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ebursztein

Documentation back online
Documentation is back online
The hacker news post caught us exactly as we are redoing the site ahead of the unprompted talk: https://unpromptedcon.org/agenda-10-2026/ - Screenshots and everything else will be back shortly. Capsem is fast moving so we delayed finishing the site until all the core features where stable.
There is no direct network access instead all traffic is routed through the security engine that perform network reconstruction, including parsing models and MCP sessions to enforce rules written in a custom DSL based of CEL.
Capsem supports both Linux (x86 / Arm64) and MacOs M1 or later (arm64). There are placeholders on the site as the post happen exactly as we are redoing the site ahead of the talk at unpromted: https://unpromptedcon.org/agenda-10-2026/
Thanks for looking in-depth in our post. The Hitachi RTU500 mention is not an hallucination, we did check for those. It is mentioned in the Mandiant threat intelligence data.
Try Usearch - it's really fast and under rated https://github.com/unum-cloud/usearch
Thank you - we are adding them to our test suit for the next version.
Thanks for the feedback -- we will look into it. If you can share with us the list of URL that would be very helpful so we can reproduce - send us an email at [email protected] if that is possible.

For crawling we have planned a head only model to avoid fetching the whole file but it is not ready yet -- we weren't sure what use-cases would emerge so that is good to know that such model might be useful.

We mostly use Magika internally to route files for AV scanning as we wrote in the blog post, so it is possible that despite our best effort to test Magika extensively on various file types it is not as good on fonts format as it should be. We will look into.

Thanks again for sharing your experience with Magika this is very useful.

Co-author of Magika here (Elie) so we didn't include the measurements in the blog post to avoid making it too long but we did those measurements.

Overall file takes about 6ms (single file) 2.26ms per files when scanning multiples. Magika is at 65ms single file and 5.3ms when scanning multiples.

So Magika is for the worst case scenario about 10x slower due to the time it takes to load the model and 2x slower on repeated detection. This is why we said it is not that much slower.

We will have more performance measurements in the upcoming research paper. Hope that answer the question

Thanks for the list, we will probably try to extend the list of format supported in future revision.
Indeed but as pointed out in the blog post -- file is significantly less accurate that Magika. There are also some file type that we support and file doesn't as reported in the table.
Thanks :)
We did release the npm package because indeed we create a web demo and thought people might want to also use it. We know it is not as fast as the python version or a C++ version -- which why we did mark it as experimental.

The release include the python package and the cli which are quite fast and is the main way we did expect people to use -- sorry if that hasn't be clear in the post.

The goal of the release is to offer a tool that is far more accurate that other tools and works on the major file types as we hope it to be useful to the community.

Glad to hear it worked on your files

Show HN: Magika: AI powered fast and efficient file type identification

We are very excited to announce the release of Magika our AI powered fast and efficient file type identification lib and tool - https://opensource.googleblog.com/2024/02/magika-ai-powered-fast-and-efficient-file-type-identification.htmlThanks to its optimized Keras model, large scale training dataset, and Onnx Magika massively outperform other file identification tools while be very fast even...

( Read More... | 1 comment | 2 points | on HN )

Show HN: RETVec: Resilient and Efficient Text Vectorizer

Happy Friday,Really happy to share that the code and model for RETVec our new SOTA robust text tokenizer for classification is available on Github: https://github.com/google-research/retvec/ and the NeurIPS paper on Arxiv: https://arxiv.org/abs/2302.09207Beside its compactness and robustness one of the RETVec strong point is that it greatly simplify the creation of on-device models: RETVec work...

( Read More... | no comments | on HN )
For those interested I did put Crowley original tarot deck on the Etteilla Foundation website https://etteilla.org/en/deck/69/crowley-s-thoth-tarot

Show HN: Etteilla Foundation my side project

Hi,After over two years of intense efforts, I am thrilled to share that the Etteilla Foundation and its website https://etteilla.org are finally live. The Etteilla Foundation is a 501(c)(3) non-profit organization dedicated to preserving and promoting the rich cultural heritage of playing cards.Over the last two years, as side project, I created the foundation and spend my weekend and vacations...

( Read More... | no comments | on HN )
Re:AI helps keeping Gmail inboxes malware free [slides] on Monday April 24, 2023 @10:11PM (#35695786)
Here are the slides of my recent talk at FIC on how Google uses AI to strengthen Gmail's document defenses and withstand attacks that evade traditional antivirus solutions.

This talk recounts how in the last few years we researched and developed a specialized office document scanner that combines a custom document analyzer with deep-learning to detect malicious docx and xls that bypass standard AVs. In 2021 our AI scanner was able to detect 36% additional malicious documents that eluded other scanners on average and 178% at peak performance.

I hope you will find those slides useful and informative. If you have any questions, please ask away, will do my best to answer :)

Re:Ask HN: Share Your Personal Site on Friday January 06, 2023 @03:48PM (#34280841)
https://elie.net mostly about the research we do at Google. Generated statically and hosted on firebase. The design was custom made for it.

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