1_DevOps'ish

archived 13 May 2026 15:49:56 UTC

We used the depthfirst system to analyze the NGINX source code, and it autonomously discovered 4 remote memory corruption issues, including a critical heap buffer overflow introduced in 2008. We further investigated the exploitability of the issues, and developed a working proof of concept demonstrating RCE with ASLR off. If you use rewrite and set directives in your NGINX configuration, you're at risk.

How curl’s disclosure policy filtered an AI scanner’s findings at source

Following last week's disclosure of the Dirty Frag vulnerability for the Linux kernel, which only finished being patched up in mainline on Monday, Fragnesia is now public as a similar local privilege escalation (LPE) vulnerability.

Discover how analyzing numeric patterns in domain names—specifically a rare base-5 encoding—reveals hidden links between seemingly separate clusters and exposes a single coordinated campaign.

Raw MCP tools provide the connection, but Red Hat Agentic Skills provide the expertise. Move beyond manual tool-calling with a curated collection that embeds reliability, safety, and Red Hat best practices into every AI interaction.

In the first episode of the Platformer podcast, Box CEO Aaron Levie makes the case that you'll keep your job — but soon, you might not recognize it

It's not too early to start planning for Wi-Fi 8. New features include non-primary channel access, seamless mobility domain (SMD) roaming, intermediate modulation and coding scheme (MCS) levels, and dynamic power-save modes.

AI-powered desktop SQL client. Cross-platform. Built with Flutter. - sjjian/openhare

The `boring` SSH tunnel manager. Contribute to alebeck/boring development by creating an account on GitHub.

10 undocumented gotchas for deploying Hermes agent on Railway with Telegram—from the wrong gateway command to zombie MCP processes to the volume path that wipes your bot's memory on every deploy.

Safe OpenTofu and AVM module migrations in practice.

Hey, you know who is good at making "distroless images"? Distros.

Let coding agents diagnose and fix your React code - millionco/react-doctor

Big Tech’s reliance on TSMC makes the China-Taiwan dispute the world’s most dangerous geopolitical flashpoint, says writer Eyck Freymann ahead of this week’s Xi-Trump meeting in Beijing.

The latest artificial intelligence models from Anthropic and OpenAI are extending the United States’ lead over China and intensifying the rivalry between the countries.

A dispute over fsnotify maintainer access set off supply chain alarms around one of Go’s most widely used filesystem libraries.

Alon Haimovich is leaving after an investigation into alleged unethical use of Azure by the Ministry of Defense, “Globes” has learned. Microsoft Israel has been placed under the management of Microsoft France.

Introducing the Fedora Hummingbird Linux image-based OS: A new rolling Linux distribution that brings zero-CVE security, atomic updates, and the container workflow model to Fedora Linux.

When trying to use any Kubernetes CRD (or even core types) I am pretty much always pulling up a reference doc of some sort to see what fields are available and what they do. However, I have pretty much always found the options for this to be pretty bad. To remedy this, I have been working on a new tool that automatically generates documentation for Kubernetes CRDs, and I wanted to share it here.

Production-version patches are coming online and should be installed pronto.

In a word: AI.

Master Exim source repository

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About half of agent tasks can run on a local 35B model. The real advantage isn't cost or privacy — it's latency. 2.1x faster means more iteration cycles per session.

Idempotency is not just an HTTP header or a key lookup. This article covers the failure cases that bite real APIs: different requests with the same key, concurrent retries, partial success, downstream uncertainty, response replay, expiry, and duplicate message handling.

A field guide to the engineers and designers firing AI agents at every problem in sight

LLM agents that consolidate experience into textual memory often make their memory worse over time. We trace the failure to the consolidation step itself.

Experiments with getting usable outputs out of local models on a standard Macbook