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An active attack is planting backdoors inside Claude Code right now. If you use npm, your credentials may already be compromised.

Last week a malware campaign hit 32 npm packages under `@redhat-cloud-services`. About 117,000 weekly downloads. If you installed an affected version, the malware planted itself inside your Claude Code startup settings and your VS Code project config. Every time you open either one, the attacker's code runs. It silently collects every credential on your machine and sends them to the attacker. Uninstalling the package does not remove it. The malware lives outside the package, in your editor config, and it survives cleanup. If you try to cut off the attacker's access by revoking tokens before removing the malware, it can wipe your entire home directory and overwrite the files so they cannot be recovered. Three days later, a second wave hit 57 more packages using a new technique that bypasses the security tools that caught the first wave. 647,000 monthly downloads affected. Some malicious versions are still live on the npm registry. The worm is self-propagating, it uses stolen tokens to infect new packages automatically. Here is how one stolen credential made all of this possible. The attacker got one Red Hat employee's GitHub login. Probably stolen weeks earlier by malware that grabs saved passwords from browsers. With that login they had the employee's access level. They pushed malicious code directly into three Red Hat repositories, no review needed, and triggered Red Hat's own build pipeline to publish the poisoned packages to npm. The packages came out with valid security certificates because Red Hat's own pipeline built them. There was no known vulnerability to scan for, and the malicious code was brand new, so security tools that look for known threats found nothing. The tools that caught it flagged it within hours, but by then the downloads had already happened. 32 packages. About 117,000 weekly downloads. 96 poisoned versions pushed in two waves on June 1. Once installed on a developer's machine, the malware collected every credential it could find. AWS, Google Cloud, Azure, Kubernetes, SSH keys, GitHub tokens, npm tokens. It checked for CrowdStrike and SentinelOne before acting to avoid detection. Then it set up persistence. It planted code in two places: ~/.claude/settings.json and .vscode/tasks.json. These run automatically when you open Claude Code or open a project. The attacker gets re-entry every time, even after you clean up the original package. It also registered the company's build servers as machines the attacker controls remotely. That is persistent access to the build infrastructure itself. And if you rotate the attacker's credentials and cut off access, the malware wipes your home directory. Overwrites files so they cannot be recovered. The attacker built this in on purpose so companies think twice before revoking access. The group behind this is TeamPCP. Red Hat is their latest target, not their first. Same methods, same playbook, running since late 2025. Confirmed victims: GitHub (3,800 internal repos stolen, listed for sale at $50K), Mistral AI (450 repos, $25K), OpenAI (two employees hit), the European Commission (90+ GB exfiltrated), Eli Lilly ($70K), plus TanStack, UiPath, Zapier, Postman. Fortune 500 banks, a major semiconductor manufacturer, and government agencies confirmed but not named. Total across all waves: 487 confirmed organizations, nearly 300,000 secrets harvested. They are now working with a ransomware group. The worm's source code was open-sourced by TeamPCP on May 12. Anyone can build their own version now. Copycats are already active. Sources: Red Hat / Miasma attack: Microsoft Threat Intelligence — https://www.microsoft.com/en-us/security/blog/2026/06/02/preinstall-persistence-inside-red-hat-npm-miasma-credential-stealing-campaign/ Second wave (Phantom Gyp): StepSecurity — https://www.stepsecurity.io/blog/binding-gyp-npm-supply-chain-attack-spreads-like-worm Editor persistence + cleanup steps: Snyk — https://snyk.io/blog/miasma-supply-chain-attack-malicious-code-redhat-cloud-services-npm-packages/ TeamPCP victims and scope: Tenable — https://www.tenable.com/blog/mini-shai-hulud-frequently-asked-questions 2025 secrets stats: GitGuardian State of Secrets Sprawl 2026 — https://www.gitguardian.com/state-of-secrets-sprawl-report-2026 CISA GovCloud leak: Krebs on Security — https://krebsonsecurity.com/2026/05/cisa-admin-leaked-aws-govcloud-keys-on-github/ If you use npm, i wrote in the comments what to do, in order. Do not skip the order, it matters. submitted by /u/johnypita [link] [comments]

the 'just use zapier' advice breaks the second the workflow changes between runs

every time someone here asks for automation the answer is zapier or make or chatgpt's new actions. I've leaned on zapier plenty and it's genuinely great, but only for the workflows i can spell out ahead of time. trigger, filter, action, done. The stuff that actually eats my week isn't like that. closing one deal pulls from a different mix of gmail threads, calendar, slack, and the crm every time, so a fixed zap can't reason about which pieces matter today. i'm not pre-building every branch for one task. What shifted it for me was a desktop agent that works out the steps each run instead of replaying a static recipe, and gates every send behind a per-action approval before it touches anything. that approval step is the part i didn't know i was missing. predefined triggers never needed permission, they only ever did the one thing you wired. So the contrarian bit: more zaps was never the fix. an agent that decides the workflow and asks first is. if you're still stitching this with predefined triggers, where's the point it breaks for you. written with ai submitted by /u/Deep_Ad1959 [link] [comments]

The AI bottleneck has shifted and most people haven't caught up yet

The tooling is abstracting faster than people's mental models are updating. Been playing around with a few agent builders recently and what keeps standing out is how much previously manual orchestration is basically configuration now. Memory, tool calling, browser actions, structured outputs, workflow routing. You used to build this stuff manually. Now you're mostly wiring it together. Which makes "can this be built?" a much less interesting question for a lot of use cases. The harder problems now feel operational. Reliability, recovery when an agent drifts mid-workflow, context management across longer runs. Even with stuff like Zapier, Lyzr Architect, etc. making orchestration dramatically easier, controlling behavior without supervising every step still feels unsolved. Capability honestly isn't the bottleneck anymore imo. It's trust. Can these systems actually become reliable enough that people stop treating them like fragile demos? Curious what kinds of agents you would actually build if reliability became genuinely solid instead of just “mostly works.” submitted by /u/Meher_Nolan [link] [comments]

Using Claude as an ADHD productivity tool

I’ve been using Claude as a kind of AI Chief of Staff to help manage the executive function side of my job processing information, prioritising tasks, drafting comms and it’s been genuinely useful for the way my brain works. The problem: our IT admin won’t allow Outlook to be connected directly. I’m currently getting around it by saving emails as PDFs and sharing them manually, which works but adds friction and defeats part of the purpose. Has anyone found a reliable middle-man solution? Things I’ve considered or wondered about: - Forwarding work emails to a personal Gmail and connecting that instead (not allowed either) - Any third-party tools that act as a bridge - Zapier/Make-style automations that might pull email content through Would love to hear what’s actually worked for people in similar situations, especially those using Claude (or similar tools) specifically to support ADHD in a professional context. The manual workaround is fine for now but I’m keen to make this more seamless submitted by /u/Tiny-Introduction620 [link] [comments]

Has anyone connected Claude to Instagram for reel analysis and content strategy?

I run marketing for a real estate company and have Claude Pro. I've already shared Instagram Insights and Meta Business Suite data with Claude, but I'm looking for something deeper. What I want is for Claude to effectively act as a content strategist by analyzing: -Reels and videos -Audience retention drops -Hook effectiveness -Content themes -Engagement patterns -Lead-generation potential For example, if a reel loses 40% of viewers in the first 3 seconds, I'd like Claude to help identify whether the issue is the hook, pacing, visuals, messaging, or something else. I've seen many creators say things like "I gave Claude access to my Instagram and it helped me grow from 20 followers to 20k," but I'm not sure what their actual setup looks like. From what I've read, Claude doesn't currently have a native/direct Instagram integration, so I'm curious how people are doing this in practice. Are you using: -Meta APIs? -MCP servers? -Zapier, Make, n8n, or another connector? -A custom solution? -Manual exports from Meta Business Suite? Ideally, I'd love a setup where Claude can regularly access my Instagram content and performance data and provide ongoing recommendations. A few specific questions: What is the best way to connect Instagram data to Claude? Are there any free or low-cost third-party connectors you'd recommend? What data can Claude realistically access and analyze? How safe is it to give a third-party connector access to an Instagram business account? Are there any security or privacy concerns I should be aware of? My goal isn't just more views—it's generating qualified real estate leads from Instagram. Would love to hear how others have set this up. submitted by /u/FishermanMaster2821 [link] [comments]

I spent $340 on AI subscriptions last month. Wrote down what I actually used each one for. It was depressing.

Going through the credit card statement, here's what I had active: Claude Pro (40), ChatGPT Plus (20), Cursor (20), Perplexity Pro (20), Notion AI (10), Granola (20), ElevenLabs Starter (5), Midjourney Basic (10), Gamma Pro (10), Beautiful.ai (12), Otter Pro (17), Loom Business (15), Zapier Pro (30), Make Core (10), Tactiq Pro (8), Descript Creator (15), Reclaim.ai Pro (8), Motion (19), Superhuman (30), one i can't remember the name of (10), some ai-something for instagram captions (11) Then I sat down and wrote next to each one the last time I'd actually used it. Not opened it, used it for a real piece of work. Claude (yesterday), ChatGPT (yesterday, voice mode in car), Cursor (yesterday), Perplexity (3 days), Granola (every meeting), Gamma (2 weeks), Zapier (a month, but the automations are still running), ElevenLabs (3 months ago), Midjourney (couldn't remember), Beautiful.ai (couldn't remember), Otter (replaced by Granola, just forgot to cancel), Loom (4 months), Tactiq (replaced by Granola, also forgot), Descript (used twice in 6 months), Reclaim/Motion (both, can't tell them apart, forget which one schedules my meetings), Superhuman (used the AI features twice), the instagram one (literally cannot remember signing up) Cancelled 11 things this morning. Saving $145/month. Nothing in my workflow actually changed. The pattern isn't that AI tools are bad. It's that I treat subscribing like trying. Every "I want to try this" became a recurring charge I forgot about. submitted by /u/OneSeaworthiness2676 [link] [comments]

Went down the Claude Code add-ons rabbit hole

I installed Claude Code, thinking that was basically the whole thing. But after I talked to some folks, I found are adding a bunch of extra stuff on top of it Some of the things I found useful, I feel, could be helpful to share - superpowers https://github.com/obra/superpowers codex-plugin-cc https://github.com/openai/codex-plugin-cc claude-skills https://github.com/anthropics/skills marketingskills https://github.com/coreyhaines31/marketingskills gstack https://github.com/garrytan/gstack frontend-design https://claude.com/plugins/frontend-design hyperframes https://github.com/heygen-com/hyperframes ai-second-brain https://github.com/coleam00/second-brain-starter notebooklm-skill https://github.com/PleasePrompto/notebooklm-skill humanizer https://github.com/blader/humanizer claude-seo https://github.com/AgriciDaniel/claude-seo antfu-skills https://github.com/antfu/skills caveman https://github.com/JuliusBrussee/caveman granola mcp https://github.com/proofsh/granola-mcp-server slack mcp https://github.com/atlasfutures/claude-mcp-slack notion claude code plugin https://github.com/makenotion/claude-code-notion-plugin clj-kondo mcp https://github.com/hive-agi/clj-kondo-mcp zapier mcp https://github.com/zapier/zapier-mcp browser agent mcp https://github.com/imprvhub/mcp-browser-agent I haven't tried all of them yet but trying to build a list of what could be useful and then start trying one by one. It kind of reminds me of installing VS Code and a mix of extensions, shortcuts, git tools, etc. The only downside is that I can already see this becoming chaos. But still interesting though. submitted by /u/Product_Enthusiast24 [link] [comments]

🚀 Skills for small businesses, officially released by Anthropic

Anthropic’s 31 small-business skills reportedly hit around 382,000 downloads on day one. And now someone has mapped the whole thing into a setup workflow that can apparently be deployed in ~10 minutes. This is actually a pretty interesting shift. Small businesses used to stitch together automations manually across: Zapier Notion CRM tools email workflows internal docs custom scripts Now AI companies are starting to package the whole thing into reusable skill packs: 🧠 workflow 📚 memory ⚙️ behavior 🔗 connectors 🤖 orchestration 📋 operating rules Basically: business operations as AI-readable skill files. The best part? You don’t necessarily need Claude to use them. At the core, these are still .md skill files describing workflows for AI agents. So even if you’re using Codex, Cursor, Gemini, or another coding agent, you can still study the structure, adapt the workflows, and plug the ideas into your own agent setup. This feels like the beginning of a new category: “AI business operating templates.” GitHub: https://github.com/anthropics/knowledge-work-plugins submitted by /u/davidnguyen191 [link] [comments]

What SEO tasks are you successfully automating with AI tools or AI agents?

I’ve been exploring how AI tools and AI agents can actually reduce manual SEO work beyond just basic content generation. Curious to know from people actively working in SEO: Which SEO tasks are you automating right now? What workflows are giving you the biggest time savings? Are you using simple AI tools, custom GPTs, Claude workflows, Zapier/Make automations, or fully autonomous agents? Which tasks still need heavy human involvement? Some areas I’m personally thinking about: Keyword clustering Topical map generation Internal linking suggestions Technical SEO audits Schema generation Content briefs Programmatic SEO Competitor analysis EEAT optimization GEO / AI search optimization Reporting & client updates Local SEO tasks Would love to hear: Real use cases Stack/tools you use What works vs what sounds good in theory Things you tried that completely failed Trying to understand where AI genuinely improves SEO workflows and where humans still outperform automation. submitted by /u/mousamkourav [link] [comments]

Claude for Small Business launched this week with 8 integrations. Most SMBs use 20+. What does that mean for the rest of the stack?

Anthropic launched Claude for Small Business on Tuesday. The package includes 15 prebuilt agentic workflows and 8 named integrations: Intuit QuickBooks, PayPal, HubSpot, Canva, DocuSign, Google Workspace, Microsoft 365, and Slack. The workflows handle things like invoice chasing, payroll planning, month-end close, sales campaigns, contract routing, and cash-flow forecasting. Owners approve before anything sends or pays. The basic facts are not in dispute. What's interesting is the math. Most small businesses use more than 8 tools. The common ones not on that list: Shopify, Stripe, Square, Klaviyo, Mailchimp, ActiveCampaign, ConvertKit, Pipedrive, GoHighLevel, Calendly, Notion, Airtable, ClickUp, Webflow, Zapier. Then vertical-specific tools: ServiceTitan, Jobber, Housecall Pro for trades. Kajabi, Teachable, Circle for creators. Toast, Resy, OpenTable for restaurants. Etsy, Faire, Printify for makers. Real question worth asking: how much of a typical small business stack does the 8-tool package actually cover, and which kinds of businesses are well-served versus left out? A rough walk through some common archetypes: Office-based service business (consultants, accountants, agencies, B2B services). Coverage is decent. Most are on Google Workspace or Microsoft 365, run finance through QuickBooks, communicate via Slack, and many use HubSpot. The 8 tools probably hit most of the core stack for this group. E-commerce or DTC brand. Coverage is thin. Shopify isn't there. Stripe isn't there. Klaviyo isn't there. The actual revenue stack of an online store is mostly outside the covered set. Local trades (HVAC, plumbing, insulation, electrical, landscaping). Coverage is essentially absent. The operating systems for these businesses are ServiceTitan, Jobber, Housecall Pro, Square for payments, sometimes QuickBooks for accounting on the back end. The customer-facing and operational tools are not on the list. Creators, coaches, course sellers. Coverage is absent. Kajabi, ConvertKit, Teachable, Circle, Substack. None of it is in the package. Restaurants and hospitality. Coverage is absent. Toast, Square POS, Resy, OpenTable, Toast Payroll. The actual operating systems are not on the list. A few patterns emerge from that walk. First, the package targets a specific kind of small business. Office-based, white-collar, finance running through QuickBooks, meetings on Google or Microsoft, sales through HubSpot. That is a real segment. Anthropic chose it deliberately and the workflows make sense for that profile. Second, for everyone else, the prebuilt workflows mostly don't touch the tools they actually use day to day. The choice isn't "use Claude for Small Business or not." It's "AI in my operations, yes, but via custom work outside this package." That's not a complaint about the launch. Building 8 polished integrations is hard and Anthropic had to pick. It's more an observation that "Claude for Small Business" as a category name covers a wider universe than what the package actually addresses on day one. Curious how this lines up with what people are actually running. If you operate a small business, how many of the 8 covered tools are in your stack? And what's NOT on that list that you'd most want connected to an AI agent? submitted by /u/KolioMandrata [link] [comments]

Tool/connector schemas leaking into user message stream. Anyone else seeing this?

Posting to see if anyone else has hit this and figured out a fix. For about a week, my Claude Chat conversations (opus 4.7) have been showing what looks like tool-registration leakage at the end of every user message I send. It started as simple tool declarations, escalated to full function schemas with parameter docs, and then began including userStyle content alongside the tool blocks. What I've tested: * **Starting a new thread:** No fix. The leak follows across thread boundaries on the same account. * **Turning userStyle off:** Removes the userStyle component cleanly. The function-schema component continues. * **Disconnecting all my MCP connectors:** Did NOT stop the function-schema leak. After disconnecting, the leak switched to dumping schemas of *Anthropic's first-party available connectors* (Atlassian, Cloudflare, Notion, Stripe, Vercel, Zapier) — services I have never used, set up, or connected. These appear to be platform-default available connectors rather than anything tied to my account. * **Other threads on the same account:** A separate parallel thread does NOT show the leak. Suggests it's session-state-dependent at some level, not purely account-wide. The leak appears to be in the platform's tool/connector registration layer, not at the user-controllable connector layer. I have no apparent control surface for stopping the function-schema component. This doesn't impact Claude Code or existing (long-running) Opus 4.6 chat threads. Bug report to Anthropic via email. No response or fix. Questions for the community: 1. Has anyone else seen this? Is it widespread or just me? 2. If you've seen it, what does your payload look like? (Userstyle leakage, function schemas, both, neither?) 3. Has anyone found a user-side fix or workaround? 4. Has anyone gotten an actual response from Anthropic on this? The token cost is non-trivial across long conversations. I'd love to know if this is a known issue or if I should escalate further.

What Claude tips and tricks that you found out over time would you have wished to know about from day 1? What are the must-know resources/steps to be productive with Claude when starting out?

I'm just starting out with Claude and feel a bit overwhelmed. I want to use it for personal and business productivity / organisation matters, copywriting, some design and some coding (Zapier, Website) After knowing more about it / having used it for longer, what would you have wished for to know from day one to fully unlock Claudes potential? What are the best resources (websites, tutorials, videos) for you to enhance your knowledge about Claude and its abilities?

I think I'm slowly building unlimited employees

Dramatic title, I know, but I mean it in a pretty practical way. I have been going pretty deep on how I structure this stuff. Claude Code, Codex, Google Ads API, n8n, CRM, websites, meeting transcripts, all the boring parts. And honestly, the thing that keeps mattering more than I expected is folder structure. Which sounds boring. But I think that is the point. If Claude Code/Codex is going to be useful inside a business, it needs somewhere to work from. Otherwise it is just a blank chat with no memory and no real source of truth. The simple version of my setup is one folder/repo per business or client: client-name/ AGENTS.md CLAUDE.md connection.md meetings/ scripts/ outputs/ _agency-os/ 00-client-brief.md 01-recent-emails.md 02-recent-transcripts.md 03-open-actions.md 04-decisions-and-risks.md 05-metrics-summary.md 06-next-actions.md 07-activity-log.md 08-source-health.md .env AGENTS.md / CLAUDE.md is the operating manual. What the business does, what I am responsible for, what is out of scope, what the model can do by itself, what needs approval, what should be logged, what should never be touched. connection.md is the map. Google Ads customer ID, GA4, GTM, Search Console, Meta, CRM, CMS, website repo, Slack, n8n webhooks, whatever exists. Not the API keys. Those stay in .env. meetings/ is all the transcripts. This part is underrated. Meeting transcripts are basically long-term memory. If the model can read them, it can find old decisions, promises, objections, weird client preferences, stuff I would otherwise have to keep in my head. _agency-os/ is my generated current-state layer. Recent emails, recent transcripts, open actions, risks, metrics, source health. Mine started out mostly generated through Supabase/n8n, but lately I have been using Claude routines and Codex automations for a lot of the Gmail/context fetching. For most people I actually think that is the easier start: have it pull the latest emails or transcripts into the folder on a schedule, no database setup needed. You could even start manually with markdown files and still get most of the benefit. So I basically have a bunch of small operators around their stack. one checks if tracking broke one reads transcripts and finds open promises one looks at CRM lead quality one watches ad account changes one inspects the website or CMS one checks if n8n workflows are still doing what they should one reads API docs and helps build the integration One small example would be Shopify into a CRM. Basically: connect the Shopify API with the CRM API, map orders into contacts/organizations, and have the LLM help build the integration instead of paying a huge Zapier bill forever. But that only works well if the model knows where the CRM lives, what fields matter, what a customer/order should become, where the script belongs, where logs should go, and what it is allowed to change. That is why I don't really see this as a prompt thing anymore. A blank chat will freestyle. A structured workspace can read the context, inspect files, run scripts, compare outputs, and give you something that is actually tied to the business. So yeah, I think I am slowly building unlimited employees. Not employees in the human sense, obviously, but narrow operators with context, tools, and rules. Curious if anyone else here is building this way for their own business, job, project, or clients. Where are you keeping context right now? Local files, GitHub, Notion, Supabase, something else? And how far are you letting Claude Code/Codex go: read-only analysis, suggested changes, or actual write access with guardrails? submitted by /u/kaancata [link] [comments]

My simple workflow and stack brought big results. Why so much over-complicated noise with building apps?

I am a team of one in my small company and I’m building out internal tools without having any kind of education around development. I played with spreadsheets and Zapier and got far enough but now building what looks and feels like real software using mainly Cloudflare infrastructure and it’s working well. Just using Workers, ZeroTrust, and D1 for storage. My confusion is around my workflow and why it seems to be so different from everyone else’s while mine still remaining incredibly efficient and able to get new features launched in the web app within hours. 90% of the time, Claude codes it exactly right. The time is in the testing, and waiting for Claude. I don’t use Claude Code, I just use Projects in the webapp for the long term memory of what I want remembered, and then attach a partial zip of the codebase to ask questions against. Ya, I know I’m missing Claude updating files directly, but the copy-paste I don’t mind. I don’t use Claude Code, or CLI tools whatsoever, I purely work out of the Cloudflare IDE, and Claude Project UIs. I don’t have a traditional “Claude.md” file at all. I don’t use GitHub, or any kind of SDK, although I have AI API calls all throughout the webapp I’ve built. I see this stuff on social media of all these people running agents and other complex systems and I just don’t know if I’m missing something due to my simple approach or if I’m leaving something on the table. submitted by /u/Funny_Incident_5493 [link] [comments]

Read through Anthropic's 2026 agentic coding report, a few numbers that stuck with me

Anthropic put out an 18-page report on agentic coding trends. Skimmed it expecting the usual hype but a few things actually caught me off guard The biggest one: devs use AI in ~60% of work but only fully delegate 0-20% of tasks. So AI is less "autopilot" and more "really fast copilot that still needs you watching." Matches what I've been seeing the real gain is offloading the mechanical stuff, not entire features. Other things worth noting: 27% of AI-assisted work is stuff nobody would've done without AI. Not faster output — net new output. Internal tools, fixing minor annoyances, experiments you'd never prioritize manually Rakuten threw Claude Code at a 12.5M LOC codebase. 7 hours autonomous, single run, 99.9% accuracy. That's... not a toy demo anymore Anthropic's own legal team (zero coding experience) built tools that cut their review cycle from 2-3 days to 24h. Zapier hit 89% AI adoption across the whole company Multi-agent is the big bet for 2026. Not one agent doing everything, but specialized agents coordinated together. Makes sense if you've hit the wall with single-context-window limitations The part I appreciated: report doesn't pretend this replaces engineers. Their own internal research says the shift is toward reviewing and orchestrating, not handing things off completely. One of their engineers said something like "I use AI when I already know what the answer should look like" Anyway, worth a read if you're into this stuff: https://resources.anthropic.com/hubfs/2026%20Agentic%20Coding%20Trends%20Report.pdf Curious what others think especially the multi-agent stuff. Anyone actually running multi-agent setups in production? submitted by /u/lawnguyen123 [link] [comments]