Silver Bullet Security Podcast

Welcome to the Silver Bullet Security Podcast, created and hosted by the Berryville Institute of Machine Learning, where we are defining the future of machine learning security. From 2006-2018, we explored the nascent field of software security through the lens of building security in. But today, the frontier has moved. As we integrate machine learning into the fabric of our essential systems, we find ourselves facing a new set of architectural flaws and security challenges that traditional software security can’t touch. On Silver Bullet, we’re shifting our focus to the security of machine learning—bringing the same deep-dive, “no silver bullet” philosophy to the world of AI.

Theme song is “Zagreb” by The Cheebacabra.

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Using Gemini in the Silver Bullet Reboot

I hosted the Silver Bullet Security Podcast for 13.5 years from 2006 to 2018. For each of the 153 episodes that meant: choosing the guest, getting help from research assistants (at IEEE S&P magazine) to gather background, digesting the background, writing a script (of 9 or so questions), recording the podcast in our studio at…
Breakfast with Brains

We held a small breakfast gathering in the Bay Area with coffee flowing and even better conversation. Joining Gary McGraw and Katie McMahon were Dr. Avery Wang, Jonah Proball, Dr. David Eagleman and Dr. Sarah Eagleman. The conversation spanned subject matters including neuroscience, early neural nets, brain-machine interfaces (BMI), and the early start-up scene across biotech companies doing interesting work…
Science Visit with Giovanni Vigna

We recently visited Giovanni Vigna in the glory of Santa Barbara’s sun and coastline. His students are lucky to have such a setting to learn about malware analysis, vulnerability analysis and other areas of artificial intelligence and even more lucky to have him as their professor at University of California in Santa Barbara (UCSB). He…
Gadi Evron in the House

From time to time, we enjoy inviting guests to participate in our regular Friday research group meetings. We try to do an in person meeting at least once a month, and love it when guests can join that way. Part of our mission at BIML is to spread the word about our views of machine…
Letter Spirit Examiner – Now at Home!

Back in the mid-’90s, an era or two ago, and long before the advent of the transformer model and explosive rise of LLMs that define the modern ML landscape, our own Dr. Gary McGraw (under the guidance of Doug Hofstadter) was exploring a fundamental question of artificial intelligence: “What are the mechanisms underlying the fluidity…
The Pretty People and the Inevitability of Beige

The brilliance of Anthropic’s Super Bowl Ad campaign spotlights what might be considered the core of humanity’s brilliance: creativity and nuanced communication. Unless these ads were created 100% by AI with zero human involvement (even in the ideation phase), this is a moment to celebrate the (presumably-human) humor and pause for the deeper thoughts that they might…
Getting Inside the Network: Whitebox MLsec

We all know that WHAT machines like LLMs reflect the quality and security of everything in their WHAT pile (that is, their training set). We invent cutesy names like “hallucinate” to cover up being dangerously wrong. However, ignoring or soft pedaling risk is often not the best way forward. Real risk management is about understanding…
[un]prompted still too prompty

What happens when you organize a machine learning security conference together with a bunch of security experts who have widely varying degrees of machine learning experience? Fun and games! The [un]prompted conference has a program committee reading like a who’s who of security, stretching from Bruce Schneier on one end to Halvar Flake on the…
Oh my, a MoMa and ChatGPT Moment

Pushing back on my flight from NYC to IAD, I caught one last headline before powering down the computer in my palm. This, from OpenAI: Hum, “Education” or “OpenAI’s Education”… The headline felt worrisome given the total ‘fail’ experience I just had with ChatGPT, during a MoMa guided tour, the evening before, when I used it…
Recursive Pollution and Model Collapse Are Not the Same

Forever ago in 2020, we identified “looping” as one of the “raw data in the world” risks. See An Architectural Risk Analysis of Machine Learning Systems (January 20, 2020), where we said, “If we have learned only one thing about ML security over the last few months, it is that data play just as important…