An interview with contributor Ulrik Lykke, a researcher and investor in the digital asset space. 

Meet the Writer: Hacker Noon's Contributor Ulrik Lykke, Head of Research @ Bitcoin Global Macro

Lordmancer II (http://lordmancer2.io) is a mobile MMO RPG in which players can use crypto token Lord Coin for in-game trading. To make more use of Lord Coins, players should have an easy way to buy and sell Lord Coins for either fiat money or cryptocurrency.

Lordmancer II partners with Lykke to create a customized blockchain wallet

Testing four LLMs on Emotet scripts, GPT-4 led in deobfuscation, but all models struggled with hallucinations and prompt limitations.

Model Performance and Pitfalls in Automated Malware Deobfuscation

Using 2,000 real Emotet dropper scripts, the experiment tests LLMs’ ability to deobfuscate malware and extract threat intel at scale.

AI Detectives and the Case of the Disguised Droppers

LLMs can automate extracting obfuscated malware payloads, streamlining threat intelligence even as attackers change packing and obfuscation tactics.

Extracting Hidden Malware Payloads with AI-Powered LLMs

LLMs boost cybersecurity by automating threat detection, analysis, and compliance, but can also be misused for attacks and malware development.

The Pros and Cons of LLMs in Cybersecurity Practice

Malware uses packers, cryptors, and obfuscators to evade static analysis, challenging analysts to adapt detection and analysis methods.

Why Static Analysis Struggles Against Modern Malware

LLMs show strong potential for automating malware deobfuscation, efficiently analyzing real Emotet scripts and enhancing future threat intelligence pipelines

The Future of Malware Analysis: LLMs and Automated Deobfuscation

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