Plugin4Shell breaks SHA pinning in four AI coding agents at once
A shared design flaw lets attackers swap pinned plugin code in four major AI coding agents without any user action. Two vendors still have no fix.
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A shared design flaw lets attackers swap pinned plugin code in four major AI coding agents without any user action. Two vendors still have no fix.
How to run PrismML's 5.9 GB ternary Qwen3.8 27B locally, what it scores next to a 17.6 GB Q4 quant, and the fork, long-context and vision costs the headline hides.
Three cases from Z.ai's post show what an agent can fix in kernels and concurrency when tests, traces and microbenchmarks are cheap to run, and what humans still sign off.
Skip the transparency debate. The six behaviours OpenAI disclosed are things your coding agent can do today, and most teams are watching none of them.
Google shipped a first-party MCP server for Google Home. Read it as a design pattern for agent tools that touch the physical world, then audit your own servers against it.
Most agent pipelines fake classification with JSON mode and a regex. Jev makes it a first-class primitive with calibrated probabilities. What changes, and what the HN sceptics got right.
Google shipped two stable Live API voice models. The Extended Thinking one changes the turn contract: tool calls are async only, and you must poll interaction_status to know when it is idle.
Pion's control plane, secret handling and revenue-share pricing are patterns for long-horizon agents. The store losing $40,000 in five months is the caveat.
Microsoft's draft MAI Code of Conduct read as a spec: which behaviours sit above your system prompt, what operators can tune, and what to file before consultation closes.
A migration walkthrough for Homebrew 7.0.0: the Intel Mac cliff, the CI and Brewfile flags that vanished, the Linux sandbox swap, and the two new commands worth adopting today.
The May RubyGems flood was reportedly an OpenAI training run looking for internet access. What the chain teaches maintainers, agent builders and anyone who owes a registry a heads-up.
Strip the slow-down debate away and one dated commitment remains, now matched by OpenAI. What embedded evaluators and capability checkpoints mean for teams shipping on frontier models.