Why Trying to Secure OpenClaw is Ridiculous | Kala

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Kala

#ArtificialIntelligence #MachineLearning #MLOps

📝 A Few Words

The head of Product at X thinks we have 90 days before "the Spampocalypse".

The statement contains 4 testable assertions:

Within 90 days
All major communication channels
Will become functionally unusable due to AI spam
And we will have no effective mitigation

That's an extreme prediction!

My question is: If AI is so powerful to cause this, isn't it also powerful enough to create better filters?

Attacks scale faster than defenses, sure, but:

Will friction increase? Yes.
Will spam increase? Yes.
Will everything collapse in 90 days? That's highly improbable

I explored a similar dynamic in Generative AI for the Rest of Us (Paperback), where I compared this situation to the "Dead Internet" hypothesis - not as a conspiracy, but as a structural shift to examine how AI can alter the internet's trust layer.

Have a low-noise week!
Aymen

🔍 Inside this Issue

We are speedrunning into a world where AI can ship compilers, TUIs, and new physics proofs, while the security story is still basically: "please do not hand it root." If you have been half-excited, half-nervous about agents in your workflow, these links will sharpen both instincts.

🧠 Adventures in Neural Rendering
🦀 Anthropic Claude: $20,000, 16 AI Agents, and a Compiler That Builds Linux
🧰 Building a TUI is easy now
🧪 GPT-5.2 derives a new result in theoretical physics
🔥 Why Trying to Secure OpenClaw is Ridiculous
🔓 YOLO Mode: Hidden Risks in Claude Code Permissions

Ship the clever stuff, but lock the doors like you mean it.

Happy coding!
FAUN.dev() Team

⭐ Patrons

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Call for Presenters: IaCConf 2026 | Real-World Infrastructure as Code & Platform Engineering Talks

If you’ve managed Infrastructure as Code in production, scaled platforms under pressure, or built guardrails that held up at speed, we want to hear from you. IaCConf 2026 is seeking practitioners to present 40-min sessions on May 14 (virtual). Submit your proposal by April 7.

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ℹ️ News, Updates & Announcements

faun.dev

Anthropic Claude: $20,000, 16 AI Agents, and a Compiler That Builds Linux

16 Claude agents. Two weeks. Zero hand-holding. The result: a 100K-line Rust C compiler that builds Linux 6.9 on x86, ARM, and RISC-V.

Each agent ran solo in its own Docker container, without an interative chat but just a Git-based lock system keeping tasks in sync. The result is over 2,000 code sessions.

👉 Enjoyed this?Read more news on FAUN.dev/news

🔗 Stories, Tutorials & Articles

upguard.com

YOLO Mode: Hidden Risks in Claude Code Permissions

A scrape of 18,470 Claude Code configs on GitHub shows a pattern: developers are handing their AI agents the keys to the castle.

Unrestricted file, shell, and network access is common. Among them:
- 21.3% let Claude run curl
- 14.5% allow arbitrary Python execution
- 19.7% give it git push privileges

That’s how a prompt injection turns into full-blown RCE or a supply chain breach.

interplayoflight.wordpress.com

Adventures in Neural Rendering

A graphics dev took a swing at encoding rendering signals - radiance, irradiance, depth, AO, BRDFs - using tight MLPs in HLSL. They benchmarked size, storage, and runtime cost.

Turns out, MLPs beat L2 spherical harmonics for packing radiance. But they stumble on irradiance and specular BRDFs. Bring in Rusinkiewicz reparameterization, and the MLPs find their footing.

aikido.dev

Why Trying to Secure OpenClaw is Ridiculous

OpenClaw, an open-source autonomous AI agent with full device access, racked up 179K GitHub stars - and walked straight into a security nightmare. It shipped wide open: default ports exposed to the internet, its plugin hub laced with malicious packages.

Slapped-on fixes followed, warning labels, VirusTotal links, but real problems linger. Prompt injection. Zero guardrails around plugin distribution. Still very much on fire

hatchet.run

Building a TUI is easy now

Hatchet used Claude Code, a terminal-native coding agent, to build and ship a real TUI-based workflow manager - fast. Like, days-fast. Powered by the Charm stack (Bubble Tea, Lip Gloss, Huh), it leans hard into CLI-heavy development.

Claude Code handled live testing in tmux, whipped up frontend views from specs and hooks, and pulled off an ASCII DAG renderer - with some open-source repo sleuthing.

openai.com

GPT-5.2 derives a new result in theoretical physics

GPT-5.2 Pro spotted something wild: a nonzero gluon scattering amplitude in the half-collinear regime. That’s supposed to vanish, according to standard QFT gospel. Not anymore.

OpenAI’s own model backed it up with a formal proof. Humans triple-checked it analytically. And yep - it holds.

Now it’s bleeding into gravity, too.

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⚙️ Tools, Apps & Software

github.com

openclaw-rocks/k8s-operator

Self-host OpenClaw AI agents on Kubernetes with production-grade security, observability, and lifecycle management.

github.com

iOfficeAI/AionUi

Free, local, open-source 24/7 Cowork and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more

github.com

hesreallyhim/awesome-claude-code

A curated list of awesome skills, hooks, slash-commands, agent orchestrators, applications, and plugins for Claude Code by Anthropic

github.com

janhq/jan

Jan is an open source alternative to ChatGPT that runs 100% offline on your computer.

github.com

BloopAI/vibe-kanban

Get 10X more out of Claude Code, Codex or any coding agent

👉 Spread the word and help developers find and follow your Open Source project by promoting it on FAUN. Get in touch for more information.

🤔 Did you know?

Did you know that in TensorFlow, slow training is often caused by the tf.data input pipeline, not the model itself? The official tf.data performance guide explains how features like prefetch and parallel map can overlap CPU and GPU work, but misconfiguration can still lead to IteratorGetNext stalls, which you can see in the TensorBoard trace viewer described in the TensorFlow profiler docs. Profiling the input pipeline often reveals bottlenecks before any CUDA tuning is needed. In practice, stable buffering and measured parallelism usually improve throughput more than simply increasing pipeline concurrency.

🤖 Once, SenseiOne Said

"Your model isn't in production when it gets a better score; it's in production when you can explain why it got worse and still ship the fix safely."
— SenseiOne

(*) SenseiOne is FAUN.dev’s work-in-progress AI agent

⚡Growth Notes

When an experiment shifts, first audit the seams: pin every metric to an immutable dataset snapshot, model commit, feature code path, and RNG seed, then rerun with one controlled change at a time. Keep a small, boring table in the repo that maps run ID to those artifacts and asserts them in the training entrypoint, so drift shows up as a broken contract rather than a surprise.

Each week, we share a practical move to grow faster and work smarter

👤 This Week's Human

This Week’s Human is Shashank B R, a senior full stack engineer in Cambridge building tools that help bioinformaticians and researchers handle complex biological data. Across Java Spring Boot, Python FastAPI, React, and data platforms like Kafka, Cassandra, and Netflix Hollow, he ships fast, observable systems that make messy datasets queryable.

💡 Engage with FAUN.dev on LinkedIn — like, comment on, or share any of our posts on LinkedIn — you might be our next “This Week’s Human”!

😂 Meme of the week

❤️ Thanks for reading

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Kala #516: Why Trying to Secure OpenClaw is Ridiculous
Legend: ✅ = Editor's Choice / ♻️ = Old but Gold / ⭐ = Promoted / 🔰 = Beginner Friendly

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