AI-Powered Threat Detection Scenario Playbook

December 17, 20234 min read

Playbook Objectives

  • To simulate an advanced persistent threat (APT) utilising AI-powered tools to infiltrate and exfiltrate proprietary data from an organization.
  • To test and enhance the company’s incident response protocols and the effectiveness of AI-powered threat detection systems.
  • To provide analysts and IT security teams with hands-on experience in identifying, containing, and eradicating a sophisticated cyberthreat.
  • To evaluate the security posture of the network and identify potential areas of improvement.

Difficulty Level

  • Advanced: This scenario involves a sophisticated, multi-stage attack requiring complex defensive strategies and a high level of familiarity with AI-based security tools.


  • Company Name: SolarNova Corp
  • Network Infrastructure: Cloud-based services, internal data centers, and remote office connectivity.
  • Systems: Web servers, application servers, database servers, end-user workstations, and BYOD (Bring Your Own Device) mobile devices.
  • Users Involved: Cindy (CIO), John (Lead Security Analyst), and Jane (Network Administrator).
  • SolarNova Corp is a leading company in the renewable energy sector, renowned for developing cutting-edge solar panel technologies. With various global patents and high-profile contracts, protecting intellectual property and customer data from cyber threats is crucial. Due to the sensitive nature of their work, they are a prime target for sophisticated cyber-espionage.
  • The company is undertaking this cyber range exercise with an AI-Powered Threat Detection scenario to stress test their cyber defences. The goal is to ensure that their cutting-edge AI-driven security solutions can effectively detect and respond to emerging threats that leverage AI for malicious purposes, such as evading traditional security measures and learning from the environment to maximize attack impact.
  • The scenario envisions a state-sponsored threat actor with access to AI-based cyber tools, attempting to compromise SolarNova Corp’s network, establish a foothold, and exfiltrate R&D data, causing significant intellectual and financial damage.


  • Advanced Persistent Threats (APTs)
  • Artificial Intelligence and Machine Learning in Cybersecurity
  • Data Exfiltration

Exercise Attack Steps

  • Initial Reconnaissance:
    • The threat actor uses AI-powered reconnaissance tools to map out SolarNova’s external-facing infrastructure, identifying vulnerabilities in web applications and network devices.
    • Engage in passive scanning techniques to avoid detection by traditional security tools.
  • Initial Compromise:
    • Utilize machine learning algorithms to craft and deliver a highly sophisticated spear-phishing campaign targeting key personnel.
    • A malicious attachment, seemingly a regular document, is encrypted to evade signature-based detection and is designed to trigger upon opening.
  • Establish Foothold:
    • Once executed, the document deploys an AI-powered malware that adapts its behavior to avoid heuristic analysis and sandboxing environments.
    • The malware creates a covert backdoor that camouflages with regular traffic using AI to mimic legitimate network patterns.
  • Privilege Escalation:
    • The malware uses an AI-based module to observe and learn daily administrative activities, identifying patterns to exploit for elevating privileges without raising alarms.
    • Automated lateral movement tools are deployed to spread across the network, exfiltrating credentials and compromising critical systems efficiently.
  • Data Exfiltration:
    • AI algorithms analyze and prioritize data based on context and value, stealthily packaging and encrypting R&D information for exfiltration.
    • Utilize machine learning to determine optimal exfiltration timing, ensuring that large data transfers coincide with peak traffic hours to blend in.
  • Maintain Presence:
    • Implement AI-driven tactics to create persistent, adaptive mechanisms within the network that evolve with detection attempts, ensuring long-term access for continued espionage.
  • Eradication and Remediation:
    • Participants are challenged to use AI-enhanced security tools to detect and eradicate the threat presence from the network.
    • Cyber range technologies help identify anomalies in system behaviours and traffic patterns indicating AI-driven intrusions.
  • Review and Analysis:
    • After-action reporting assisted by AI for a comprehensive review of threats, incidents, response efficacy, and recommendations for enhancing security posture.