Gemini 1.5 Pro – Powered With Automated Malware Analysis To Detect Zero-Day

Google has introduced Gemini 1.5 Pro for malware analysis, an advanced AI tool capable of processing up to 1 million tokens. This tool revolutionizes automated malware analysis and marks a significant leap forward in the ongoing battle against the ever-evolving threat landscape.

Gemini 1.5 Pro for automated malware analysis successfully identified a zero-day threat undetected by any anti-virus or sandbox on VirusTotal. The tool processed the decompiled code and issued a malicious verdict, revealing suspicious functionalities aimed at stealing cryptocurrency and evading detection.

“This showcases Gemini’s ability to go beyond simple pattern matching or ML classification and leverage its deep understanding of code behavior to identify malicious intent, even in previously unseen threats,” said Smith.

The Limitations of Traditional Malware Analysis

Historically, Malware Analysis has relied heavily on static and dynamic analysis techniques. Static analysis involves examining the malware without executing it, providing insights into its code structure and logic.

On the other hand, dynamic analysis observes the malware in execution, offering a glimpse into its behavior in a controlled environment. While these methods are foundational, they face limitations in handling the increasing complexity and volume of malware, often requiring extensive manual effort and expertise.

Parallel to these traditional techniques, AI and machine learning have been explored to enhance malware detection.


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These technologies have shown promise in classifying and clustering malware based on behavioral patterns and anomalies. However, their effectiveness is challenged by new and sophisticated malware variants that can evade detection, highlighting a gap in cybersecurity defenses.

Enter Gemini 1.5 Pro: A New Era of Automated Malware Analysis

Gemini 1.5 Pro emerges as a groundbreaking tool designed to address the limitations of existing malware analysis methods. It leverages generative AI to automate and scale malware analysis, particularly reverse engineering.

With the capability to process prompts of up to 1 million tokens, Gemini 1.5 Pro significantly expands the scope of automated analysis, enabling a comprehensive examination of complex malware samples in their entirety.

“By analyzing the entire code at once, Gemini 1.5 Pro gains a comprehensive understanding of the malware, allowing for more accurate and comprehensive analysis,” explained John Smith, Lead Researcher on the Gemini project.

Key Features and Advancements

  • Increased Processing Capacity: Gemini 1.5 Pro can handle up to 1 million tokens and analyze large and complex malware samples in a single pass, providing a holistic understanding of their functionality and behavior.
  • Code Interpretation: Unlike traditional methods that primarily identify patterns or similarities, Gemini 1.5 Pro interprets the intent and purpose of the code. It is trained on a vast dataset of code, including assembly language and high-level languages, allowing it to emulate the reasoning of a malware analyst.
  • Detailed Analysis Reports: The tool generates summary reports in human-readable language, offering detailed insights into the malware’s potential actions and attack vectors. This feature enhances the accessibility and efficiency of the analysis process.

The analysis of WannaCry binaries demonstrated Gemini 1.5 Pro’s capabilities, showcasing its ability to accurately identify ransomware characteristics and potential attack vectors.

Gemini 1.5 Pro For Malware Analysis

Furthermore, its performance in analyzing unknown malware samples illustrates its potential to detect and understand never-before-seen threats, a critical advantage in proactive cybersecurity defense.

Let’s explore a practical case study to examine how Gemini 1.5 Pro performs in analyzing decompiled code with a representative malware sample.

Google processed two WannaCry binaries automatically using the Hex-Rays decompiler, without adding any annotations or additional context.

Credits: Google.

This approach resulted in two C code files, one 268 KB and the other 231 KB in size, which together amount to more than 280,000 tokens for processing by the LLM.

Detecting Zero-Day

The ability of malware analysis tools to identify novel threats that evade traditional security measures and to provide proactive defense against zero-day attacks is a crucial metric for determining their effectiveness.

In this context, we explore an instance where the executable file “medui.exe,” which went undetected by all antivirus programs and sandboxes on VirusTotal, was analyzed.

Gemini 1.5 Pro analyzed the 833 KB file in just 27 seconds, breaking it down into 189,080 tokens, and producing a thorough malware analysis report from a single examination.

Gemini 1.5 Pro For Malware Analysis

This rapid and detailed analysis pinpointed several suspicious features, leading Gemini 1.5 Pro to classify the file as malicious.

The analysis determined that the malware’s main purpose was to steal cryptocurrency by manipulating Bitcoin transactions and to avoid detection by disabling security software.

This instance demonstrates Gemini 1.5 Pro’s advanced capabilities in identifying and understanding malicious code behaviors beyond traditional pattern recognition or machine learning classifications, highlighting its effectiveness in addressing novel security threats.

Despite its advancements, Gemini 1.5 Pro, like any tool, faces challenges. These include dealing with malware obfuscation techniques, increasing binary sizes, and evolving attack methods.

To get around these problems and keep automated malware analysis working well, generative AI models and preprocessing techniques will need to keep getting better.

Gemini 1.5 Pro represents a significant milestone in cybersecurity, offering a scalable and automated solution to malware analysis challenges.

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BALAJI is an Ex-Security Researcher (Threat Research Labs) at Comodo Cybersecurity. Editor-in-Chief & Co-Founder - Cyber Security News & GBHackers On Security.