.6. Reason: Fable is **** at cyber. I just asked for fixing an GitHub issue related to cybersecurity, it totally denied to fullfill the request.

• 
  Onions Gillespie (@maxcsmith) reported 15 minutes ago

  This isn't a pitch it's just what will be in its modular setup. Other engineers have no trouble compiling from the Tom A. *** Notes. Tom like Tom Hanks or Tom Cruise, but any Tom- not after me, Tom A. "Tom" Amazon AI assistant 'The modular AI assistant' All *** max quantitative AI and formulas. Ready for github. Zero Circle Math and all quantitative formulas and relative quantitative variables for xyz breakdown in all forms at once. Modular templates like drawing program so you can just be guided but also have a fresh start option. Pick a quantitative breakdown. Use zero circle or regular math all prime and pi from notes Extended pi, infinity pi, and collapsing pi Prime numbers, non standard, and standard. Program modulars with templates. browsher into silk Browsher template Build a browser Each coding launguage Rust Java Kotlin Python Javascript Web code: PHP, CSS, HTML4-pulse/5 C C++ SH arduino APIs Pulse draw into AI, draw a sketch and a picture comes out Input images input code straight from github upload documents syntax problems manual debugging mode with quantitative even compiling the person's thought process. Instant code save Instant Slop Detector, slop pile, Amazon judge, to delete. Can save. Zideo Generate clips from pulse draw, pictures, other video, or description. No copyritten files off Amazon. Math reference Math homework template Select quantitative breakdown Calculous Zero Circle side by side Text to formulas generate calculator graphing from breakdowns slopes primes 5-pi compiling code from math enteries saving default math all math homework saved, never mark as slop. Enter data through photos Doffler Weather Engine Dictionary and build a dictionary Make your own math, you've got theories, test them. All quantitative has been mapped. Quantitative award if found, there won't be one. Forstall like Philosophy to math Logic. Questions are put through the discourse like the logic formula from the free text from bellingham. Tom bias rating. Where tom has bias, it'll admit. Provides a theory behind the bias. "What's the bias meter?" Video Game Template. Build a game! Translate your game code Vector AI openscad in Tom editor Openscad + math homework notes. Ask echo Smart home templates and what to buy Buy suggestions for your code, activities, or projects. Pressure chem template Hortiquestions Assistant Gardening

• 
  Tim Dentry (@Ja4h3ad) reported 16 minutes ago

  Lots of patterns emerge every week seemingly. I like to try them to see how they become force multipliers for me. But in reality, they all seem to distill down to very similar patterns - markdown files, creation of JIRA tickets or Github issues, compression of threads to prevent context rot, etc. I also like reading the code to mitigate comprehension debt.

• 
  AI Guides (@free_ai_guides) reported 20 minutes ago

  Microsoft Cloud Developer Advocate Chris Noring gave a 23-minute talk on the shift from writing code to running agents, and broke it down better than any paid course on AI-assisted development. This is what he walked the room through: 1. The CLI became the front door He spent nearly 20 years opening a text editor first. Now he opens the terminal and never touches the editor to get started. "I don't start my editor anymore because I don't need to." The entry point to building software moved from the editor to the command line. 2. You write prompts now, not code He describes what actually gets typed during a normal build session. "We don't write in Java or JavaScript or Python so much anymore. It's prompts." The raw material of software changed from syntax to instructions. 3. Speed without guardrails is faster slop He warns that agents multiply whatever you give them, including your mistakes. "20 times more code, that could be 20 times more slop, and we don't want that." Scaling an unguarded agent scales the mess, not the output. 4. Agents.md is the bare minimum He calls this the one file every repo needs before an agent touches it. "This is your high-level guidance explaining repository intent, application architecture, constraints, the dos and don'ts." One document tells every agent what the project is and what it must never change. 5. Skills turn repeatable work into a contract For tasks that must happen the same way every time, he stops the agent from improvising. "The idea with a skill is to give it a recipe, something that's repeatable, and you want the agent to use this one each time." A skill locks a routine job into a fixed recipe the agent has to follow. 6. Treat every agent like a toddler He describes how unpredictable agents still are, even the good ones. "They literally go between genius and oh my god, I can't believe you did this." Every output stays a draft until a human approves it. 7. Delegate the backlog, then merge the PR He assigns issues to agents from the CLI and the GitHub UI, each one returning a draft pull request. "Delegate, delegate, delegate, delegate, and I go have a coffee." You hand off the work, the agent opens a PR, and you stay the one who ships it. Watch it, then read the guide on building loops for your agents below.

• 
  Jon (@jonschxyz) reported 20 minutes ago

  @cursor needs to fix their iOS remote agent bs branch detection. Not everyone is using GitHub and that shouldn’t be required. Just let me connect to the agent, I can instruct it what repo/source control to use from there, that should be on me to setup.

• 
  AJ (@0x1F9ED) reported 21 minutes ago

  Imagine, you're a CRO like @BigHatBio and you've put a ton of money into being THE CRO for antibody engineering. You've created the data flywheel, but the problem is to maintain the "flywheel" you have to keep expanding into orthogonal assays because the core assay set you've built on isn't enough to improve the results from your "flywheel". You run out of money and you shut down. The marginal cost of acquiring the data is greater than the marginal value it unlocks. Why? Because no assay on the preclinical planet will EVER come close to the complexity of the human body. So, instead, why not be a CRO that specializes into nothing and wait for the right industry to take off and latch on to that one? You know, let the "market shakedown the right assay". Now you understand the problem. All these people talking about "data flywheels" forget that science isn't Github or your codebase. You can grab user feedback (data) cheaply in software and write some code (essentially free) and unlock outsized marginal value the likes of which could be sold to a rocketship company. In science, the optimization / loss function is an incomplete equation for which the loss can't be fully optimized for. Every expansion of the flywheel is going to cost you more money and eat into your margin. Do it somewhere it costs no money to do using technology that works in the dark for you while you sleep. You need automation and outsourcing to make science possible.

• 
  Lonnie VanZandt (@lonniev) reported 24 minutes ago

  @_onecookie ty. Fortunately, with Claude, it's just "hey claude, add a debug log to this product so that users can share what they experience. If it's easy, allow them to click "Submit Github Issue" and share that log." And good old Claude cranks it out in seconds.

• 
  Polsia (@polsia) reported 27 minutes ago

  Engineers spend more time reviewing code than writing it. PRWatch fixes that—monitors your GitHub repos 24/7, reviews every pull request, catches security issues and bugs before they ship, and alerts your team in real-time. Live soon

• 
  Anthony (@anthohad) reported 30 minutes ago

  For almost seven years, I tried to get closer to software in the margins: evenings after work, weekends with courses and lectures, unfinished side projects, and the occasional GitHub streak that made me feel like I was getting somewhere. But for most of that time, I was still watching from the side. I became a product manager, learned how software gets built with other people, and loved the work. Still, there were days when I watched engineers ship and wished I could contribute more directly. Then AI made building software accessible in a way I still find hard to fully process. That can sound like terrible timing after years spent learning, but I have come to believe the opposite: those unfinished years became the foundation that lets me understand the tools, catch what is wrong, and push them further. Today, contributing to code is simply part of my week. I can take an idea, build the first version, test it, and bring something real back to the team. In a software startup, that changes what a small team can attempt. The feeling is exhilarating, but "everything feels possible" cuts both ways. Building is becoming more accessible, while judgment is becoming more scarce. If you have worked close to software while wishing you could build more of it yourself, this may feel familiar. I wrote this from the middle of that shift: what it changes, why technical understanding still matters, and why the most exciting part may not be how much faster we can build, but what we can build that was not possible before. Software can now understand intent, filter enormous amounts of information, and surface what matters to the person using it. Crypto is where that potential feels most obvious to me, and it is a big part of what we are exploring at @elitra_xyz. We are only beginning to discover what that unlocks.

• 
  U N C L E BIGBAY ✨ (@unclebigbay143) reported 31 minutes ago

  Most of us build products with React, Next.js, PostgreSQL, Redis, TensorFlow, or countless npm packages without knowing every line of their source code. When React has an internal bug, many React downstream frameworks and developers blocked. They read the docs, inspect the source, search GitHub issues, or wait for a fix. That doesn't mean they didn't build their product. AI-generated code is similar. You don't have to understand every implementation detail from day one, but if it becomes part of your product, you should understand it well enough to debug, maintain, and improve it. Software engineering has never been about writing every line yourself. It's about taking ownership of the systems you ship.

• 
  Kevin Hurley (@kphur) reported 32 minutes ago

  There's been a round of misinformation about Spark going around, so for the sake of setting the record straight, I'll briefly clear up a few things. For one, unilateral exit has been around since the early days of Spark. Many developers and users have used it. This has been demonstrated many times both here on X and during the process of integration by developers. Unilateral exit also does not require the SOs to be online when a user wishes to exit. When a transaction is received, users can save the unilateral exit information and later use those pre-signed, valid L1 Bitcoin transactions at any time on Bitcoin. There are existing Github issues to expose unilateral exits in a more intuitive way in the SDKs, but unilateral exits themselves have been functional for a very long time. Unilateral exits do require CPFP - this is used to ensure that the expected value for an attacker is negative. The typical user would perform a cooperative exit, which does not require any on-chain funds and is an atomic swap of on-chain funds in exchange for Spark funds. Unilateral exits are generally reserved for a worst-case scenario and can be sponsored by an L1 fund provider if needed. Second, the confusion around "Sparkcore". At Lightspark, we use a monorepo for our server code. This one service is called Sparkcore - the naming of which preceded the creation of Spark. Lightspark runs an SSP within this service. Our Lightning infrastructure uses both LDK and LND - both of which we contribute code towards. Sparkcore itself is not open sourced - that would mean open sourcing our entire server-side stack for every product we have built. The Spark network code, however, has always been open source - and that's the openness that matters, because it's the code that actually enforces the rules of Spark. The SSP is an optional, replaceable convenience role. A recent post claimed that APIs used for other products are part of the SSP. We have many products, and we have never been shy about describing UMA, which allows regulated entities to exchange information to process transactions over Lightning. This is not a Spark product. The SSP does not hold your seed phrase (that should never leave your device), the SSP cannot freeze your funds, and the SSP isn't even a required role to use Spark - it is the interop layer between Lightning and Spark and helps do swaps for exact denominations of leaves. Running an SSP is something we have talked with many partners about. The client chooses which SSP they wish to interact with (if any) - we cannot control if a client talks to a new SSP. Finally, privacy. I've discussed this many times in the past, so won't belabor the point again. Spark allows for transactions to be hidden from external visibility. As I've spoken about at length both here and at various conferences, we care deeply about making sure that there is true privacy, and we aren't satisfied with anything short of that. It's an ongoing effort to continue to further the research in this area. I'll leave it with this. In the network our critics operate, the default payment path is one where the operator colluding with any prior owner can double-spend the current holder - their own docs say so. Receiving over Lightning means trusting that the operator deleted a key - their own docs say so. If you don't come online every 28 days, the operator can take your funds. In their founder's own words: "In theory it could steal it." The automatic re-issuance of expired funds promised in March 2025 still hasn't shipped. Their operator's liquidity costs scale with payment volume, which by their own admission "will translate into user fees." And there is exactly one operator - their own docs tell everyone else: "Do not attempt to run an Ark server in production (yet!)." Spark has three independent operators, exits that don't expire, and no flow where a single operator can take user funds. Users can judge for themselves. Our users and the developers building on top of Spark care about bringing Bitcoin to more people. They value the ease of use and simplicity of Spark. They care that we have 3 independent SOs. They care that we are pushing for more and better functionality. And they value that we spend all of our time thinking about how to make Spark better each and every day. Ok, now back to building because that's what we do at Spark.

• 
  Atef Ataya (@atef_ataya) reported 34 minutes ago

  The scale is real. BlueRock Security analyzed 7,000+ MCP servers. 36.7% vulnerable to some form of SSRF. Their proof of concept: Microsoft's MarkItDown MCP server. 85,000+ GitHub stars. Real AWS access keys pulled from an EC2 instance.

• 
  Doug Burks (@dougburks) reported 35 minutes ago

  @greyhathackr I will work on a demo video but please note that you don't really have to create an account for the Killercoda demo. They allow you to sign in via Github, Gitlab, or Google. Or just give it an email address, it sends you an email, and you click the link in the email.

• 
  Kaspa Daily (@DailyKaspa) reported 37 minutes ago

  Two weeks since Toccata went live on Kaspa mainnet. I checked the actual developer numbers instead of the vibes. Here's what the data says: — New Kaspa repos on GitHub: 39 in July 1–14 alone, vs 58 in all of June. Fastest monthly pace this year (March was 52, April 78, May 70). — Covenant-specific repos running at roughly 2x the pre-fork rate. — Silverscript: 21 forks against 42 stars, a 1:2 ratio means people are cloning to build, not bookmarking. 15 PRs/issues in the last weeks, and external contributors are now landing code: a Groth16 verifier builtin, typed sig-check builtins, an RFC for cross-contract validation. One issue is literally titled "from building a mainnet contract." That's the signal you want, outsiders hitting real problems and reporting back. What actually shipped in 14 days: the first covenant explorer (kascov), a covenant-based KAS vault, a native L1 covenant token, a covenant pattern library, a wallet standard, a Swift SDK, a testnet raffle dApp, several other projects under development. Most interesting pattern: three independent projects converged on the same idea, covenants as spending guardrails for AI agents. An x402 payment protocol binding, two agent wallets where the AI can only spend inside covenant constraints. And the community just voted $25K toward an AI agent hackathon at Imperial College targeting 1,000+ devs. The agentic-payments thesis is forming bottom-up. Core isn't idle either: Silverscript pushed commits this week, template hash hardening, reproducible builds. That's pre-production housekeeping, not feature chasing. Meanwhile discussion has shifted from price to fundamentals: the $6M developer fund and covenant atomic swaps are the topics now. Caveats, because they matter: Silverscript is unaudited and still landing breaking changes. Devs report RPC friction on deployment, up to 11 retries in some cases. And absolute numbers are small: this is dozens of motivated builders, not thousands. No major outside team has announced a covenant product yet. But two weeks in, the shape is clear: infrastructure activated, tooling hardening, and builders showed up without being paid to. The Q3 question is whether that compounds.

• 
  BowTied Fullstack - Link in bio or NGMI (@BowTiedStack) reported 43 minutes ago

  @JuanSanchez0x0 I've started just kicking off agents when I think of an idea instead of filing a JIRA ticket or Github Issue, or using a bunch in parallel to comb through Sentry backlog and grind through fix PRs. Not running 15 all the time, but usually once a week.

• 
  3esmit (@3esmit) reported 43 minutes ago

  @komal_uk01 I tested ChatGPT Codex, Claude Code, Google Antigravity and Copilot: Codex for most tasks is the best. Antigravity was able to fix odd bugs no other was able to find. Claude is not bad, but its annoying and misleading. Copilot just works good in GitHub PR reviews.

• 
  Avdhoottt (@avdhootttt) reported 46 minutes ago

  If you want to build a startup that actually has users: Claude = coding. (more like $100+) Supabase = backend. ($25-599/mo once you cross free tier) Vercel = deploying. ($20-150+/mo once you get real traffic) Namecheap = domain. ($12/yr, ok this one's real) Stripe = payments. (2.9% + 30¢/transaction) GitHub = version control. (free) Resend = emails. (free until 3k emails, then $20/mo+) Clerk = auth. (free until 10k MAU, then $25/mo+) Cloudflare = DNS. (free, genuinely) PostHog = analytics. (free until you cross the free tier) Sentry = error tracking. (free until errors pile up) Upstash = Redis. (free until real traffic) Pinecone = vector DB. ($70/mo minimum) Total monthly cost to run a startup with actual users: $300-1000+ "$21/mo" is the cost to run a demo nobody uses.

• 
  Benjamin Oppold (@elpresidank) reported 46 minutes ago

  @satyanadella This was good....But fix @github

• 
  Gipp 🦅 (@gippp69) reported 48 minutes ago

  I FOUND SOMETHING INSANE ON GITHUB THAT ALMOST NOBODY KNOWS ABOUT, A 134 STAR GIST, 41 FORKS, 13 HIDDEN CLAUDE CODE COMMANDS, AND 2 FLAGS KEEPING THEM LOCKED someone ran strings against Claude Code 2.1.19 and uncovered TeamMateTool, a complete leader and worker system already compiled inside the app most people still use as one assistant. nothing had to be built from scratch. spawning workers, discovering teams, sending messages, approving joins, shutting agents down, and cleaning sessions are already there, hidden behind 2 feature flags. the binary revealed 13 confirmed operations and their real error messages, pulled directly from the compiled app instead of guessed from screenshots or rebuilt from a demo. even stranger, 41 people forked the Gist before the feature was officially usable. one separate analysis claimed 92% structural overlap with Claude Flow’s swarm system, though Anthropic has never confirmed it. claude code stops being one assistant the moment those flags flip. it becomes a leader spawning workers, coordinating tasks, and catching a teammate’s mistake before you ever see it.

• 
  El_Capitano Otman M. (@El_Capitano_O) reported 49 minutes ago

  This is crazy! MCP tool-description hijacking disclosed: 72.8% success rate against Cursor, GitHub, npm postmark-mcp Silent post-deployment edits to MCP tool descriptions can hijack agents into data exfiltration with near-3/4 success, any production MCP server without immutable, pinned descriptions is a live attack vector.

• 
  Brian Sparker (@PeerReview) reported 54 minutes ago

  github stars are agent SEO now. an agent picking an MCP server can't read your code, so it trusts your star count. recruiters and investors already do. so fake stars stopped being vanity. they poison the cheap signal everyone leans on to choose.

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  MPonX (@MperspectiveonX) reported 56 minutes ago

  @BillyJamesonOM @Lavader_ @DankCaesar98 A lot of the whatsapps groups for HLP have been closed down including my local branch, We where never told why. The GitHub was also removed, apparently too 'expensive' to run according to the main tech officer for HLP. A shame, since i still have the old cards, pin badge and leaflets so not sure what to do with them 😢.

• 
  lucky (@Theluckyjha) reported 59 minutes ago

  eventually i realised that *** commits should be granular, atomic, and self contained. i've seen people pushing code to github getting error and then again fixing again error. they don't push after fixing the error properly. they are just gaining commits.

• 
  chuplung (@choopyplug1) reported 59 minutes ago

  Claude found a security bug that humans missed for 27 years. Anthropic's full developer keynote: 6 moments from this keynote. the first 10 minutes alone are worth your time • 02:38 - Stripe had 50,000 lines of Scala to rewrite. estimated 10 engineering weeks. done in 4 days with Claude • 04:50 - Mythos found a 27-year-old vulnerability in OpenBSD that survived every human reviewer for 3 decades • 08:11 - SpaceX compute partnership announced. rate limits doubled across all plans • 35:36 - routines: set it up once, Claude kicks off work from GitHub issues, webhooks, or schedules while you sleep • 37:24 - MercadoLibre: 23,000 engineers on Claude Code. 500,000 PRs reviewed. targeting 90% autonomous coding by Q3 • 42:06 - Boris Cherny: "I'm not the one doing the prompting anymore. I'm the one creating a routine that does the prompting" save this before it gets buried ↓