Shauli Zacks
At the cutting edge of cyber defense lies a tool designed not just to detect attackers—but to outsmart them. SafetyDetectives recently interviewed Mario Candela, the mastermind behind Beelzebub, a next-generation honeypot framework that blends artificial intelligence with cybersecurity expertise. With a background that spans from founding hacker forums as a teenager to joining the prestigious Honeynet Project, Candela has always chased innovation. His latest creation, Beelzebub, aims to revolutionize how we lure, monitor, and learn from malicious actors—without the traditional risks honeypots often carry. In this interview, Mario shares the story behind Beelzebub, how it’s changing the honeypot game, and where he sees the future of cyber deception heading.
Can you share a bit about your background and what led you to create Beelzebub?
I started developing when I was very young, around 10-11 years old. At 14, I founded a hacker forum, and at 22, I graduated with a degree in computer engineering. I’ve always followed my passion and hunger for knowledge! Now I’m a member of Honeynet, and in my free time, I work as an independent researcher, analyzing and counter-attacking botnets and malware. You can read my latest research on the Beelzebub Lab blog. During my research activities, I needed a secure and easy-to-configure honeypot, so I created the Beelzebub honeypot framework.
What sets Beelzebub apart from other honeypot frameworks in the cybersecurity landscape?
It’s the first LLM-based honeypot that behaves like a high-interaction honeypot, but you don’t need to constantly monitor it. With just one configuration file, you can implement multiple honeypots.
Honeypots have traditionally been a double-edged sword—valuable for detection but risky due to potential exploitation. How does Beelzebub address security concerns while maintaining effectiveness?
Thanks to its LLM plugin, Beelzebub functions as a super sandbox where it’s impossible to find exploits because all services are virtualized.
With the increasing use of AI in cybersecurity, how does Beelzebub leverage AI to enhance honeypot deception and attacker analysis?
Beelzebub uses AI to virtualize SSH and HTTP honeypots and has a crew of AI agents that work together like a real SOC (Security Operations Center).
Many organizations struggle to integrate honeypots into their existing security infrastructure. What advice would you give to companies looking to implement Beelzebub successfully?
Contact me at mario.candela@beelzebub.cloud, and I’ll be happy to guide you in the best way possible.
What future developments do you see for Beelzebub and the honeypot industry as a whole? Are there any upcoming features or trends we should watch for?
A public beta is already available that allows you to remotely monitor and configure your fleet of honeypots, manage and aggregate logs, and configure an alert manager. I’ve also developed an AI SOC connected to Beelzebub that analyzes attacks in real-time and produces automatic post-mortem reports.
