Deep Instinct Launches Advanced, GenAI-Based Security Analysis Assistant for Unknown Threats

Deep Instinct, the prevention-first cybersecurity company that stops unknown malware pre-execution with a purpose-built, AI-based deep learning (DL) framework, is unveiling Deep Instinct’s Artificial Neural Network Assistant (DIANNA), a prevention-first, generative AI (GenAI) cyber companion designed to offer explainability for unknown threats. Equipped with  revolutionary, expert-grade static malware analysis, DIANNA is an enterprise’s virtual team of malware analysts and incident response specialists that delivers deep analysis into all attacks—including those not yet discovered. 

DIANNA is composed of a large language model (LLM) that surfaces critical information into how unknown attacks are malicious in nature—not just generating a simple summary of attack data. Integrating with Deep Instinct's Prevention Platform, DIANNA delivers in-depth, easily consumed insights into both known and unknown attack behavior before a breach occurs. 

“DIANNA is the ultimate cyber companion for security teams,” said Yariv Fishman, chief product officer of Deep Instinct. “There are two factors that set DIANNA apart from other AI-powered chatbots. First, its unprecedented malware analysis compresses hours of work, requiring deep cyber threat expertise, into seconds. Second, DIANNA’s ability to analyze unknown threats, including scripts, documents, and raw binary files, is unmatched. Both of these capabilities build upon our prevention-first approach and allow security teams to focus on what truly matters.”

Deep Instinct’s latest innovation transcends traditional machine learning-based security tools, offering more than classification results, according to the company. DIANNA delivers robust analysis and reporting in an easily digestible format that empowers security teams to make informed decisions and prioritize threats with greater efficiency. Not only does this optimize security operation center (SOC) performance, it also reduces mean-time-to-repair (MTTR) and increases job satisfaction by eliminating tedious security tasks. 

To augment the power of security teams to fight the advanced attacks their organizations face, DIANNA offers the following: 

  • Unparalleled expertise for unknown threats, providing insights into unknown scripts, documents, and raw binaries
  • Code intent and activity translation into natural language, offering deep understanding of a code’s potential actions, intended design, what makes it malicious, and how it impacts systems
  • Enhanced visibility into the decision-making process of Deep Instinct's prevention models, enabling security teams to fine-tune their security posture
  • Expert-level analysis of threat delivery file types, including binaries, scripts, documents, shortcut files, and more
  • Streamlined workflows via DIANNA’s automation of tedious SOC tasks 

“With the rise in AI-generated attacks, organizations can no longer be complacent or reactive in how they approach cybersecurity. It’s time to fight AI with better AI, and raise greater awareness about the unknown threats impacting businesses,” said Lane Bess, CEO of Deep Instinct. “DIANNA provides vital threat explainability, enhances our prevention-first approach, and marks a strategic shift towards a more informed, efficient, and effective cybersecurity environment.”

To learn more about DIANNA, please visit