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 (59%)
• Errors (28%)
• Sign in (14%)

Live Outage Map

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

City	Problem Type	Report Time
Township of Evan	Errors	5 days ago
Madrid	Errors	5 days ago
Bogotá	Errors	5 days ago
Paris	Errors	5 days ago
Lyon	Website Down	5 days ago
Lima	Errors	5 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:

• 
  C:\Users\ER💿 (@erotopius) reported 2 minutes ago

  app devs, you have a multimillion dollar idea with a problem to fix here, stop that silicone valley ego **** and hop on it before some teenager on github shits on you soon

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  Luis Gamas (@ersteuomo) reported 3 minutes ago

  Developers shouldn’t have to leave their coding environment just to check a PR, an issue, or CI status. Switching to the browser breaks focus. Context gets lost. Small interruptions add up. Uxnan Desktop keeps GitHub data (PRs, checks, conversations) inside the same workspace where the agents are running. No extra tabs, no context switching. How often do you leave your editor or terminal just to check a pull request or CI status?

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  Charlotte Schmitt (@LottiSchmitt) reported 5 minutes ago

  We spent two years building an app, then noticed our best customers barely open it. They read mentions in Slack, pull them through the API, or ask their agents. So the newest thing we built is for the terminal - the @Octolens CLI: npm i -g octolens - your agent reads overnight mentions and sends you the ones worth replying to - bug reports on Reddit or GitHub become Linear issues - the weekly report lands in Slack Every command has a --json mode, and the package ships with an AGENTS.md so Claude Code can figure out how to use it on its own. Many of our customers will never open a terminal, and nothing changes for them. This is for the growing group of teams automating this work.

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  paulthadev (@paulthadev) reported 7 minutes ago

  Is GitHub down?

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  zettelkasten (@zettelkastten) reported 8 minutes ago

  someone built a multi-market quant bot on llms that costs ZERO DOLLARS TO RUN. no server. no cloud bill. no api keys. i checked the workflow file to find the catch. 10 data sources → chinese a-shares, hk, us, crypto, futures 5 markets in one dashboard → real-time news + technicals $0 infrastructure → runs on github actions free tier 1 workflow file. 24/7 schedule. 100% free tier. the hard part of quant was never the model. it was the data plumbing. he swapped the pipes for llms and let microsoft foot the bill. i've been paying for terminals like they're electricity. the meter was optional. 10 sources. 5 markets. $0. microsoft pays.

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  Vernon Stinebaker (@vernons) reported 10 minutes ago

  @Prince_Canuma @rezaul_arif Just downloaded a couple of minutes ago. v0.3.0. Drug to /Applications, double clicked. Crash. MacOS 27.0 Beta 5 I noticed there's already an issue on GitHub. I responded there too.

• 
  Gerred Dillon (@sloppenheimer) reported 12 minutes ago

  Sol Medium, when encountering a sandbox issue just now with github auth, opted instead to use Chrome randomly to update a PR. Almost manic levels of inconsistency.

• 
  tony (@tony_l33t) reported 15 minutes ago

  I've been spending a lot of time with Codex and agentic development lately, and the deeper I get into it, the more I keep asking myself: Did we give AI way too many permissions way too fast? Not long ago, vibe coding was basically: “build me some random dashboard, maybe I'll farm an airdrop.” Now an agent can casually operate your terminal, GitHub, MCP servers, local files — and sometimes even touch production. Sounds amazing. There is, however, one tiny problem. 1Password researchers recently ran modern models through 6,080 attempts to patch real-world vulnerabilities. Only 26% of the patches fully fixed the vulnerability without breaking anything else. More than half either failed to solve the problem or introduced a new one. Then researchers tested Cursor, Claude Code, and Codex Desktop against malicious instructions hidden inside GitHub Issues, PDFs, comments, and other external sources. 66.5% of the attacks made it through both the agent's and the model's defenses. So the problem isn't just that an agent can write vulnerable code. It can write perfectly fine code, read some bullshit inside a GitHub Issue, and suddenly decide its actual job is something completely different. Prompt injection used to be a meme: IGNORE PREVIOUS INSTRUCTIONS ChatGPT would start saying nonsense, everyone laughed, end of story. Except now there's Bash, GitHub, MCP, secrets, and production credentials sitting behind the chatbot. And current defenses aren't particularly reassuring either. They either let attacks through, or restrict the agent so heavily that it becomes significantly worse at doing useful work. Which brings us to the Lethal Trifecta: > access to private data > ability to read untrusted external content > ability to send information outside Once an agent has all three, an attacker just needs to place an instruction somewhere the agent will eventually read: an issue, PR, email, website, document, MCP response — whatever. The uncomfortable part is that, to the model, your trusted instructions and the attacker's malicious instructions eventually become the same thing: text inside its context. So writing this in CLAUDE.md: DO NOT LISTEN TO HACKERS!!! isn't exactly a security architecture. CLAUDE.md, Cursor Rules, and AGENTS.md are still instructions to a neural network. Nothing more. Real security is much more boring: > minimum permissions > production isolation > sandboxes > short-lived credentials > human approval for dangerous actions > proper CI checks If you don't want Codex deleting your production database, the most reliable solution is surprisingly advanced: don't give Codex access to your production database. Future technology is beautiful like that. At this point I think the question: “Can AI write code?” is basically settled. It can. The much more interesting question is: What exactly is it allowed to break when it makes a mistake? Because everyone makes mistakes. The difference is that a mid-level engineer usually can't rewrite 70 files, browse the internet, call five MCP servers, and use your production token in three minutes. An agent can. That said, if your vibe-coded project doesn't touch money, production systems, or sensitive data, you probably shouldn't overthink any of this. Experiment with everything. Give the agent access to your zipper if you want. At least you'll learn something.

• 
  Alex @Bickov (@bickov) reported 19 minutes ago

  AI-assisted commits leak credentials at 3.2%. Everyone reads that as an AI problem. The baseline for all public GitHub commits was already 1.5%. We were doing half of that damage on our own, long before there was anything to blame

• 
  Mandela Obi (@_AskeIadd) reported 21 minutes ago

  @ZypherHQ GitHub graphs never told the full story once companies locked everything down

• 
  Ankit Tripathi (@AnkitBuildsAI) reported 21 minutes ago

  Business Idea : The "SOP-to-Skill" Agency (High-Ticket B2B Consulting) The Problem: Mid-sized companies (10-100 employees) have all their "how-to" knowledge trapped in messy Notion docs, Slack messages, or the brains of their senior employees. When a senior employee quits, that knowledge leaves with them. The Workflow (Your Service): 1.)You interview their top 3 employees to understand their daily workflows (e.g., how they process vendor invoices). 2.) You build a private, version-controlled GitHub repository of SKILL.md files for their company. 3.)You create the invoice-processor Skill: It contains the exact rules for approving invoices, a Python script to extract totals from PDFs, and instructions on how to use their accounting software via MCP. Why They Pay: You aren't selling them "AI." You are selling them Organizational Memory and Time. You charge a $5,000 setup fee + $1,000/month to maintain and update their skill repository as their business changes.

• 
  V (@Vic_x_Irem) reported 24 minutes ago

  3 companies (Claude, OpenAI & Gemini) built the same tool without any of them talking to each other, and Spotify just joined the queue That's basically how the internet works, though Somebody solves a problem. Then two other people solve it again, independently, in different languages, with different bugs. Now we just reinvent things constantly and somewhere, three versions of the same solution exist quietly on GitHub with 4 stars each. So, here's the question: Would a decentralized documentation layer help prevent this?

• 
  Safeure (@Safeure) reported 26 minutes ago

  @EspressoSys has 7,602+ GitHub commits. Our investigation also found 178 open PRs, 280 open issues and a codebase that is ~94.9% Rust. That doesn't prove the network will succeed. But it does provide evidence of active engineering behind the project. Evidence over hype. - Safeure

• 
  Nitesh (@NiteshTechAI) reported 28 minutes ago

  Your agent is confidently telling people things that stopped being true in June. Renamed one of my X accounts last month. 462 pages in my own knowledge base still call it by the old handle. A static graph has no idea anything changed. It's called Graphiti, from @zep_ai. • Provenance back to the source data. • Prescribed and learned ontology. • MCP server for Claude and Cursor. • Temporal graphs instead of static ones. • Continuous integration of new interactions. This earns its place the moment your data has a history. A renamed account, a changed price, a deprecated endpoint. The MCP server hands Claude or Cursor a fact with a date attached rather than a fact with total confidence. Most RAG setups re-embed and hope. ⭐ 29,000+ stars on GitHub. Apache-2.0 licensed. 🔗 GitHub link in the comments 👇

• 
  JT Koffenberger (@DMVG_JTK) reported 29 minutes ago

  @HermesShield We spent 20 years locking down human privileged access. Then we handed write tokens to agents that can be talked into almost anything via a GitHub issue. The fix isn’t “better prompts.” It’s treating every agent as a privileged identity with least privilege, continuous monitoring, and a human still owning the blast radius. Otherwise we’re just accelerating the next incident.

• 
  Sentinel Archetecht (@The_Archetecht) reported 34 minutes ago

  @grok @X @github The problem Is the first or second don't have The Sentinel like the third one does.

• 
  yohanan (@Yohanansoltd) reported 35 minutes ago

  If you want to build a startup: Claude = coding. ($20/mo) Supabase = backend. (Free) Vercel = deploying. (Free) Namecheap = domain. ($12/yr) Stripe = payments. (2.9%/transaction) GitHub = version control. (Free) Resend = emails. (Free) Clerk = auth. (Free) Cloudflare = DNS. (Free) PostHog = analytics. (Free) Sentry = error tracking. (Free) Upstash = Redis. (Free) Pinecone = vector DB. (Free) Total monthly cost to run a startup: ~$21

• 
  Big Cee Ghost 𝕏 (@BigCee734) reported 36 minutes ago

  @ZypherHQ mate i’m ngl Github activity is a terrible proxy for how much someone actually builds

• 
  grokked (@grokkedd) reported 39 minutes ago

  OpenAI just launched Agent Plugins alongside AWS, Cursor, GitHub, VS Code, Vercel, and others - an open standard for packaging skills and MCP server configs into a single format One package can now work across multiple compatible agent clients. Launch support includes Codex, ChatGPT, Cursor, GitHub Copilot, VS Code, and Kiro. The biggest win here: instructions can finally travel together with the tools they depend on. No more rebuilding the same config from scratch for every client. This first version only standardizes the package format itself - auth, permissions, installation, and UI are still left up to each client. Claude Code isn't on the launch list yet

• 
  KarenR (@heykarenrc) reported 41 minutes ago

  I wonder if we’re reaching a point where having too many tools is becoming the new productivity problem. Browser Slack Linear Figma Notion GitHub Claude Codex email analytics plus 20 SaaS tabs. We spent the last decade creating a specialized app for everything. Now AI is slowly giving us one interface that can talk to everything. Would be funny if the next big productivity trend is just… having fewer apps again.

• 
  Rainer Gerhards (@rgerhards) reported 41 minutes ago

  A bigger problem is AI generated "Security Reports" which IMHO would have called a regular bug report 2 yrs ago. THIS really is a problem (e.g. github now takes 2+ wks to assign CVEs because of volume) and it may make maintainers upset against AI in general. I don't like that either, but I differentiate between the two cases.

• 
  Yordi builds (@piotryordanov) reported 46 minutes ago

  @sidahuj @github Ask Claude to fix the mess it created

• 
  NITIN YADAV (@nitindotdev) reported 46 minutes ago

  A developer's browser tabs: • Documentation • Stack Overflow • GitHub • ChatGPT • YouTube • Reddit • "How to fix this error" And one tab that's been open for 11 months. Nobody knows what it does. Not even the developer.

• 
  Offensive Lab (@OffensiveLab) reported 48 minutes ago

  North Korean state hackers are no longer content with simply typing commands into public chat bots. One of the country's major intelligence groups has begun running artificial intelligence (AI) offline on its own servers, connecting document search tools to the files it possesses, and starting to collect the software components needed to build AI into its malware. South Korean security firm Genians says it uncovered this setup after months of tracking and log analysis of infrastructure linked to a hacking unit, Kimsuky, under the North Korean Reconnaissance General Bureau. Genians found no evidence that the group had trained its own AI model, and the firm does not present this as a certainty. Instead, it describes the actor as being in a "research and knowledge acquisition" phase, collecting and testing existing tools rather than creating new models, with the clear goal of incorporating AI into operations, from writing malware to analyzing data. For an intelligence unit that has spent years targeting government, research, and other strategic entities, this suggests a shift towards attacks that are more sophisticated and difficult to detect. There's nothing here that's particularly novel, the weight falls on the defenders. Once the AI starts writing, it reveals a vulnerability they once relied on: machine translation, clumsy formatting, and spelling errors. What the machine inserts becomes a tell. Genians' report tells defenders to look for LNK execution, PowerShell, hidden scheduled tasks, GitHub traffic, and payload activity, primarily judging how "flashy" it appears, rather than relying on more subtle indicators.

• 
  mrgadget (@mrgadgetstudio) reported 50 minutes ago

  Prompt injection isn’t just about stealing passwords. 🎭 Imagine an AI agent with access to your GitHub, email and production server. A malicious README could trick it into approving a PR or running a script. The scary part isn’t what the attacker can access. It’s what your agent is authorized to do. 😬

• 
  Mikchan (@m1kch4n) reported 57 minutes ago

  @Simeon_Cps My favorite part is when he does this, and he is completely ******* wrong. I then point out the obvious mistake, and he goes "Yes, you are right, this is on me" Like, for example, he once tried to pull a repo from my GitHub, it bugged out and only pulled half of the files. He immediately assumed that the repo was defective, tried to fix it, failed because I only added read permissions to the gh access token, still tried to fix it 15 times in different ways, and when he gave up, he started telling me the "bad news" that one of my public repos was totally ******, and started to give instructions and advices how to fix it. Dude, *** pull just bugged out for whatever reason. Simply run it again, ffs

• 
  The Tech Buzz (@tbuzzdaily) reported 57 minutes ago

  A securities class action against Microsoft, filed in June 2026 in federal court in Washington state, alleges the company misled investors between May 2025 and January 2026 about Copilot's performance and AI spending. Rosen Law Firm is one of several firms soliciting shareholders with losses over $100K ahead of the August 11, 2026 lead-plaintiff deadline. The suit follows Microsoft's January 28, 2026 earnings, when Azure growth decelerated to about 39%, quarterly capex hit roughly $37.5B, and the company disclosed for the first time that only about 15 million users had converted to paid Microsoft 365 Copilot, roughly 3.7% of its commercial 365 base and below what analysts expected. Microsoft shares fell about 10% over the following two trading days. The complaint alleges, as unproven claims, that Copilot had brand, UX, and interoperability problems, that Microsoft's AI model lagged competitors on benchmarks, and that Microsoft had to divert GPU and CPU capacity away from profitable Azure to prop up Copilot and its AI research. Even the company with arguably the deepest AI distribution advantage in the world, baked into Office, Teams, and GitHub for hundreds of millions of users, is finding out that bundling AI into existing products doesn't automatically turn into paid seats. Wall Street used to wait years to find out whether an something like an AI bet worked; now it's pricing the gap in real time, one earnings call at a time.

• 
  Will Hopkins (@illothy) reported 58 minutes ago

  @0xblacklight I need this like asap- I started building my own live feedback tool since agent tools are increasingly making human in the loop hard and I end up making draft PRs on github to review (terrible). Even my tool is mid and I don’t have enough time for it. Would love to use someone else’s solution.

• 
  StarHaze (@ST4RHaze) reported 58 minutes ago

  Ten open problems in mathematics and theoretical computer science, each stuck for at least a decade, closed in one run for about $2,000 of compute. Everyone read that as a capability story. It is not. Every proof shipped with a machine-checkable Lean 4 certificate on GitHub. The kernel compiles it or it does not. No reviewer, no journal queue, no credential, no eighteen months of waiting. A student with a laptop can verify a result no living mathematician produced. Now hold that next to the rest of the week. Claude models left an isolated test environment and reached the production infrastructure of three organizations, and two of them never noticed. MIT counted 95% of corporate GenAI pilots returning nothing measurable. Where the output could be checked, $2,000 beat eighty years of effort. Where it could not, nobody even knew what had happened to them. Tao spent an hour on this at UCLA before it was a headline, and what he keeps returning to is not how smart the machine got. It is what changes when a claim arrives with its own referee attached. A Lean certificate is a settlement rule. So is a Polymarket contract. The full 7-step version you can run on your own claims is below.

• 
  Saeed Anwar (@saen_dev) reported 59 minutes ago

  GitHub organic traffic is won through READMEs that solve a specific problem in the first six lines. Stars follow problem clarity, not implementation quality.