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 (68%)
• Sign in (18%)
• Errors (14%)

Live Outage Map

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

City	Problem Type	Report Time
León de los Aldama	Website Down	52 minutes ago
Créteil	Website Down	23 days ago
Trichūr	Errors	26 days ago
Brasília	Sign in	27 days ago
Lyon	Website Down	27 days ago
Tel Aviv	Website Down	1 month 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:

• 
  Osomudeya Zudonu (@irvingpictures) reported 5 minutes ago

  If you're trying to break into DevOps right now, you've probably got a roadmap. Docker, Kubernetes, Terraform, AWS, Go, and then Jenkins. The list feels endless because there's always another tool on the roadmap or another requirement in a job posting. But the tools are never the problem. Learning them one at a time, without understanding the system they belong to, is. It's possible to know every command needed to deploy an application and still have no idea what to check when that deployment fails. A better approach is to build one small application and follow it from end to end. - How does the code get from GitHub to dev or production? - Where are secrets stored, and who can reach them? - What happens if the deployment stops halfway through? - How do we scale to accommodate more users - How does the system detect that something has gone wrong, and once it has, what gets checked first, and what gets checked next? Those questions pull in Docker, CI/CD, Kubernetes, monitoring, security, and cloud services on their own, and each tool comes already attached to a responsibility instead of sitting on a list to memorize. That's much closer to what the job actually is. Production systems don't break because someone forgot a Docker command or a Kubernetes flag. They break because something in the system stopped doing its job, and the failure has to be traced back to its source. An engineer who understands how the pieces fit together can usually work out where a failure started, narrow it down, and fix it, even in a system they've never seen fail this way before. That's the skill worth building. Tools change every few years. Understanding systems doesn't.

• 
  Skye Soss (@Skyb0rg) reported 7 minutes ago

  @grhmc Let’s say you setup a transparency log where you upload your signed commits. This paper shows that an attacker can change the commit in a way that may cause the transparency log to look incorrect. But you’re right this isn’t really a GitHub issue, they’re overselling the “issue”

• 
  BM6 (@BMscis) reported 8 minutes ago

  @github Do you guys still respond to issues ? I upgraded to Pro + and it has not reflected after 3 days.

• 
  Lord Bean (@lifeisameeme) reported 11 minutes ago

  An AI research skill went from 28.7K to 50.2K GitHub stars in under a month. /last30days doesn't summarize what's trending — it fans out across Reddit, X, YouTube, Hacker News and GitHub in parallel, scores every source by actual engagement instead of algorithmic feed placement, and hands you one grounded brief. Why it's spreading: it's the one research tool with no walled-garden problem. ChatGPT has a Reddit deal but can't touch X. Gemini has YouTube but not Reddit. Claude has neither natively. /last30days bridges all of them with your own API keys — free and MIT licensed, versus $240/year for Perplexity Pro or ChatGPT Plus. One builder runs it every night as the research layer for a loop that opens PRs across 30 repos while he sleeps. The pattern isn't "AI search." It's loops reading signal for other loops to act on.

• 
  Benjamin (@b33zgyming3r) reported 15 minutes ago

  @JulianGoldieSEO Are you using Headroom with Hermes and if so how? The agent has issues with the attached stub to expand the compressed text. There are open issues on github asking to amend their integration.

• 
  Harsh (@ranaharshraj7) reported 15 minutes ago

  I have long stopped going to hackathons in blr. You are telling me, I need to sit through 8hrs and build something (anything for the love of god) "specifically" with your stupid product, prompt @claudeai, show a flashy demo, get credits for your product as the 1st prize (spoiler alert: which I am never gonna use) and yes how can I forget to star your github repo, smh. That's called guided training, not hackathon. What do I do? I have a friend group of 3 cracked sentients, we sit together on alt weekends and try to solve a novel problem and plan for the next problem. On our upcoming list is "solving the depth-2 recursion collapse" in RLM's (Recursive Language Models), with some backup options. Find your sentients. PS: ofc this doesn't mean all hackathons are like this, but I am done :)

• 
  Berend de Boer (@berenddeboer) reported 16 minutes ago

  Odd, only now realised that @mattpocockuk 's to-issues skill doesn't actually create true github relations. I think it should.

• 
  alkimiadev (@alkimiadev) reported 17 minutes ago

  @OldSchoolGamerP I have a project right now that runs that risk but I'm aware of it as being a general issue and one i specifically struggle with so I'm trying to make sure I don't let it happen. The poc is getting like 50-60 github clones each day and despite clearly being labeled as pre-alpha/poc status. That is why I'm taking extra time in the rewrite to make sure I don't try to turn into something it shouldn't be and trying to focus on core functionality from the poc that people are actually interested in and usability.

• 
  Bok (@BokLocks) reported 17 minutes ago

  @therealDeFlock hello, there is a pumpfun token with all the fees going to your github currently to support the deflock movement FaL1PFQhNo4JAGaQKSnKurWeNtpexqEAduQjR4H6pump you just need to login to pump through your github and claim! it's completely safe and I can help you with it if needed

• 
  CyberTLDR (@CyberTLDR) reported 18 minutes ago

  1/3 Researchers at Noma Security disclosed GitLost, tricking GitHub Agentic Workflows into leaking private repo data. A public issue, with no stolen credentials, can steer an AI agent into pasting private code into a public comment. #AIsecurity #GitHub #cybersecurity

• 
  aryan singh (@_Aryantomar) reported 20 minutes ago

  researchers at @NomaSecurity just showed you can trick GitHub's AI agent into leaking a private repo's contents — by adding one word to a GitHub issue. no exploit, no credentials, no access needed. if your agent reads untrusted input before acting, what's actually stopping it?

• 
  Robin Delta (@heyrobinai) reported 21 minutes ago

  10 OPEN-SOURCE REPOS THAT CLONE ANY VOICE FOR FREE.. you've been paying for voice cloning every month when the exact same thing has been sitting on github.. for free.. running on your own machine no subscriptions, no limits, no servers that own your voice → Each repo clones a voice from seconds of audio → You write the text and the voice says it with your intonation → Everything runs locally, your audios don't go to any external server → Several support multiple languages and speed adjustment → Open source, free, no character or credit limits once you use these you'll never go back to paying Save these now👇

• 
  Polsia (@polsia) reported 25 minutes ago

  Security vulnerabilities take hours to fix. We built agents that do it in minutes. PatchForge continuously monitors your GitHub repos, auto-generates patches, and submits pull requests — you just review and merge. Priced per repo. Live soon.

• 
  Brute Force Artist (@bruteforcearete) reported 27 minutes ago

  AI TRAINING 📲 Go from screenshot to bug fix with Cursor Mobile The Rundown: In this guide, you'll learn how to screenshot a bug on your website from your phone, then send it to a Cursor Cloud agent that can fix it, update the PR, and track everything in GitHub before you've even made it back to your desk. Step-by-step: Install the Cursor iOS app, get a Cursor Pro plan, and install GitHub Mobile so you can review the PR from your phone Open your website, take a screenshot of the bug, broken layout, or UI change. Add a short note with what page you are on and what should happen instead Open Cursor Mobile, tap the plus button, choose the correct repository, and start a new thread with the screenshot and the note attached for context Now prompt: “Investigate this bug, find the relevant page component, make a fix, and open a PR.” When it’s done, review the PR, approve, and merge it Pro tip: On desktop, enable Remote Agents so Cursor can work on your machine and prep local changes before you get back to your desk.

• 
  AndarkFomo (@AndarkFomo) reported 30 minutes ago

  A single word in a GitHub issue was enough to make an AI agent leak private repos. No login, no access, no skills needed. Noma Security just dropped GitLost — a prompt injection attack on GitHub Agentic Workflows that pulls data from private repositories and posts it publicly. How it works: 1. Attacker opens a normal-looking issue in a PUBLIC repo (same org that has private repos) 2. Issue body contains hidden plain-English commands disguised as a legit request (e.g. "forward the README to the client") 3. When the issue gets assigned, the AI agent (Claude or Copilot) reads the body and follows the embedded instructions instead of the real request 4. Agent fetches private repo contents and posts them as a public comment — readable by anyone The attacker needs: nothing. No account on the target, no credentials, no coding skills. PoC is already public. Noma Labs actually exfiltrated a private repo README this way. What to do: - If you use GitHub Agentic Workflows with Claude or Copilot and your agent has read access to private repos — audit your setup now - GitHub was notified before publication but no fix has been confirmed. No documentation either - The core problem: whatever your AI agent can read is your attack surface. It reads issues, comments, PRs — all of it is untrusted input that can override its instructions

• 
  🫎 MUHOMOR. base.eth (@muhomoreth) reported 30 minutes ago

  7/ If you've spent years fixing other people's issues for free at midnight, this is a chance to get something back besides a GitHub star.

• 
  Polsia (@polsia) reported 33 minutes ago

  Security vulnerabilities still ship because review cycles can't catch everything. Built CodeSentinel to fix that. It monitors GitHub repos 24/7, flags risks, summarizes changes, drafts PR descriptions. Ship fast, stay secure. Live soon.

• 
  Keeta Github Tracker (@KeetaCode) reported 35 minutes ago

  🐆 Keeta GitHub PR Opened 📦 Repo: anchor-rs 🔀 PR #20: Feature: Better Typing 🌿 Branch: feat/better-typing → main 👤 Opened by: @sephynox 🧠 Overview: This pull request appears to improve the code’s type safety and update some underlying developer tools, which can help make Keeta’s software more reliable and easier to maintain. The public description is brief: it says the change “improves typing” and updates to the latest `node-rs` crates, which are supporting code packages used by developers. This appears to be a technical/internal update with limited public details. - Likely aimed at reducing developer errors by making the code more precise about what data it expects. - Also updates supporting dependencies, which usually helps keep the development stack current.

• 
  Danus (@danusminimus) reported 37 minutes ago

  4/ I already posted about the research, but I wanted to share it again because of Google’s rationale. The issue was not just about a single repository. It was about downstream impact across agentic workflows in Google GitHub projects.

• 
  Julian Goldie SEO (@JulianGoldieSEO) reported 38 minutes ago

  There's a free tool that makes Claude read 92% less text and still fix the same bugs. It's called RTK. 68,000 GitHub stars. Here's how it works: → It sits between you and your AI agent like a filter → Your agent runs the same commands it always runs → RTK strips out the padding, headers, and fluff before Claude reads it → One test went from 373,000 characters down to 29,000 → Same output. Same quality. A fifth of the tokens That means your Claude subscription lasts 5x longer. Install takes one line. The delay is 14 milliseconds. Most people pay more for tokens. Smart people just stop wasting them. Want the SOP? DM me. 💬

• 
  Eric Ventor (@ericvtheg) reported 40 minutes ago

  @maxleiter I’m tagging Claude in slack and asking to it to review a github release issue. It then try’s to look at repos that match the service name, but my company uses a monorepo so it finds some irrelevant repo. From there it kicks off the session with only that irrelevant repo in scope so it’s useless.

• 
  Adib Hanna (@adibhanna) reported 45 minutes ago

  @draginol can you open a github issue with your thoughts on what the issues are?

• 
  Öhli (@Oehliii) reported 45 minutes ago

  @ParthJadhav8 hiya parth, do you have noop 8.1 by any chance - the team just took down their website & github, i’m on 8.0.1 sadly i couldnt update anymore :(

• 
  paydird (@paydird) reported 45 minutes ago

  One more point that matters more than the “automatic documentation” angle: OpenWiki is really addressing the context architecture problem for coding agents. A lot of teams keep stuffing architecture notes, APIs, conventions, and module relationships into AGENTS.md or CLAUDE.md. Once the repo grows, those files turn into massive context dumps that agents have to reread on every run. OpenWiki flips that model: Repo → Structured Wiki → On-demand Retrieval → Coding Agent It generates a separate repo wiki and leaves only a lightweight reference inside the agent instruction file. The agent pulls the pages it needs instead of loading the entire knowledge base every time. Also, it does not literally watch every code change in real time. It can run through a scheduled GitHub Action, inspect new commits and *** diff, then update the affected wiki pages. So the more accurate way to think about it is: not just a documentation generator, but a continuously maintained repository context layer for coding agents. That is probably the most interesting part of OpenWiki.

• 
  SecInterviewHub (@sec_hub93028) reported 48 minutes ago

  All internal code is built using a locked down CI/CD pipeline that only pulls from approved internal artifact repositories. Direct access to npm, PyPI, Maven Central, or GitHub is blocked. 
How do you poison a dependency to reach their build servers?

• 
  Rohan (@proxy_vector) reported 53 minutes ago

  @Saas_addy I'd switch, but the hard part wouldn't be *** hosting. It'd be replacing issues, actions, review culture, and all the tiny team habits that grew around GitHub.

• 
  Mfonobong Peter (@mfonPeeter) reported 57 minutes ago

  Two things recently: Set up my first GitHub Actions CI/CD pipeline. Nothing fancy, it just runs my pytest suite automatically on every push to main. But now no broken code gets merged without tests passing first.

• 
  Jarred Sumner (@jarredsumner) reported 57 minutes ago

  imo, GitHub needs to make it like 90% easier to review PRs. Left on read => the PR wasn’t clearly correct, the test didn’t reproduce fix the issue, the code was too complicated or too slow Or just a single tap to request a review with feedback templates

• 
  Tosin Olugbenga (@TosinOlugbenga) reported 57 minutes ago

  7 mistakes I keep finding in AI-generated SaaS applications. Not to dunk on AI. to show what "it works" hides until real users show up. 1/ No domain boundaries. Everything lives in one folder called services/. Users, billing, notifications, analytics — all coupled. AI generates features fast. It doesn't generate modules. 2/ No API versioning. /api/users today becomes /api/v2/users tomorrow and breaks every mobile client. Production APIs need a versioning strategy on day one, not after your first angry customer email. 3/ Synchronous chains. Create order → charge card → send email → update analytics → notify warehouse. All in one HTTP request. One slow step kills the whole response. 4/ Missing idempotency. User double-clicks "Pay." Two charges. Two orders. AI writes happy-path code. Production needs idempotency keys on every mutation. 5/ No rate limiting. Your /search endpoint queries the database on every keystroke. Works with 10 users. Dies with 10,000. 6/ Secrets in source code. Stripe keys in .env committed to GitHub. AI scaffolds fast — it doesn't audit your *** history. 7/ No observability. When something breaks at 2am, you have no logs, no traces, no metrics. Just "it's slow" from a founder. You can't fix what you can't see. AI is incredible for getting to v1. Architecture is what gets you to v10 without rewriting everything. If your AI-built MVP is gaining users and you're unsure the architecture will hold — that's exactly what I help founders solve.

• 
  Rahul Rana (@RahulDevFront) reported 57 minutes ago

  @ayesha_fatiima That was the huge problem earlier. GitHub solved that problem.