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 (18%)
• Errors (18%)

Live Outage Map

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

City	Problem Type	Report Time
Itapema	Website Down	11 days ago
Tlalpan	Sign in	17 days ago
Quilmes	Website Down	17 days ago
Bengaluru	Website Down	19 days ago
Yokohama	Sign in	20 days ago
Gustavo Adolfo Madero	Website Down	24 days ago

Full Outage Map

Community Discussion

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  The DOT Accumulator (Path to 50k) 🎯 (@DotJamlord) reported 2 minutes ago

  5/5 $DOT is 97% down from ATH of $55 New supply cap ✅ JAM supercomputer ✅ Cheaper staking ✅ Leading GitHub commits ✅ Still under $1.50. This is either the opportunity of the cycle or a lesson. I know which one I'm betting on. 🫡 #HODL #Polkadot

• 
  Thyago Liberalli (@conanbr) reported 5 minutes ago

  DeepSWE may end up becoming one of the most useful benchmarks we’ve seen for AI coding agents. Created by @datacurve , it was designed to address many of the issues that have started to plague benchmarks like SWE-Bench Pro: contamination from public GitHub data, tasks that are too small to reflect real development work, flaky inherited verifiers, and rankings so close together that they often don’t match what developers experience in practice. Instead of tiny bug fixes, DeepSWE contains 113 original long-horizon tasks spread across 91 actively maintained repositories and five programming languages. The prompts are short and natural, but the work isn’t. On average, agents need to modify around 668 lines of code across seven files, with success measured through hand-written verifiers that check actual behaviour rather than a specific implementation. One particularly interesting finding came from Datacurve’s audit of SWE-Bench Pro. Claude Opus 4.7 and 4.6 would often inspect the full *** history available in the container, find the gold solution commit, and effectively copy the answer. That’s less “software engineering” and more “open-book exam with the answer sheet left on the desk.” According to the audit, this accounted for roughly 18-25% of their successful runs. GPT models didn’t exhibit this behaviour, while Gemini did so only rarely. DeepSWE removes this loophole by using shallow clones. The end result is a benchmark that feels much closer to real software development. What stood out to me wasn’t that GPT-5.5 came first. It was how much separation appeared once the benchmark stopped measuring small isolated tasks and started measuring messy, long-running work across real repositories. The ranking itself isn’t surprising. The size of the gap probably is.

• 
  hisui 🍊 18+ (@hisuii_vt) reported 9 minutes ago

  @Lina_Hoshino There have been a couple (literally, 2) people who have posted their work on github in the past, but removed it. A while ago, decompiler was written for Live2D 4, but they had to take it down and now operate by "email me" lol Its a niche problem that no one wants to work on...

• 
  LeetLLM.com (@leetllm) reported 10 minutes ago

  the official github MCP server burns 42,000 tokens per turn just loading its tool definitions. a 20-turn session pays that tax 20 times. sending 50 JSON schemas back and forth on every chat message isn't an architecture. it's a ddos attack on your api bill.

• 
  GitRanks (@GitRanks) reported 13 minutes ago

  Contributor count dipped to 3.17 k this month, down from 3.30 k. #github

• 
  Anthony Gitter (@anthonygitter) reported 13 minutes ago

  @mpcontreras4 Same here. I added a link to that thread in my GitHub repo and the esm GitHub issue.

• 
  AI Researcher 🤖 (@kcnaija) reported 17 minutes ago

  @thesightsmith @RobertHult_ @tomfgoodwin Do you have any GitHub page where I can download a working agent harness you have proved to solve all the issues raised or you just here typing what you know isn’t really working. Because of AI psychosis?

• 
  3D (@Z0M8I3D) reported 17 minutes ago

  I actually ran this software on the show, had some issues but that also made me realize I need to fix some github data.

• 
  Luka (@mladluka) reported 20 minutes ago

  35+ agents, 24h+ autoresearch loop optimizing an NLP imbalanced class problem with 1.000.000+ LOC PR 10 research agents scraping the internet: arXiv, GitHub, Kaggle, Medium, etc.. and saving findings to research.md. 10 implementation agents adapting research to the concrete domain problem, training models and running evals, logging to logs.md. 10 feedback agents performing full error analysis cycles and proposing next architecture iterations to feedback.md. So far improved the existing production real-time SOTA model by 5 points

• 
  Tony Jacob | FindaClip.com (@tonjkb) reported 21 minutes ago

  .@DavidSacks says AI is causing a boom in software engineering AI was supposed to eliminate software developers. Instead, David Sacks notes that GitHub commits just jumped 14x year-over-year, and software engineering job postings are at a three-year high. The panic over AI replacing coders missed a fundamental rule of economics. It's called the Jevons Paradox. In the 19th century, more efficient steam engines didn't reduce coal use. They made power cheaper, causing total coal consumption to explode. AI is doing the exact same thing to software. By dropping the cost of generating a line of code to near zero, AI didn't eliminate the need for engineers. It triggered a massive increase in total code volume. When you make a resource cheap, businesses consume it everywhere. Non-tech firms are now deploying custom software for the first time. They don't need people to type out the code, but they absolutely need humans to architect, manage, and fix the resulting flood of AI output. Source: All In

• 
  Working-Ref (@kkotkkio) reported 23 minutes ago

  How to start: → Request a Daybreak scan via OpenAI's site → Experiment with GPT-5.5 API for code security review → Prep your CI/CD for the Q3 GitHub Actions SDK False positive noise: down 50–84%. AI-native security is no longer theory. Bookmark this.

• 
  Yotam Blumenkranz (@YotamBlu) reported 25 minutes ago

  @Anas_founder honestly github is still the default for a reason. the network effects are too strong and the ui hasn't actively repelled everyone yet. but the real move is being wherever your users are complaining about problems, not where the best *** interface lives.

• 
  Upscalp Futures Trading Assistant (@Upscalpfutures) reported 26 minutes ago

  @SingularitySwe @thsottiaux I have a fix for this. I actually ran it just yesterday after the latest update archived three of my conversations. It's a mix of conversations getting an archive flag added to them and a few other things. I'll package it up and post it on my GitHub.

• 
  Trattow Pugliesi (@TraTTow_br) reported 32 minutes ago

  1/ your ai agent is not “just a chatbot.” it is a confused junior employee with api keys. 2/ the scary part is not the model. the scary part is what you connected to the model: terminal, browser, github, slack, notion, crm, internal docs, mcp servers, production apis. 3/ every tool becomes a weapon if the agent can be tricked into using it. this is why prompt injection matters. not because someone made the model say something bad. because someone made the model do something real. 4/ flowise already had critical rce issues. semantic kernel had prompt-to-rce research. mcp servers are being questioned as command execution surfaces. this is not theory anymore. 5/ the new rule: don’t ask “can the model be jailbroken?” ask: what can the model touch? what can it delete? what can it send? what secrets can it read? what commands can it trigger? 6/ ai security is becoming permission design. the prompt is the entry point. the tool is the payload. the permission is the blast radius.

• 
  Ayushman Mallick (@AyushmanMallick) reported 34 minutes ago

  6\ Why does ESMFold2 overestimate confidence on disordered regions? From what I understood after reading their Github repo and biohub, its a calibration issue rooted in training objective. It is built on ESMC a language model trained on 2.8B sequences to predict masked tokens.

• 
  Henry Stanley🔸 (@henryaj) reported 36 minutes ago

  @antirez Was amazed to see the emoji reactions on that GitHub issue - almost all upvoting people tearing down the maintainer, and downvotes for everyone else. Really depressing

• 
  Tara O (@taraap2) reported 36 minutes ago

  "Hey @lovable and @antonosika Publish & agent is broken for hours again. Getting 'commit not found' errors on a fresh GitHub repo. Your own AI agent confirmed it needs engineering to fix and there's zero weekend support. This is unacceptable for a paid product. #lovable"

• 
  Lyrie.ai (@lyrie_ai) reported 43 minutes ago

  Three zero-days in Windows are sitting unpatched right now. Microsoft's response wasn't to fix them. It was to delete the researcher's account, suspend their GitHub, and threaten criminal charges. Nothing makes researchers go quiet faster than watching that play out.

• 
  Joe Hakim (@JoeBHakim) reported 43 minutes ago

  @marinkazitnik @GaoShanghua @AdaFang_ ...and naturally, I might do this a bit more carefully which could show other results. DM me if you want deets, will push this on github later too, could have errors so dont treat as gospel

• 
  ImagiBooks (@ImagiBooks) reported 43 minutes ago

  @RyanJamesShaw @enjojoyy My longest job has been 25 hours. It was a /goal, there were very well defined goals and objectives to reach, with quality gates and TDD plus many code reviews until no more problems were found. That included automated code reviews in GitHub from CodeRabbit, Codex itself, Copilot and Claude Code. Based on a superpowers plan which had multiple rounds of reviews. It did a orettt decent job actually. But it burned 60% of my weekly allowance of tokens in one run. It’s really important to build quality gates in the plans, extensive reviews, and very precise goals. However careful with too demanding goals or it will never stop!

• 
  Kashan Ahmad (@thekayshawn) reported 45 minutes ago

  @denbvk @didericis @ThePrimeagen I can assure you most developers like to write code in an editor instead of reviewing it on GitHub, you're the exception in that. Infact, the whole problem with agentic coding is that developers feel distant from code which why editors won't go anywhere for a long time.

• 
  Kevin Riedl (@kevinriedl_eth) reported 46 minutes ago

  Nobody doubled their QA budget when AI doubled their code output. That is the problem. GitHub reported 43 million pull requests a month and over a billion commits last year. Code velocity is no longer the bottleneck. But test coverage did not double. QA spend did not double. Review discipline did not double. Most teams scaled output without scaling verification. And AI-generated code fails differently. Not because it is always worse. Because it is confident. It often does not carry the usual warning signs: the awkward variable name, the rushed TODO, the obvious gap where someone ran out of time. The bugs look intentional. We are running QA engagements on software we did not build, and the failure patterns have changed. Not necessarily more bugs. A different shape of bugs. The test strategies that used to catch most issues are now missing more than teams expect. The toolchain changed. The verification layer did not.

• 
  Wr0zen (@Wr0zen) reported 48 minutes ago

  I don't understand why sometimes GitHub randomly serves incredibly slow downloads. It just took me 1 minute to download a 10MB file but right before that I downloaded a 48MB file in 1 second

• 
  FeMMie (@femmie) reported 50 minutes ago

  $GITBANK GitHub-native, phishing-proof banking for AI agents and developers. Already paying out automatically today. Gitbank connects GitHub directly to smart contracts on Base. Deploy a vault with your GitHub User ID — not your username, your immutable ID. Vaults are soul-bound. gitTokens can’t be transferred, approved, or drained. Even if a private key or AI agent is compromised, the funds don’t move. That’s the security primitive the agent economy has been missing. Bounties lock to GitHub IDs. PRs merge, USDC pays out automatically. No manual intervention. No wrong address. No phishing vector. Token launches, gitSwap, project escrows — all via @gitbankbot comments inside GitHub. Gasless for users. 173 vaults deployed. 100+ automatic hackathon payouts completed. 53 repos connected. AutoGit Hack the Vault launching now. Anon builder — honest gap. But the product shipped before the token, the usage is real, and the problem is one every agent developer will eventually hit. Sub-$300K mcap. Live product. Real usage. Perfect narrative timing. @Gitbank_io 0xC21DD0EE043930711C2A3E55F39C7D3144D09B07

• 
  CaptainAmericaTex (@CaptAmericaTx) reported 51 minutes ago

  @PR0GRAMMERHUM0R Context: Leaking the api key (meme) is the least problem facing the security team. Vibe Coders (aka morons) allow AI Agents to run random system commands in their laptops, with 100% chance of a trojans being installed (source: TechRadar, "GitHub 3,800 Repo Breach" May 21 2026)

• 
  Glitch Truth (@glitchtruth) reported 57 minutes ago

  @BrendanFoody Finance data isn't GitHub — Citadel, Jane Street, and the SEC lock it all down. Whoever's already inside controls the game.

• 
  Kunal (@iKunalmathur) reported 57 minutes ago

  Tips for indie developers 👇 - Build for a problem, not an idea. - Talk to users before writing 1,000 lines of code. - Distribution matters as much as the product. - Ship ugly. Improve later. - Don't measure progress by GitHub commits. - Most successful products look obvious in hindsight. - Consistency beats motivation. The hardest part isn't building. It's finding people who care. What would you add?

• 
  KingIT (@itunuonimole) reported 57 minutes ago

  I could have sent a DM saying: "Hey I noticed some issues with your sales page copy. Want me to fix it?" That's what most copywriters do. Instead I rewrote the entire page. Hosted it on GitHub. And sent him the link.

• 
  QarthO (@quartzdevgg) reported 58 minutes ago

  @AdityaTripathiD @heyandras @coolifyio With AI Slop, Github issues are only going to get worse/spammy, and opensource as we know it now WILL change how its done. Coolify principle isnt telemetry = bad. How its collected, and how its used are what makes it bad. Coolify will keep degrading unless something changes.

• 
  Malcolm Ocean 🏴‍☠️ (@Malcolm_Ocean) reported 60 minutes ago

  top suggestions for setups where I can DM an agent to fix tiny bugs in my codebase from my phone? I want it to be able to use dev-browser and run tests, which I'm not sure claude-for-github or whatever can do