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ok! i heard you! i made charts and graphics to explain things and make this all more approachable! htmlpreview.github.io/?https://githu…

This ProPublica story about the government approving Microsoft cloud products despite reviewers deeming them alarmingly opaque and insecure sure doesn't reflect well on Microsoft, its third-party auditors, its government allies, or D.C.'s revolving door. propublica.org/article/micros…

Who knew a really long string could make an Entra ID login disappear from the logs entirely? In our #blog, @nyxgeek breaks down how overflowing #Azure's sign-in logging mechanism allowed access tokens to be issued without a single log entry. Read it now! hubs.la/Q047xTVc0

threat intel reports:

it’s that time of year again! get ready to dig into a couple million words of threat intel! don’t worry, no worry to go through the vendor gauntlet. check them all out here: github.com/da5ch0/2026_03…?😉🫶🏴‍☠️

Metaverse is shutting down. WHO COULD'VE SEEN THIS COMING

This video is wild. @rez0__ goes deep into how he works with AI for bug bounty hunting. youtube.com/watch?v=qTX9u-…

i love teachy orange man johng hambone so dang much, y’all

Solid mathematical ideas almost always outperform contrived engineering tricks. For years deep learning has been dominated by increasingly complex architectural hacks: CNN blocks, attention layers, channel mixers, residual pathways, normalization stacks. Every few years a new architecture is announced as if it were a revolution. One of the most famous examples was Kaiming He and Residual Networks (ResNet). At the time he was paraded around the AI world like a celebrity because residual connections supposedly “solved” deep learning. But these were largely engineering patches. Now something much more interesting appeared. A new architecture called CliffordNet returns to mathematics — specifically Clifford Algebra, developed in the 19th century by William Kingdon Clifford. Instead of stacking arbitrary modules, the model is built around the geometric product uv = u·v + u∧v A single algebraic operation that simultaneously captures inner product structure and geometric interactions. In other words: the math already contains the interaction mechanism. No attention blocks. No mixer layers. No architectural spaghetti. The result: • 77.82% accuracy on CIFAR-100 with only 1.4M parameters • roughly 8× fewer parameters than ResNet-18 And with strict O(N) complexity. The paper even suggests that once geometric interactions are modeled correctly, feed-forward networks become largely redundant. A good reminder for the AI community. Engineering tricks can dominate for years. But eventually mathematics shows up and deletes half the architecture. Paper: [arxiv.org/pdf/2601.06793…) 19th century geometry just walked into computer vision.

Remember the first rule of memory safety in C is to have fun

@ZackKorman @fr0gger_ word. and don’t forget defender friday! 1130 MDR so whatever time that is on the Narnian clock 😉

@da5ch0 @fr0gger_ Cool, will also check this in the morning

I got mad about people defending MCP so I made this video. The first minute is just me being very mad, but then I tried to contribute something of value after that. youtube.com/watch?v=m0VyZU…

oh, i know lol. but you can coach interleaved models to stay within the therapeutic window (so to speak) where they are producing usable outputs, much easier than single-pass monolithic chain-of-thought models. but even then, you gotta specifically tell them HOW to logic it out 😉

@da5ch0 @0x686967 @stanziirl The thing is, it’s more about the process and less about the models themselves…

had to code at work today hey claude remind me how dumb i am 🤡

my problem is i keep reading cybernetics books. and then they all reference one another. so one quickly goes from “that was good, i wonder who all they cite” to “crap, there’s still 23 papers and 3 full books i haven’t read yet!” paired with deep frustration at myself for not reading even more 😅😭

one of the best parts of finishing a book is having room to start another 😄

@Douglas19558190 … you got a cat?

I am seriously considering disabling all keyboard shortcuts!

@ZackKorman @fr0gger_ in the meantime you should peep the operator context md i been seeding. i’d love your thoughts/critiques! github.com/da5ch0/How-to-… 🙏🖖🏴‍☠️

@da5ch0 @fr0gger_ Oh I haven’t looked at it. Might look tomorrow

strong agree! we need to formalize a modern version of the old school “aqua book” (i know @nyxgeek knows what i’m talking about;) and get everyone using an actually-shared and — precise — vocabulary so we don’t linger stuck in problems of miscommunication and swindling longer than we already have: github.com/da5ch0/Securit…

@da5ch0 I mainly care from the perspective of industry agreed upon terms randomly get shaken up by marketing people for no reason which makes client sales calls confusing.

Prior to the recent “pentest agent” wave on GitHub, app testing hadn’t really been framed as “pentesting” in a long time.

parsers are hard

@essobi @0x686967 @stanziirl i figured i should finally stop just hoarding knowledge/power like some greedy dragon and share with the young’ns a bit. it’s been, freeing

@da5ch0 @0x686967 @stanziirl I should probably write something down… I’ve been doing this for a while now.

@stanziirl np! if you don’t already have something like it i recommend you download and edit this to use with every session for a good time, too!: github.com/da5ch0/How-to-… always happy to make others’ experiences less painful than mine were, and let them learn from my mistakes, ya know?😅