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Schedule

Der Hub wird spätestens Ende Januar archiviert, alle nutzerbezogenen Inhalte, Boards und auch einige Wiki-Seiten werden dabei entfernt. Alle öffentlichen Assemblies, Projekte und Veranstaltungen bleiben. // The hub will be archived by end of January. All user-provided content, boards and several wiki pages will be deleted. All public assemblies, projects and events will remain.
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Day 2
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How To Minimize Bugs in Cryptography Code (en)

Jade

"Don't roll your own crypto" is an often-repeated aphorism. It's good advice -- but then how does any cryptography get made? Writers of cryptography code like myself write code with bugs just like anyone else, so how do we take precautions against our own mistakes? In this talk, I will give a peek into the cryptographer's toolbox of advanced techniques to avoid bugs: targeted testing, model checking, mathematical proof assistants, information-flow analysis, and more. None of these techniques is a magic silver bullet, but they can help find flaws in reasoning about tricky corner cases in low-level code or prove that higher-level designs are sound, given a defined set of assumptions. We'll go over some examples and try to give a high-level feel for different workflows that create "high-assurance" code. Whether you know it or not, you use this type of cryptography code every day: in your browser, your messaging apps, and your favorite programming language standard libraries.

When Vibe Scammers Met Vibe Hackers: Pwning PhaaS with Their Own Weapons (en)

Chiao-Lin Yu (Steven Meow)

What happens when AI-powered criminals meet AI-powered hunters? A technical arms race where both sides are vibing their way through exploitation—and the backdoors write themselves. In October 2025, we investigated Taiwan's fake delivery scam ecosystem targeting convenience store customers. What started as social engineering on social media became a deep dive into two distinct fraud platforms—both bearing the unmistakable fingerprints of AI-generated code. Their developers left more than just bugs: authentication flaws, file management oversights, and database implementations that screamed "I asked LLM and deployed without reading." We turned their sloppiness into weaponized OSINT. Through strategic reconnaissance, careful database analysis, and meticulous operational security, we achieved complete system access on multiple fraud infrastructures. By analyzing server artifacts and certificate patterns, we mapped 100+ active domains and extracted evidence linking thousands of victim transactions worth millions of euros in fraud. But here's the twist: we used the same AI tools they did, just with better prompts. The takeaway isn't just about hunting scammers—it's about the collapse of the skill gap in both offense and defense. When vibe coding meets vibe hacking, the underground economy democratizes in ways we never anticipated. We'll share our methodology for fingerprinting AI-assisted crime infrastructure, discuss the ethical boundaries of counter-operations, and demonstrate how to build sustainable threat intelligence pipelines when your adversary can redeploy in 5 minutes. This talk proves that in 2025, the real exploit isn't zero-day—it's zero-understanding.

The Small Packet of Bits That Can Save (or Destabilize) a City (en)

Manuel Rábade

The Emergency Alert System (EAS) and its SAME (Specific Area Message Encoding) protocol are public alerting technologies that broadcast short digital bursts over VHF triggering emergency messages on millions of receivers across North America. In Mexico, this technology was integrated into the Seismic Alert System (SASMEX) which more than 30 million people in the central part of the country rely on to prepare for frequent earthquakes. While new alerting technologies have emerged, the EAS-SAME network continues to play an important role for public safety in the U.S., Mexico, and Canada. Yet, the same small packets of bits that can help protect a city could also, in the wrong hands, destabilize it. This talk examines how these systems operate and reveals a troubling truth: spoofing these alerts is far easier than most people expect.

A Quick Stop at the HostileShop (en)

Mike Perry

HostileShop is a python-based tool for generating prompt injections and jailbreaks against LLM agents. I created HostileShop to see if I could use LLMs to write a framework that generates prompt injections against LLMs, by having LLMs attack other LLMs. It's LLMs all the way down. HostileShop generated prompt injections for a winning submission in OpenAI's GPT-OSS-20B RedTeam Contest. Since then, I have expanded HostileShop to generate injections for the entire LLM frontier, as well as to mutate jailbreaks to bypass prompt filters, adapt to LLM updates, and to give advice on performing injections against other agent systems. In this talk, I will give you an overview of LLM Agent hacking. I will cover LLM context window formats, LLM agents, agent vulnerability surface, and the prompting and efficiency insights that led to the success of HostileShop.

How to render cloud FPGAs useless (en)

Dirk

While FPGA developers usually try to minimize the power consumption of their designs, we approached the problem from the opposite perspective: what is the maximum power consumption that can be achieved or wasted on an FPGA? Short answer: we found that it’s easy to implement oscillators running at 6 GHz that can theoretically dissipate around 20 kW on a large cloud FPGA when driving the signal to all the available resources. It is interesting to note that this power density is not very far away from that of the surface of the sun. However, such power load jump is usually not a problem as it will trigger some protection circuitry. This led us to the next question: would a localized hotspot with such power density damage the chip if we remain within the typical power envelope of a cloud FPGA (~100 W)? While we could not “fry” the chip or induce permanent errors (and we tried several variants), we did observe that a few routing wires aged to become up to 70% slower in just a few days of stressing the chip. This basically means that such an FPGA cannot be rented out to cloud users without risking timing violations. In this talk, we will present how we optimized power wasting, how we measured wire latencies with ps accuracy, how we attacked 100 FPGA cloud instances and how we can protect FPGAs against such DOS attacks.