cross-posted from: https://feddit.org/post/28915273
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That marketing may have outstripped reality. Early reports from Mythos preview users including AWS and Mozilla indicate that while the model is very good and very fast at finding vulnerabilities, and requires less hands-on guidance from security engineers - making it a welcome time-saver for the human teams - it has yet to eclipse human security researchers.
“So far we’ve found no category or complexity of vulnerability that humans can find that this model can’t,” Mozilla CTO Bobby Holley said, after revealing that Mythos found 271 vulnerabilities in Firefox 150. Then he added: “We also haven’t seen any bugs that couldn’t have been found by an elite human researcher.” In other words, it’s like adding an automated security researcher to your team. Not a zero-day machine that’s too dangerous for the world.
Does this mean browsers are going to crash less in the near future?
What do you do with your browsers so they crash? Mine didn’t do that in at least a decade
More often than crashing outright, I hit situations where the browser just isn’t working, won’t load pages or won’t execute button clicks on pages or similar and the only thing (on Windows) that will fix it is a reboot. In Linux usually closing the browser and restarting will get it going again. Yeah, BSODs are rare lately (though not entirely gone), but malfunctions still abound.
Interesting. So far, all my experiences with stuff like that turned out to be faulty hardware.
My last (confirmed) faulty hardware crash (resulting from user operation, not just an outright failure to boot, or random crash “for no particular reason” other than a program trying to access a failing SSD or similar) came in the late 90s with a GPU card that would take down the system bus voltage in response to certain CAD operations - repeatably - do this rotation, watch the CPU do a hard reboot every time. Stay away from the GPU heavy operations - no problems.
These days the browser is the OS for over half of what happens on my work machines. And they’re almost, but not quite, 100% reliable, until they’re not. Working out those rare problems takes a long time, and with “progress” it feels like they’ve reached a kind of equilibrium where the rate of new problem introduction is about the same as the rate of known problem fixes.