May 18, 2026
Bug drama with extra AI spice
Project Glasswing: what Mythos showed us
AI bug hunter stuns, but commenters demand receipts and roast the write-up
TLDR: Mythos Preview impressed testers by not just finding software weaknesses but showing how small issues could be combined into a real break-in. Commenters, though, were far more interested in what the post didn’t say: how bad the bugs were, how many were real, and whether the whole thing read like AI-written marketing.
Mythos Preview, shown through Anthropic’s Project Glasswing, was supposed to be the big star: an artificial intelligence tool that can do more than spot tiny software flaws. According to the post, it can connect multiple small mistakes into one bigger attack and even test whether its own idea actually works. In plain English: this thing doesn’t just point and gasp — it tries to prove the break-in is real. That’s a huge leap, and even the skeptics in the crowd seemed willing to admit the workflow sounds powerful.
But the comments? Absolutely not ready to clap just yet. The loudest reaction was basically: cool demo, where are the numbers? Readers kept asking how many problems it found, how many were real, and how serious the worst ones actually were. One commenter flatly said that was the “most interesting and important bit,” accusing the post of dancing around the juicy details. Another jabbed at the article’s style itself, with snark about whether the company or the AI had written the blog post. Ouch.
That’s where the drama really kicked in: not over whether the tool is impressive, but whether the post felt like substance or spin. One person joked about the inevitable backlash machine, while another dismissed it as a “poorly written post” even while conceding the actual discovery process “might actually give good results.” So the mood was classic internet: half amazed, half suspicious, and fully ready to turn a product write-up into a comment-section trial by fire.
Key Points
- •The authors tested security-focused LLMs on their own infrastructure and used Anthropic’s Mythos Preview on more than 50 internal repositories through Project Glasswing.
- •The article says Mythos Preview differs from earlier frontier models by acting as a different kind of security tool rather than a simple incremental improvement.
- •Mythos Preview was described as capable of constructing exploit chains by combining multiple attack primitives into a working exploit path.
- •The model was also described as generating proof-of-exploit code by writing, compiling, running, and iterating on test programs in a scratch environment.
- •The Project Glasswing version of Mythos Preview reportedly lacked some safeguards found in generally available models, while still showing inconsistent emergent refusals on certain requests.