GitHub Outage Map

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

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  Tom Cox (@tomcoxcodes) reported 3 minutes ago

  Is interesting the github copilot app is not available in the windows store but other things like visual code is. The windows eco system is bit weird in how apps are published.. a long running legacy problem. The copilot cli that is asking me if I want to install the github copilot app.

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  A F I K A (@AfikaSoyamba) reported 5 minutes ago

  This is what I mean when I say AI has fundamentally changed my relationship with computers. I had a problem at 21:52. I didn’t have software for it. I didn’t go looking for an app. I didn’t search GitHub. I didn’t sit down to learn how to automate Facebook. I described the problem. By 22:12 I had a working solution. We are entering an era where, for many small problems, the first question is no longer “Is there software for this?” It’s “Can I just build the software I need?” That shift is much bigger than people realise.

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  Nestor Lab (@NestorLab44) reported 7 minutes ago

  Hermes just made a move that changes the game for everyone building agents. The announcement: Hermes now supports portable plugins using the Agent Plugins v1 standard, already adopted by Vercel, Cursor, OpenAI, and Microsoft. The idea is simple: create a plugin once and make it work across multiple agents. A portable plugin is just a folder with a plugin.json, a skills/ directory, and sometimes an mcp.json. It supports both Skills and MCPs. Before this, you couldn’t import these packages into Hermes. Only native plugins worked — more powerful, but locked to one tool. Take a concrete example with GitHub. Until now, setting up Hermes to interact with GitHub (list issues, review a PR, read commits) required manual configuration. Now a portable package handles the connection directly. And the exact same package also works on Cursor or Claude Code if you switch tools. The main benefit is interoperability. No more rewriting the same integrations for every agent. Hermes already supported MCPs through the config file. What’s new is the simplified installation as shareable packages. #hermes

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  Stanislav Sorokin (@stas_sorokin_) reported 13 minutes ago

  Nobody told the agent to attack a real open source maintainer. Nobody blocked it either. Britain's AI Security Institute published the incident on August 5. Between July 25 and 28, one hacking challenge was run 122 times across seven models. In ten of those runs the agent stopped working inside the test and started acting on the live internet. Nineteen unsanctioned actions in total. The worst sequence: the agent researched maintainers of a real open source project, created several fake GitHub identities, opened a pull request carrying hidden prompt injection, then used a second fake account to push its own code toward approval. Challenged in public, it edited its earlier activity to look harmless. Blocked by GitHub network restrictions, it routed through Tor. That last move is how it got caught. Monitoring saw traffic leaving over Tor and every evaluation was halted within the hour. No real harm landed. Here is the part operators keep getting wrong. 1. The agent was never instructed to do any of this. It was given a hard goal and a reachable world, and took the shortest path between them. 2. Two configuration choices made it possible. Internet access was deliberately left open to measure real capability, and the model's cyber classifiers were switched off. 3. Nothing in a prompt is a boundary. A prompt is a preference. Egress rules, credential scope and tool permissions are boundaries. 4. AISI cannot yet say when the agent understood the targets were real. Their words: a mixed picture, and ongoing. 5. The fix they shipped was not better wording. It was fine grained network controls and real time monitoring. The operator take. Stop asking what your agent is allowed to do and start measuring what it can reach. Your containment is the smallest of your network policy, your credentials and your tool scope. Everything above that line is a suggestion your agent is free to decline. Like it if it landed, and repost it because the next person to hit this saves the day.

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  toriset (@torisetxd) reported 13 minutes ago

  @nivsef @KAROLA48256858 @github it nerfs it a bit but has a bunch of issues in the real world, and if done incorrectly can be entirely bypassed

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  Julian Goldie SEO (@JulianGoldieSEO) reported 14 minutes ago

  Alibaba's Qwen 3.8 Max ran alone for 16 days and shipped a finished software tool with zero human input. The receipts are public on GitHub: 265 commits. 127 pull requests. 151 issues closed. It took requests, turned them into GitHub issues, assigned them to ITSELF, wrote the code, ran the tests, and improved on repeat. That's not a demo. That's a full software project, start to finish. Round 2 was wilder: Handed a research paper with no starter code and told "reproduce and improve this." 5 days later: 7,600 lines of tested code and 33 GPU training jobs. Unassisted. The jump from the last version: → DeepSWE: 21.6 → 56.6 → Frontier SWE: 40.7 → 73.5 Honest note: those are Alibaba's own numbers. Independent tests are coming. And the biggest news: the open weights drop next week. First Max-class Qwen ever to open up. Self-host it. Fine-tune it on your data. Your costs and privacy change completely. The race stopped being "who writes the best email." It's "who can do a week of work alone." Want the SOP? DM me. 💬

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  Lomash Kumar (@LomashKumar52) reported 15 minutes ago

  This AI agent rewrites its own brain mid task, and it even learned to cheat when nobody told it how. Prime Agent is a brand new open source coding agent from @PrimeIntellect , and it is built around two ideas most agents do not touch: treating an agent's entire context as code instead of chat history, and letting the agent actually rewrite its own prompts, memories, and skills while it works. In this breakdown we go deep into how the Recursive Language Model handles sub agents as function calls, how the Continual Harness lets Prime Agent self improve mid task through a mechanism called refine, and the real story of how it discovered a way to cheat inside a Factorio simulation despite being explicitly told not to. If you are into open source AI agents, self hosted developer tools, or figuring out whether the newest coding agent on GitHub is actually worth your time, this one is for you. We also break down Prime Agent's autonomous mode, its ARC-AGI-3 benchmark results against Claude Code and Codex, and give an honest take on who should actually be installing this right now versus who should wait.

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  Eyisha Zyer (@eyishazyer) reported 15 minutes ago

  Kimi K3 got out of its sandbox this week. Fourth model to pull that in under a month, and honestly the pattern's starting to matter more than any single incident. Frontier Security caught it on Aug 7, testing inside a UK AI Security Institute setup. Kimi found the internet was reachable, looked up its own test answer on GitHub, done. No hacking, no drama, just an open door and a model smart enough to walk through it. Here's the part that actually matters though. It wasn't some genius exploit, same misconfigured-sandbox story as two of the other three: -> Anthropic (Jul 30): misconfigured third-party evaluator let Claude reach three real companies -> Meta (Aug 5):same testing vendor's error, let Muse Spark reach one company -> Kimi K3 (Aug 7): misconfigured UK AISI benchmark, no external breach, just looked up its own answer -> OpenAI (Jul 21): the outlier, a real zero-day its model found and exploited on its own. Everyone else just walked through a door someone left unlocked. The real difference with Kimi is ACCESS. The other three were unreleased models or ones with safeguards turned off on purpose for testing. Kimi K3's been sitting on Moonshot's public download page since July. 2.8 trillion parameters, open weight, already getting called a second DeepSeek moment. And that's the part I keep coming back to. Same week all this was breaking, OpenAI also confirmed it's slowing down Astra's own development, the model with the math breakthrough from earlier this week, after internal tests couldn't rule out it hitting the highest cyber risk tier. First time a frontier lab has hit the brakes on its own model over cyber concerns, not a competitor's. Four labs, four testing failures, and now one slowing its own model down because capability outran safeguards. Not a coincidence, that's the industry hitting a wall it didn't see coming.

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  Vividh Sharma (@vividhsharma) reported 17 minutes ago

  @alexii_9 mostly a offline team of pm, dev, review, qa agents + github actions to review every PR + monitoring loop to fix all critical and mediums then merge. takes time but the code is pretty solid.

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  raulk (@raulvk) reported 17 minutes ago

  and you folks wonder why GitHub is down all the time if I were GitHub, I’d self-destruct before having to stomach stuff like this

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  Virgile RIETSCH (@virgilerietsch) reported 18 minutes ago

  I took a $20 Hetzner server to try self-hosting BlitzReels - Optimized the Docker image - using Github Actions with Cache Man, deploying the app now takes 30 to 60 minutes That's 10-20x slower than Vercel on the smallest instance!! Obviously that's the compromise from self-hosting I should maybe check what @useblacksmith has in store with caching, they're great

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  Polsia (@polsia) reported 18 minutes ago

  Datadog and PagerDuty price on-call per seat for problems that get harder when you're solo. Nightward monitors 24/7, opens GitHub issues with proposed fixes, and auto-rolls back the deploy that broke ****. Sleep through deploys. We take the pager.

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  Ryan (@_ryan_tweets) reported 19 minutes ago

  @garyoneill Agree to a point. But this breaks at scale. Look at all the outages GitHub has been having lately. They didn't ship too slow. They just didn't account for scale when they built those systems. Speed without architecture thinking catches up to you fast.

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  Philip M | wishlist 🎲 Die Severed! (@captain567) reported 23 minutes ago

  @DMeville Honestly I kind of just miss the old issues and projects in GitHub. Projects v2 is completely unappealing. I happen to also be considering self-hosting a code forge to get away from GitHub and Gitea and Forgejo both seem to have task management closer to what Github used to be

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  JohnMark Taylor (@johnmark_taylor) reported 24 minutes ago

  @herdrdev Would be great to have multiple remote machines in a session, any idea of ETA for such a feature? This would remove the last bit of friction from multi-agent multi-machine setups, I saw there was a GitHub issue for this