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  • LiteLLM Supply Chain Attack Compromises Millions of AI Credentials
    LiteLLM Supply Chain Attack Compromises Millions of AI Credentials

    Someone just poisoned the Python package that manages AI API keys for NASA, Netflix, Stripe, and NVIDIA.. 97 million downloads a month.. and a simple pip install was enough to steal everything on your machine. The attacker picked the one package whose entire job is holding every AI credential in the organization in one place. OpenAI keys, Anthropic keys, Google keys, Amazon keys… all routed through one proxy. All compromised at once. The poisoned version was published straight to PyPI.. no code on GitHub.. no release tag.. no review. Just a file that Python runs automatically on startup. You didn’t need to import it. You didn’t need to call it. The malware fired the second the package existed on your machine. The attacker vibe coded it… the malware was so sloppy it crashed computers.. used so much RAM a developer noticed their machine dying and investigated. They found LiteLLM had been pulled in through a Cursor MCP plugin they didn’t even know they had. That crash is the only reason thousands of companies aren’t fully exfiltrated right now. If the code had been cleaner nobody notices for weeks. Maybe months. The attack chain is the part that gets worse every sentence. TeamPCP compromised Trivy first. A security scanning tool. On March 19. LiteLLM used Trivy in its own CI pipeline… so the credentials stolen from the SECURITY product were used to hijack the AI product that holds all your other credentials. Then they hit GitHub Actions. Then Docker Hub. Then npm. Then Open VSX. Five package ecosystems in two weeks. Each breach giving them the credentials to unlock the next one. The payload was three stages.. harvest every SSH key, cloud token, Kubernetes secret, crypto wallet, and .env file on the machine.. deploy privileged containers across every node in the cluster.. install a persistent backdoor waiting for new instructions. TeamPCP posted on Telegram after: “Many of your favourite security tools and open-source projects will be targeted in the months to come.. stay tuned.” Every AI agent, copilot, and internal tool your company shipped this year runs on hundreds of packages exactly like this one… nobody chose to install LiteLLM on that developer’s machine. It came in as a dependency of a dependency of a plugin. One compromised maintainer account turned the entire trust chain into a credential harvesting operation across thousands of production environments in hours. The companies deploying AI the fastest right now have the least visibility into what’s underneath it. Andrej Karpathy (@karpathy) Software horror: litellm PyPI supply chain attack. Simple `pip install litellm` was enough to exfiltrate SSH keys, AWS/GCP/Azure creds, Kubernetes configs, git credentials, env vars (all your API keys), shell history, crypto wallets, SSL private keys, CI/CD secrets, database passwords. LiteLLM itself has 97 million downloads per month which is already terrible, but much worse, the contagion spreads to any project that depends on litellm. For example, if you did `pip install dspy` (which depended on litellm>=1.64.0), you'd also be pwnd. Same for any other large project that depended on litellm. Afaict the poisoned version was up for only less than ~1 hour. The attack had a bug which led to its discovery – Callum McMahon was using an MCP plugin inside Cursor that pulled in litellm as a transitive dependency. When litellm 1.82.8 installed, their machine ran out of RAM and crashed. So if the attacker didn't vibe code this attack it could have been undetected for many days or weeks. Supply chain attacks like this are basically the scariest thing imaginable in modern software. Every time you install any depedency you could be pulling in a poisoned package anywhere deep inside its entire depedency tree. This is especially risky with large projects that might have lots and lots of dependencies. The credentials that do get stolen in each attack can then be used to take over more accounts and compromise more packages. Classical software engineering would have you believe that dependencies are good (we're building pyramids from bricks), but imo this has to be re-evaluated, and it's why I've been so growingly averse to them, preferring to use LLMs to "yoink" functionality when it's simple enough and possible. — https://nitter.net/karpathy/status/2036487306585268612#m

    → View original post on X — @bobgourley, 2026-03-25 03:56 UTC

  • Bespoke AI Agents with SuperCollider Direct Integration

    it's a bit easier to get going with tidal cycles or strudel, they both use sc under the hood. it would be interesting to see what a bespoke agent could do with direct sc

    → View original post on X — @genekogan

  • Hands-On Deep Q-Learning Tutorial with PyTorch and TensorFlow
    Hands-On Deep Q-Learning Tutorial with PyTorch and TensorFlow

    Hands On Deep Q-Learning! #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode https://
    geni.us/Deep-Q-Learning

    → View original post on X — @gp_pulipaka

  • Custom Entity Recognition Accelerated with Claude and Amazon Bedrock
    Custom Entity Recognition Accelerated with Claude and Amazon Bedrock

    Accelerating Custom Entity Recognition with Claude Tool use in Amazon Bedrock! #BigData #Analytics #DataScience #AI #MachineLearning #NLProc #LLM #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux

    → View original post on X — @gp_pulipaka

  • New AI Protocol Design: Exploring Technical Solutions

    Sounds like we need some kind of new protocol that’s designed for AI, any ideas?

    → View original post on X — @jiquanngiam

  • How Backward Propagation Works in Neural Networks
    How Backward Propagation Works in Neural Networks

    How Does Backward Propagation Work in Neural Networks? #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #Python #RStats #TensorFlow #JavaScript #ReactJS #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode https://
    geni.us/Backward-Backp
    rop
    …

    → View original post on X — @gp_pulipaka

  • Software Review in the Era of AI: What OpenSci Tests
    Software Review in the Era of AI: What OpenSci Tests

    Software Review in the Era of AI: What We Are Testing at rOpenSci https://
    buff.ly/cBRP7hp
    #AI #MachineLearning #DeepLearning #LLMs #DataScience

    → View original post on X — @miketamir

  • PyPI Security Incident: 425K Downloads Exposure Timeline

    In particular this clarifies the timeline more: 1.82.7 was published 10:39 UTC, PyPI quarantine approx 13:38, so this was up ~3 hours. At 3.4M downloads/day this might be approx ~425K downloads, a lot of that could be non-latest/locked versions so maybe 20K – 80K range exposure.

    → View original post on X — @karpathy

  • ChatGPT Pro and Codex introduction opportunity
    ChatGPT Pro and Codex introduction opportunity

    Chat, who can intro me to them? would love to hook them up w/ ChatGPT Pro sub & introduce them to Codex too!

    → View original post on X — @reach_vb

  • Cursor AI Tool Gets Cost Plot X-Axis Direction Right
    Cursor AI Tool Gets Cost Plot X-Axis Direction Right

    Cursor got the x-axis direction right on the cost plot this time!

    → View original post on X — @randal_olson