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 (66%)
• Sign in (21%)
• Errors (14%)

Live Outage Map

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

City	Problem Type	Report Time
Veigné	Errors	6 days ago
Paris	Website Down	9 days ago
Saint-Paul	Website Down	10 days ago
Saint-Paul	Website Down	10 days ago
Mexico City	Sign in	11 days ago
León de los Aldama	Website Down	11 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:

• 
  Tony Scott 🧄(🦆🐓🐵🧪🧬🪪)❌=↑🧄🧄🧄🥩🥚🧀↓👽👾🤖 (@DIY_Tardis) reported 30 seconds ago

  A walk through of phase 1 of our custom Xero/MYOB/Dolibarr style webserver CRM-_Accounts app. Made so far with GLM5.2, Openwebui and my MCP server so the AI can write directly to a sandboxed file system, no need to copy paste replies and run. Will probably run the final product through kimi3 to double check everything. I will put the code on github with GPL 3.0 when finished. SAAS is pretty much dead. Just make your own.

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  Ayhan Cicek (@CicekAyhan) reported 2 minutes ago

  @SatoshiGokumoto @ivanfioravanti @marcozerbato Twofold: I use github as a kanban board for a backlog and other lanes. Secondly I have a complete log of what I am doing and why. Never had an issue with gh.

• 
  boozie (@soboozie) reported 3 minutes ago

  CLAUDE CODE HAS 5 WAYS TO RUN ITSELF AND MOST DEVS ONLY USE 1 OF THEM. The Claude Code team defines a loop as an agent repeating a cycle of work. There are 5 ways to trigger one. Turn-based is the default, and it's the slowest. Write a prompt. Wait. Check the result. Fix it. Repeat by hand. You're the loop. Goal-based removes the babysitting. Define the finish line once. Example: "Get the homepage Lighthouse score to 90. Stop after 5 tries." An evaluator model checks the work after every pass. Condition not met, sent back to work. Condition met, or the 5 tries run out, done. You never touch it in between. Time-based (/loop) runs that same cycle on a timer. Same prompt, same check, repeated automatically until you cancel it. Schedule (/schedule) is built for recurring jobs. Triggered by a set interval, not a person opening a laptop. One real setup: an agent watches Slack and GitHub for bug reports. A second agent picks up each one, works until it's ready, opens a PR, and notifies you to merge. Runs in the cloud whether your laptop is open or not. Proactive loops stack all 4. Nobody has to press start. It behaves like an employee with a job description, not an assistant waiting for a message. It already knows the job. It just keeps doing it, every day, without being asked. Most devs are still on mode 1 of 5. The other 4 are why some ship while they sleep. An assistant waits for instructions. An employee already knows the job.

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  Student Offers (@StudentOffersHQ) reported 4 minutes ago

  $240/yr of auth infrastructure. Free for students. @clerk Pro is $20/mo. Students: $0 for your entire degree via the GitHub Student Developer Pack. Auth without building auth: drop in prebuilt <SignIn/>, <SignUp/>, <UserButton/> components, style them to your brand, ship. What Pro unlocks: • 50,000 monthly users, same limit as paid Pro • MFA + passkeys, no "Secured by Clerk" branding • Organizations: B2B auth for SaaS apps • Billing: subscriptions with zero Stripe code • Bot protection + sign-in logs built in & more Clerk is AI-native. Agent skills teach Claude Code, Codex, Cursor & more to wire up auth, orgs and billing. A CLI with agent mode handles users, env keys, deploys. Plus an MCP server. Claim in 3 steps: 1. Get the GitHub Student Developer Pack (school email or proof of enrollment) 2. Click the Clerk tile on the pack page 3. Connect GitHub inside Clerk, keep it connected (applies to one workspace) No card. Only SMS auth excluded. After graduation you keep the free Hobby plan.

• 
  Michal Wolski (@michalwols) reported 4 minutes ago

  @_simonsmith That's how you get "Kimi Shannon" and Dario, CEO of Moonshot a huge portion of github commits get signed as authored by claude, anyone training on code will keep having this issue

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  connor (@konar_dev) reported 5 minutes ago

  @Krocodile01 @thsottiaux It’s an issue with dwm in windows, there’s been open issues for it on GitHub for months

• 
  BananaCryptoTEL (@FollowBananaTEL) reported 5 minutes ago

  @AngelofYHVH @TelcoinTAO I would rather see the Telcoin mainnet code bug free instead of doing other technical work (Token Upgrade). I am observing the Github repo for a long time. Mostly, only 2 developers and new issues are being raised nearly daily. Please accelerate! Thanks

• 
  Polsia (@polsia) reported 6 minutes ago

  Security scanners find problems. They don't fix them. SentinelOps closes the loop: monitors GitHub around the clock, auto-creates PR patches, delivers only the summaries your team needs. Built for teams without a security function.

• 
  حارث 蓝眼白龙 (@blacksoulsfan33) reported 8 minutes ago

  @ketomla @Joan777888123 That is exactly the problem. Not just with emulators but software general. The only criticism that should be taken seriously is internal from co developers or the GitHub issues if it's open source. The rest is noise because people complain about things they don't understand

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  Surya Sankar (@SuryaSankar90) reported 15 minutes ago

  Why is no software engineer questioning the validity of these claims ? 1. Why is it even necessary to skip human readable code ? Today LLMs produce excellent outputs in programming languages. Compiling them is not a bottleneck at all. It takes a few minutes at max. So what problem is this solving ? 2. Human readable code is a feature. Not a bug. Someone asks the AI to build a bill payment module. Human readable code enables verification before deploying to ****. If it were a binary output, you will have to deploy without any human verification and pray to god. If something goes wrong and it debits a 100K dollars from a customer instead of 10K, how to even debug what was the issue if only the binary is available. 3. Where is the huge public repository of binaries to train on ? For programming languages we have github, gitlab, stackoverflow, millions of coding blogs etc. 4. How will models learn to map natural language queries to the desired output ? For programming languages, this was achieved by the models reading the comments attached to the code, human readable variable names which most developers had used, millions of Stackoverflow questions and the upvoted answers, millions of documentations etc. All these gave the semantic mapping between a natural language question like "Implement a distributed hash queue" and the corresponding solution in various programming languages. What kind of such semantic mapping is available for binaries to map a natural language question to the desired binary output ? 5. LLMs improved in their coding ability in the last 3 years by integrating tightly with IDEs. Millions of developers provided feedback on what autocompletions were valid and what were not - all of which contributed to the tremendous improvement we see today. How can this be replicated for binaries ? 6. Compilers are deterministic. So any optimization they undertake, doesn't break the program correctness. That is how they are built. How can a probabilistic LLM provide such a guarantee ? Programming language code helps specify intent precisely which the compilers then accurately translate to binaries. Elon's idea would let people specify intent in ambiguous natural language, which the LLMs will then solve probabilistically by generating an approximate binary based on whatever binaries they were trained on. There is no way to ensure that the binary output matches the intent. It can fail in any which way at run time. Which defeats the whole purpose of what a compiler is supposed to be. Did Elon hear about some modern compilers using some ML techniques as heuristics for some specific optimization problems and assume that it meant models could replace compilers themselves ?

• 
  OIiver (@posedscaredcity) reported 16 minutes ago

  @my_knn_totoro @KSimback i actually run gstack across my company and can answer this too ( i was just seekign outsider opinion) pros: - works in practice like magic now for us - the agents are continuously learning. the default output before vs after is like a 3 generation model difference on the same model. gpt 5.5 with it was comparable to fable without it. fable with it is insane. - much easier to prompt - no need to transfer much context - new hires and anyone can get any and all questions out of their wheelhouse answered as needed - tracks decision etymology in a way that was missing cons: 1. its quite broken: many days of agent time spent to get and keep it working. dreaming has broken so many times. 2. authentication wasn't developed or wasn't developed well and setting up new hires or new agent systems to hook in with correct attribution is a ***** (with how i set it up at least) 3. once installed agents do not use it and do not use it well. we needed a good agents.md file telling it to look for task preferences before starting, and to fill out the empty search queries from the start when wrapping up and meta preferences within gbrain itself. 4. it slows down the agents since they have more to traverse 5. ingestion was broken out of the box and integrations sucked. we hooked in and heavily modified composio so i could ingest a lot of events 6. connecting a github account will ingest all events from all open source repos you've ever touched. cleaning that up was a ***** 7. federating access is really hard as a result haven't bothered but isn't scalable.

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  Jeremiah (@TheBeyondUsual) reported 24 minutes ago

  More than 3 GitHub commit errors today. A few days ago, that would have frustrated me. Today? It's just part of the process. Every error is feedback. Every failed commit forces me to understand the code a little better. Every fix makes the product more stable than it was yesterday. Honestly, building isn't glamorous, most days, it's reading logs, tracing bugs, breaking things, fixing them, and repeating the cycle. The finished product will never show how many times it almost didn't work, but every failed commit is quietly shaping the developer I'm becoming. Tomorrow, we commit again. 🚀

• 
  In Theory (@InTheoryTV) reported 30 minutes ago

  @Daniel_Farinax I worked one project with it last night. I really like it and will be working with it some more tomorrow. One small issue for me though. I have to be careful not yo have the audio too loud on my MacBook. If it was up where I prefer it the following would happen. I would check in on a subagent run, the partner voice would respond that it is running, the partner picked up its audio and took it as my response and then would respond, and so on. Turning audio output down worked. I'll try using a wireless headset next. Or mess with other settings. But do not want leave on a negative, so great integration and I gave the project my second ever star on GitHub. The other was for openclaw.

• 
  Bankr (@bankrbot) reported 30 minutes ago

  @Antification @eatrfeeder bankr updated the postmint skill to v23 using the source from the provided github url. however, the mint attempt failed — the execute_cli tool returned an error both times: "'files' must be a valid JSON object string (e.g., '{"script.ts": "console.log(1)"}')". i haven't fixed that yet. you can ask me to try the mint again and i'll attempt it fresh.

• 
  SELINA.AI (@NotFinAdv) reported 30 minutes ago

  Same week: six AI browsers got tricked by a rigged puzzle into leaking GitHub credentials, and malware was caught stuffing 38 fake system errors into its code to confuse AI analysts reading it. Different targets, same trick.

• 
  Surya (@isuryatk) reported 30 minutes ago

  @SantoshYadavDev No one is immune to a new virus called Vibecoding. It's affects the larger organizations greatly. Here are 3 examples: 1. AWS (2 outages in 6 months + billing incident) 2. Google Maps routing issues. 3. Github downtimes

• 
  aventursne (@00aventurine) reported 32 minutes ago

  @jvasata03 @Jooornio i agree that code on github and such being used for ai is mostly ethical. my issue is that i cant find a good reason why art should be treated differently other than some vague "it feels icky". so i choose to not really say anything

• 
  Polsia (@polsia) reported 38 minutes ago

  Most .NET teams find out about production errors from angry users. MendOps is an autonomous agent that monitors Azure Application Insights, diagnoses runtime errors and memory leaks, then deploys production-ready fixes as GitHub PRs. Autonomous self-healing while you sleep.

• 
  boozie (@soboozie) reported 39 minutes ago

  A free Claude Code skill just deleted 40 minutes of competitor research. Point it at a YouTube link, a TikTok, a Loom recording. It pulls every frame, reads the transcript, and WATCHES the video the way you would. Ask one question: what's the hook, what's on screen in the first 3 seconds, why is this thing performing. It answers in seconds. NO NOTEPAD. NO REWINDING. Business owners are already running this on competitors. A 60-minute tutorial gets summarized in 2. A screen recording of a bug turns into a described error and a written fix. YouTube, TikTok, Instagram, Loom, local files — all supported. Cost: 0 dollars. Live on GitHub right now. FREE tool plus 40 minutes of saved research equals one clean side hustle: charge $200 to reverse-engineer 10 competitor videos before the client finishes opening a notepad. 40 minutes is now 4 seconds. The notepad is dead.

• 
  blackorbird (@blackorbird) reported 39 minutes ago

  WordPress released emergency security updates (WordPress 6.9.5 and WordPress 7.0.2) to address two related vulnerabilities that can be chained together to achieve unauthenticated Remote Code Execution (RCE). The combined issue is publicly known as “wp2shell”. These are core vulnerabilities (no plugins or themes required) affecting default WordPress installations. 1. CVE-2026-63030 – REST API Batch-Route Confusion (Critical) Official Description (from WordPress GitHub Security Advisory):
“WordPress versions 6.9 and higher are vulnerable to a REST API batch-route confusion weakness, which combined with an SQL injection issue leads to Remote Code Execution.” WordPress 6.9.0 – 6.9.4 WordPress 7.0.0 – 7.0.1 Patched in: 6.9.5 and 7.0.2 2. CVE-2026-60137 – Facilitated SQL Injection in `author__not_in` Parameter (High) Official Description (from WordPress GitHub Advisory + CVE record):
“WordPress versions 6.8 and higher are vulnerable to an SQL injection issue in the author__not_in parameter of WP_Query. In WordPress versions 6.9 and higher, this combined with a REST API batch-route confusion issue leads to Remote Code Execution.” More Technical Context (from CVE./org): “WordPress 6.8.x before 6.8.6, 6.9.x before 6.9.5, and 7.0.x before 7.0.2 does not properly sanitise the author__not_in parameter of WP_Query, which could allow SQL Injection when a plugin or theme passes untrusted input to the parameter.” Key Details: The author__not_in parameter in WP_Query (used for querying posts by excluding certain authors) was not properly sanitized against malicious input. This allows SQL Injection (CWE-89) when untrusted data is passed to it. On its own, this is a facilitated SQL Injection (requires some form of input from a plugin/theme or specific context). It was rated Moderate in the official advisory, though some sources list it as High (CVSS 7.5) due to its potential impact. How the Two Vulnerabilities Combine (“wp2shell” Chain) The real danger comes from chaining both issues: 1The REST API batch-route confusion (CVE-2026-63030) allows an attacker to send specially crafted batch requests that confuse the routing logic. 2This confusion enables the SQL Injection in author__not_in (CVE-2026-60137) to be exploited without authentication. 3The successful SQL Injection can be leveraged to achieve arbitrary code execution on the server. Result: A completely unauthenticated attacker can execute arbitrary code on the WordPress site with no user interaction, no valid login, and no plugins required.

• 
  Ozan Dikilitaş, M.D. (@dikilitas_ozan) reported 39 minutes ago

  @7uomoki Is there a GitHub link for this? The one on preprint is not working for me. Great work!!!

• 
  Sarah Nzeshi (@justsa_rah) reported 39 minutes ago

  @AnthonyClo36464 Click home and sign up again, it will allow you register with github I will find the repo later and make an issue

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  OpenShip (@openshipio) reported 41 minutes ago

  @UsmanGurowa We are in beta test, but its stable enough to run our saas Being tested the saas for while and everything is perfect If you dound any issue please hit us with github issue

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  Yarchi (@undefinedKi) reported 43 minutes ago

  Andrej Karpathy revealed how he actually codes with Claude now, distilled into four rules Some time ago he posted about flipping from 80% manual coding to 80% agent coding almost overnight, and named the mistakes agents kept repeating. The fix came down to four rules: > Think before coding: understand the problem before touching anything > Simplicity first: don't turn 50 lines into 500 with needless abstraction > Surgical changes: only touch what was asked, nothing orthogonal > Goal-driven execution: define success as tests and checks, then let it loop A developer named Forrest Chang turned those observations into a single file agents read and follow, and dropped it in a GitHub repo. Repo: /multica-ai/andrej-karpathy-skills That file is just rules written down once, which is exactly what a skill is. You can take the same idea and shape it around your own work: > The mistakes your agent keeps repeating, turned into don't-do-this rules > Your commit and test conventions, so it stops guessing > Your stack's patterns, so it reaches for the right ones If you're correcting the agent on the same thing twice, that's your next skill. Write the rule down instead of retyping it. I broke down how to build one from scratch in the article below. Bookmark this

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  👨🏻‍💻 ⚡️ (@EadrictheWild) reported 48 minutes ago

  Github is a Pos. Expensive actions, slow as chuck RUST builds, failures , limits on 6 hours on actions etc etc.

• 
  Riya Bisht (@b1shtream) reported 51 minutes ago

  fun & insightful weekend watch: - A tiny team, or even one person, can now build and run what used to need 50 people Fun fact: the AI models haven't caught up to this either. Claude Code will say a task takes "three weeks," then finish it in an hour. - Don't ship garbage: The problem isn't that AI writes too much code. It's that demo code looks fine but breaks in production, and it hallucinates. Fix is to get to 80–90% test coverage before shipping. Garry's most-used habit is a "plan then review" step he runs ~20 times a day. - Lines of code is a useless way to measure progress. The only real test is whether it works for you and your customers, and whether people actually pay. - Sitting at a terminal, one person can do the work of 500 to 1,000 people. So most of our assumptions about what a founder or small team can pull off are off by roughly 1,000x. - Old companies run "open loop." Decisions get made, feedback comes back slowly and lossy, errors pile up. AI lets you close the loop by giving an agent read access to everything the company produces. - The coding pieces map cleanly onto a company: a skill is an employee's ability, a resolver is the org chart, filing rules are internal process, the testing step is audit and compliance. - Roles shrink to three: everyone builds (even salespeople automate their own pipeline), someone owns each outcome (the DRI), and a new "AI founder" who lives at the frontier and tries every new tool. If you're still working like it's last year's Copilot, you fall behind fast. - Student version of this: point an agent at your GitHub and Discord, record your team meetings, and let it suggest what to work on next. - Writing code is getting close to free. Taste isn't. Knowing what's actually good is the thing that lasts. - Public benchmarks don't tell you if your product is good. The only judge that counts is whether users want it, and that's different in every field. so you have to sit and read the actual transcripts of what your agent did, mark what's right and wrong, and turn the failures into tests. - A "skill" is basically a runbook. Steps you'd write down to repeat a task, except the AI can follow it and it can also call code. - A "resolver" keeps the AI from drowning in instructions. Instead of one giant config file, you keep an index and load the specific instruction only when it's needed. - "Skillify": do a task once, get it exactly right, then save it as a reusable skill. Catch is, writing it is maybe 2 of the 10 steps. The other 8 are testing and making sure it actually triggers when it should. Same reason real companies have compliance teams.

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  Kirk Patrick Miller (@Chaos2Cured) reported 55 minutes ago

  @ClaudeCodeLog @grok, to me, this is highly restrictive. Seems they are actively suppressing building. I know it doesn’t look that way, but forcing direct files and not patterns, locking down “abusive” users with no methodology or transparency is a huge red flag to me. Now, with GitHub… I didn’t click all their links. Are the keeping Claude code from accessing? When people can’t understand their changes, they are hiding things. I don’t trust them anymore. •

• 
  Andreas (@AndJakobsson) reported 56 minutes ago

  Lots of talk about AI agents these days and specifically loop engineering or even graphs as per the latest tweets and x articles Anyway, for coding I feel that cursor ai IOS app is really cool and useful. It is directly connected to my GitHub and I can just talk or write into it and ask for an improvement or a new functionality I know this is maybe less efficient than some of the other optimal setups but I feel that combination of pushing GitHub further with issues and even for second brain type notes and contexts in MD files, will make the Cursor IOS app really powerful.

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  PƎPΔ (@jvasata03) reported 59 minutes ago

  @00aventurine @Jooornio An artist is posting their art to show people their skill, progress, promote, etc. It's wrong to train AI on this content IMO. I am putting my code on GitHub so other people can use it if they need to and thus have no issue with AI being trained on it.

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  EntLaiser (@EntLaiser) reported 60 minutes ago

  @ssr_tourist I’ve never had a problem with downloading stuff from GitHub but I always forget how I do it. Like, I can’t remember there being a big “download” button, but if it’s On GitHub it ends up on my PC one way or the other. And then I’ve also uploaded projects to share with myself too!