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Beelzebub

Full-stack AI deception platform to catch advanced threats with zero false positives and cut SOC costs.

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Overview

Beelzebub is an innovative AI-powered deception platform designed to revolutionize how organizations detect and respond to advanced cyber threats. Unlike traditional security tools that often fail once attackers breach initial defenses, Beelzebub focuses on catching lateral movement within the infrastructure. It achieves this by deploying intelligent deceptions across a wide array of assets, including Kubernetes clusters, APIs, AI agent tools, and IoT devices, creating a highly convincing environment to lure and trap adversaries.

The core value proposition of Beelzebub lies in its ability to deliver zero false positives, ensuring that security teams only respond to genuine threats. This precision significantly slashes the Mean Time To Respond (MTTR) from hours to mere seconds, drastically improving incident response capabilities. Furthermore, by streamlining threat detection and reducing false alarms, Beelzebub promises to cut Security Operations Center (SOC) costs by up to 60%, making it a cost-effective solution for enhancing an organization's overall security posture.

Best For

Detecting advanced persistent threats (APTs) and insider threats.
Protecting critical infrastructure like Kubernetes clusters and IoT devices.
Enhancing security posture for organizations with complex API ecosystems.
Reducing the workload and improving efficiency of Security Operations Centers (SOCs).
Safely analyzing threats and attacker behavior in a controlled deception environment.
Academic and research programs focused on deception technology and cybersecurity.

Key Features

AI-powered deception
Full-stack infrastructure coverage (Kubernetes, APIs, AI agent tools, IoT)
Lateral movement detection
Zero false positives
Reduced MTTR (Mean Time To Respond)
Open-source core with 1,500+ GitHub stars
Continuous development for over 36 months
Community contributions via GitHub

Pros & Cons

Pros

  • Highly effective at detecting advanced threats that bypass traditional security.
  • Provides full-stack deception, covering a wide range of infrastructure components.
  • Boasts zero false positives, reducing alert fatigue for security teams.
  • Significantly reduces MTTR, improving incident response times.
  • Open-source core fosters community trust and allows for transparency and contributions.
  • Proven reliability with over 36 months of continuous development.
  • Potential for substantial cost savings in SOC operations.

Cons

  • Requires integration into existing infrastructure, which might be complex for some organizations.
  • The effectiveness relies on the quality and realism of the deployed deceptions.
  • May require specialized knowledge to configure and manage the deception environment effectively.
  • Specific pricing information is not readily available on the public website, requiring a demo booking.
  • Newer technology (AI deception) might have a learning curve for security teams unfamiliar with the concept.

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