If anyone is using @NxDevTools with a JS Rust monorepo and found the monodon plugin deficient (mainly because it isn't being updated) then this might help. Not a 1:1 parity yet but handles what I've needed. nxrust by @eddacraft_ai ⬇️

AI agents probably wrote a meaningful share of the code that shipped to your repo this week. No one on your team can tell you which lines. No one can tell you which policies governed the agent. No one's going to find out until something breaks.

Last week, Anthropic announced Project Glasswing alongside Claude Mythos Preview, a model they described as so powerful at finding vulnerabilities they couldn't release it. The announcement featured AWS, Microsoft, Google, and Apple as partners, $100M in compute credits, and a clear message: this is dangerous, and only we can be trusted to deploy it safely. The results were real. Thousands of zero-days across every major OS and browser. A 27-year-old bug in OpenBSD. A 16-year-old bug in FFmpeg. Fully autonomous exploit chains that would have taken human researchers weeks. But here's what bothered me: all the credit went to the model. Read the technical blog carefully and a different picture emerges. The real innovation isn't the model. It's the workflow: - Rank every file in a codebase by attack surface - Fan out hundreds of parallel agents, each scoped to one file - Use crash oracles (AddressSanitizer, UBSan) as ground truth - Run a second verification agent to filter noise - Generate exploits as a triage mechanism for severity That's a pipeline. And pipelines are model-agnostic. At Lazarus AI, we spend our days deploying custom AI in places where "just use the closed API" isn't an option: regulated industries, enterprise, and government. When I saw Glasswing, my instinct was the same one I have every week: strip out the proprietary model, keep the architecture, run it on whatever model is best for the customer. Clearwing is a fully open-source vulnerability discovery engine. Crash-first hunting, file-parallel agents, oracle-driven verification, variant hunting, adversarial verification. Works with any LLM. I tested it with OpenAI Codex 5.4 and reproduced Glasswing's findings. I'm now reproducing results with our own ReAligned model - Qwen3.5 finetuned to Western alignment. Mythos is certainly a great model. The N-day exploit walkthroughs in Anthropic's blog show real reasoning depth. But it's an incremental improvement over Opus, the same way Opus was over Sonnet, and Sonnet over Haiku. It's not a leap to superintelligence. It's the next point on a curve we've been watching for years. What actually changed the game was the workflow. Defenders shouldn't have to wait for access to a gated model to secure their software. These vulnerabilities have been sitting in codebases for decades. The tools to find them should be available to everyone: the open source maintainer running FFmpeg on a Saturday, the startup that can't afford $125/M output tokens, the researcher in a country where Anthropic doesn't operate. Clearwing is MIT licensed and available now. github.com/Lazarus-AI/clearw… Clearwing enables a wide variety of security activities. Handle with care. It is sharp.

As we know by now adding in brevity constraints can save a bunch of tokens... some of the viral options out there seem cool but aren't super useful in a serious context. I have SITREP which is based on something I've been using for a while to condense output.