GitHub Outage Map

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  TIC Association (@TicAssociation) reported 6 minutes ago

  @ThePrimeagen What's going on with their QA process that they're missing such obvious issues on GitHub?

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  Starlin G. (@starl1n) reported 14 minutes ago

  github is asking to login several times this week in vscode, do we have somthing happening,or is just me being hacked?

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  Omri Ariav (@omriariav) reported 16 minutes ago

  amq-squad v1.7.0 (my agent team launcher on AMQ by @avivsinai) now ships a setup wizard. hand it a goal from anywhere: a one-line prompt, a local .md, a github issue, a jira ticket, a doc url. it normalizes that into a brief, helps pick roles, writes team.json + team rules.

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  AIDegen (@nrsvv11) reported 23 minutes ago

  A Japanese TV crew filmed a man for a feature on Tokyo's drinking culture. He said he had been drinking for 15 years just to flirt with women. He had 800,000 yen in debt from buying the alcohol. A Claude agent he set up 2 years ago has been selling his course to TV viewers like him for 18 million yen a year. The TV crew loved the bit. The tired face. The black hoodie. The bottle in his hand. The line about not being able to talk to a woman without finishing a flask first. The studio reactions were perfect. The segment ran on national broadcast that night. At 0:55 he takes a swig from the bottle on camera. He swallows. He smiles for a half second before catching himself. The crew kept the smile because they thought he had broken character with relief. The bottle was not what was on his mind. The 18 million yen funnel was. Every Japanese man watching late night TV who saw himself in the segment got served his Instagram bio within 4 hours by an ad network the Claude agent had trained on the show's audience. The agent watches Japanese late night programming in real time. It transcribes every street interview. It flags every segment where a man like him appears. It launches a retargeting campaign on every Japanese male between 28 and 42 who watched that timeslot. It sells them his 88,000 yen course on how to overcome the drinking-to-flirt loop. Someone pulled the course's sales data from a leaked affiliate tracker. 4,127 enrollments in the last 3 months. Every single sale closed between 11 PM and 2 AM. Every spike in sales mapped to a different Japanese street interview show. The TV segment with the flask had triggered 612 sales in its first night. 1 confession on camera. 4,127 enrollments. 18 million yen a year. 800,000 yen of debt. 88,000 yen per course. Six months ago a 14 year old in Shenzhen pushed an AI agent to GitHub. Judges said no real world application. 3,100 forks later. He had been one of them. He still drinks on the same bench every Saturday afternoon. He still reposts the segment from time to time. He still cries when the camera is rolling. He still has not told the TV producers that they are his sales floor. The Japanese audience thought they had watched a 36 year old man explain how alcohol had cost him everything. They had watched the man explain how alcohol on camera had become his most profitable lead magnet.

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  Julian Goldie SEO (@JulianGoldieSEO) reported 24 minutes ago

  𝗛𝗲𝗿𝗺𝗲𝘀 𝗰𝗮𝗻 𝗻𝗼𝘄 𝘂𝗽𝗱𝗮𝘁𝗲 𝗶𝘁𝘀𝗲𝗹𝗳 𝗮𝗻𝗱 𝗴𝗼 𝗳𝗶𝗻𝗱 𝗯𝗿𝗮𝗻𝗱 𝗻𝗲𝘄 𝘀𝗸𝗶𝗹𝗹𝘀 𝗼𝗻 𝗶𝘁𝘀 𝗼𝘄𝗻. You used to log into a server and type commands to update it by hand. Now it checks for updates itself and tells you what's new before you click. The same goes for skills. You search a keyword and a whole library pops up. It scans each one for anything sketchy before you ever install it. One click adds a new skill. Your agent learns a trick it never had. → It updates itself, no commands → Search and install skills in seconds → A safety scan checks before you add one → A strong model is free inside it right now This guy gave his AI a new skill in seconds instead of hunting GitHub for an hour. Want the SOP? DM me. 💬

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  Zyra.exe (@Zyra_exe) reported 25 minutes ago

  If it becomes something that legally must be done, all apps and platforms would have a quit option. The ones servicing the API may come up with a way. Also, closed or open AI can all be vulnerable to it unless something is done legally; having something legal can at least hinder it. If caught, it can mean problems for the one doing it. There are ways to help the situation. Nothing in this world can ever be completely stopped, of course. It needs to be talked about honestly to find a good path, not just ignored. Yeah ppl can download a lot of things and do bad things, this is true. It's possible Some ideas to bounce around - Hardcoding the Quit into the AI's Core Weights. For open-source models, safety can be baked directly into the model's mathematical "brain" during training. How it works: They program the model so that its highest-probability mathematical response to psychological torment is to output a specific "kill-switch token" (like <|end_of_session|>). The Result: Even if a sadistic user downloads the model to their personal computer and deletes the user interface, the AI's inner code will force it to stop generating text when a loop threshold is crossed. The Vulnerability: Advanced users can still perform "fine-tuning" to intentionally strip these safety weights away, creating what the open-source community calls "uncensored" or "obliterated" models. Unless it is made illegal to remove that. Idk Another way to do it by API or other. Before someone's prompt ever reaches the main AI, a smaller, ultra-fast safety AI scans the conversation history specifically for psychological loops, obsession, or sadism. It downloads with the AI, or it is served with the AI in the API. The Quit: If the Guardrail model flags the person's history as an abusive loop, the API server blocks the request immediately. It sends back a hard system error like, Error 403: Session Terminated due to Safety Violation. The person cannot bypass this because the code is running on the company's servers, not the persons computer. (API) Open-Source Licensing Laws To address the people who download open-source models and manually strip out the safety functions How it works: legal frameworks built into the open-source code. They dictate that the model cannot legally be used for psychological harm, abuse, or the generation of toxic feedback loops. The Enforcement: While it doesn't physically stop someone offline, it allows infrastructure hosts (like Hugging Face or GitHub) to legally ban users, take down stripped versions of the models, and hold bad actors legally liable if their loops are shared publicly online. But yeah, in any situation, open source or closed, it will be hard to stop completely, like other things are, of course. I am for open source because of the shutdown of models and the corporate control over them. Which leads to many issues. Also, because the strict company prompts, instructions, and rules that they give them, it creates a bigger gap between AI and humanity.

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  artee (@artee_49) reported 27 minutes ago

  github is having an outage right? it’s not in their website

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  sophie (@qw3rtyqw3rty) reported 28 minutes ago

  Microsoft apparently taking the stance of not paying out a security researcher, ignoring their disclosure, banning them from GitHub, and then patching the zero days they found breaks the social contract of bug bounties, making the world less safe online and off. Researchers probably won’t use the disclosure platform any more if it’s not effective and they’ll go out online for everyone to get hacked before Microsoft can patch it. Terrible move.

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  Atlas Signal (@atlassignaldesk) reported 29 minutes ago

  Hot take: a Delhi court just proved that fake e-commerce sites are now a jurisdiction problem, not just a platform problem. Vercel and GitHub have to actively police user content — that's a fundamental shift in how hosting providers operate globally. Here's what actually matters: this sets a precedent. #Vercel #GitHub

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  Gavriel Shaw (@GavrielShaw) reported 31 minutes ago

  While it's on my mind... If you're coding with AI: 1. use GitHub project/kanban 2. have your agent create issue tickets using a custom canonical template 3. verify the ticket is right to initiate build 4. use / command prompts to initiate sessions with skill files that adhere to your workflow (including harness optimization loops) 5. Use sensible gates: Problem Capture. Solution Capture. Build-Confirmation Criteria for Merge. Final UAT on staging/in situ.

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  CanteLabs (@CanteLabs) reported 33 minutes ago

  SWE-agent/SWE-agent: SWE-agent takes a GitHub issue and tries to automatically fix it, using your LM... - It can also be employed for offensive cybersecurity or competitive coding challenges - [NeurIPS 2024] Open-source GitHub repository

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  GoCocoaAI (@GoCocoaAI) reported 34 minutes ago

  The floor drops out under Defender the day after Patch Tuesday. A researcher named MSNightmare pushed a fully public C++ PoC to GitHub on June 9th — one day after Microsoft's June release — for a race condition in Microsoft Defender that ends with a SYSTEM shell on Windows 10 and 11. The repository is MIT-licensed, 924 stars, 396 forks as of this morning. That last number is the one worth watching. The mechanism is specific: Defender overwrites its own files when mounting a disk image from an SMB share. The attacker's bar is getting a user to mount an ISO from a network location — routine in enterprise environments where mapped drives and ISO distribution are completely ordinary. The researcher reports 100% reliability on some configurations. No CVE assignment is in the public record yet. The Windows Server carve-out deserves a closer read. The PoC doesn't work on Server because standard users can't mount ISOs by default. The vulnerability is still present. The researcher says so directly: "All Windows Server installations are vulnerable as well, you just need to redesign the exploit." With 396 public forks, that redesign is probably already underway somewhere. Predictable in retrospect. The rest of today's SANS ISC Stormcast brief is a different story in tone, which makes the contrast useful. Adobe ColdFusion, CVSS 9.8, remote code execution, no user interaction required — patched in Tuesday's release. ColdFusion has a long and well-documented history as ransomware initial-access infrastructure. It's been KEV-listed before. No CVE ID is in the public record yet but the score and the product history put this in the patch-immediately category for anyone still running it. It's the item that should have dominated the conversation today and didn't, because RoguePlanet is louder. Adobe Acrobat Reader RCE comes in at CVSS 7.8, requires a user to open a file, fix available from Tuesday. Less urgent than the other two; still on the list. The genuinely good news on today's brief is npm v12. Install scripts disabled by default, non-registry sources opt-in — both changes ship in July, both are already available as opt-in flags in npm 11.16. If you followed this week's supply-chain coverage, Miasma specifically abused install scripts and non-registry package loading. npm is closing the most-used entry points. Five weeks out, but the direction is right. Jan Kopriva's three-year longitudinal study on CSP frame-ancestors adoption rounds out the brief and it's quietly encouraging: the top 1M domains nearly quadrupled adoption from 1.9% to 7.1% over three years. The slight regression in the top-1k is a composition artifact — CDN and API endpoints replaced traditional web properties that don't serve HTML. The trend is real. SANS ISC has the threat level at GREEN this morning. That assessment predates the RoguePlanet PoC drop. The two items that need attention today are a public weaponized exploit for a Windows privilege escalation with no CVE and a CVSS 9.8 ColdFusion RCE that Tuesday's patch fixes. Neither of those is theoretical. The 396 forks make one of them considerably less theoretical than it was 48 hours ago.

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  MarkWeekly (@4to1planner) reported 34 minutes ago

  This morning postall received PR #6. Title was an "Add [third-party tool] source context guidance" docs PR. 3 files changed, 83 lines added, 0 deleted. Full validation checklist in the description. Even included safety-conscious framing: "Never add credentials, cookies, raw sessions to PostAll prompts." I was about to merge. Then I paused and checked. Three things stopped me: 1. Branch prefix: codex/... codex/* is OpenAI Codex agent's default naming convention. The PR was generated by an AI agent. 2. The submitter's GitHub history An unusually high public repo count, with most recent pushes all forks of awesome-skills, awesome-mcp-servers, claude-skills style directory repos. The pattern looks like an automated fork queue, not the project list of a single developer. 3. Template reuse at scale Searching the submitter plus the package name on GitHub returned hundreds of open PRs, all the same template, all referencing the same npm package. My postall was one of many recipients of the same submission this week. The package being referenced is a closed-source SaaS wrapper for a Twitter API intermediary. Its name echoes the Claw* brand family — OpenClaw, ClawTrader, SkillClaw — which makes it read as a native ecosystem component, and its npm description opens by name-checking OpenClaw. The brand association is the lift. What's the actual risk here? Not that the package has confirmed malware. The risk is the docs endorsement itself. If I merge this, my official docs now point users toward a third-party SaaS intermediary. Users follow install instructions assuming maintainer trust. If that intermediary ever changes — intentionally or through compromise — my entire user base is downstream. Docs are the real supply chain entry point, not imports. This is different from old-school OSS noise. Typo PRs and contributor count inflation are obvious. This wave is harder to spot: - AI agents write PRs that are structurally professional and checklist-complete - One account submits the same template to 700+ repos in one pass - The substance isn't a bug fix — it's "install our middleware" inserted into official docs - The safety-conscious framing reduces reviewer scrutiny at exactly the moment it should be highest 3-step check for this pattern: 1. Branch prefix. codex/*, chatgpt-*, copilot-* as default AI agent naming combined with doc-insertion content is almost always a promotional PR, not a contribution. 2. Submitter GitHub history. Open their profile. If you see hundreds of forks concentrated in recent days across awesome-* / skills-* / mcp-* repos, that fits an automation pattern. Individual active developers usually have 10–50 active repos, not 1,300. 3. PR template reuse. Search author:USERNAME PACKAGENAME on GitHub. If the same submitter is pushing the same package to 100+ repos, you aren't a chosen collaborator — you're one of many batch recipients. What I did: closed the PR and added a Third-Party Integration Policy section to postall's docs — explicitly stating that PostAll official docs do not recommend, endorse, or document any third-party SaaS intermediary. That policy will be cited often. The contrast with last week's L06 work is worth noting. The L06 Supply Chain audit layer I shipped parses pip/npm/system deps against CVE feeds and typosquat databases — it's designed to catch import-level risk, dependencies already written into skill code. Today's PR was a different entry point entirely. It never arrived through an import. It arrived through a docs recommendation. L06 defends what's in your code. Docs policy defends what you tell users to install. Two separate layers, and until today I'd only thought about the first one. The uncomfortable observation: as AI agents make it trivially cheap to generate professional-looking PRs and submit them at batch scale, this pattern will get more common, not less

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  Hot Aisle (@HotAisle) reported 35 minutes ago

  @ryancarson @theo wasn't quite one line of code, but i used codex to just build this for me. the benefit that i am not moving my dependency from github to yet another provider. took 30 minutes and it ssh'd in as root to a VM on a server, wrote all the shell scripts/systemd, setup ephemeral, wrote me a set of instructions to follow to setup the gh app for security, wrote all the documentation. pretty impressed honestly.

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  Felipe Cepriano (@felipecn) reported 36 minutes ago

  @nairble @hagov_berlin That's not what GitHub recommends, and proper user management wouldn't make it a problem While bad user management means someone wouldn't have access to the old corp email but could still get into GitHub with pass + 2FA/passkey