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2024-04-29 14:00:00 | De l'assistant à l'analyste: la puissance de Gemini 1.5 Pro pour l'analyse des logiciels malveillants From Assistant to Analyst: The Power of Gemini 1.5 Pro for Malware Analysis (lien direct) |
Executive Summary A growing amount of malware has naturally increased workloads for defenders and particularly malware analysts, creating a need for improved automation and approaches to dealing with this classic threat. With the recent rise in generative AI tools, we decided to put our own Gemini 1.5 Pro to the test to see how it performed at analyzing malware. By providing code and using a simple prompt, we asked Gemini 1.5 Pro to determine if the file was malicious, and also to provide a list of activities and indicators of compromise. We did this for multiple malware files, testing with both decompiled and disassembled code, and Gemini 1.5 Pro was notably accurate each time, generating summary reports in human-readable language. Gemini 1.5 Pro was even able to make an accurate determination of code that - at the time - was receiving zero detections on VirusTotal. In our testing with other similar gen AI tools, we were required to divide the code into chunks, which led to vague and non-specific outcomes, and affected the overall analysis. Gemini 1.5 Pro, however, processed the entire code in a single pass, and often in about 30 to 40 seconds. Introduction The explosive growth of malware continues to challenge traditional, manual analysis methods, underscoring the urgent need for improved automation and innovative approaches. Generative AI models have become invaluable in some aspects of malware analysis, yet their effectiveness in handling large and complex malware samples has been limited. The introduction of Gemini 1.5 Pro, capable of processing up to 1 million tokens, marks a significant breakthrough. This advancement not only empowers AI to function as a powerful assistant in automating the malware analysis workflow but also significantly scales up the automation of code analysis. By substantially increasing the processing capacity, Gemini 1.5 Pro paves the way for a more adaptive and robust approach to cybersecurity, helping analysts manage the asymmetric volume of threats more effectively and efficiently. Traditional Techniques for Automated Malware Analysis The foundation of automated malware analysis is built on a combination of static and dynamic analysis techniques, both of which play crucial roles in dissecting and understanding malware behavior. Static analysis involves examining the malware without executing it, providing insights into its code structure and unobfuscated logic. Dynamic analysis, on the other hand, involves observing the execution of the malware in a controlled environment to monitor its behavior, regardless of obfuscation. Together, these techniques are leveraged to gain a comprehensive understanding of malware. Parallel to these techniques, AI and machine learning (ML) have increasingly been employed to classify and cluster malware based on behavioral patterns, signatures, and anomalies. These methodologies have ranged from supervised learning, where models are trained on labeled datasets, to unsupervised learning for clustering, which identifies patterns without predefined labels to group similar malware. | Malware Hack Tool Vulnerability Threat Studies Prediction Cloud Conference | Wannacry | ★★★ |
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2023-08-29 10:00:00 | Lutte contre les logiciels malveillants dans la chaîne d'approvisionnement industrielle Battling malware in the industrial supply chain (lien direct) |
The content of this post is solely the responsibility of the author. AT&T does not adopt or endorse any of the views, positions, or information provided by the author in this article. Here\'s how organizations can eliminate content-based malware in ICS/OT supply chains. As the Industrial Internet of Things (IIoT) landscape expands, ICS and OT networks are more connected than ever to various enterprise systems and cloud services. This new level of connectivity, while offering benefits, also paves the way for targeted and supply chain attacks, making them easier to carry out and broadening their potential effects. A prominent example of supply chain vulnerability is the 2020 SolarWinds Orion breach. In this sophisticated attack: Two distinct types of malware, "Sunburst" and "Supernova," were secretly placed into an authorized software update. Over 17,000 organizations downloaded the update, and the malware managed to evade various security measures. Once activated, the malware connected to an Internet-based command and control (C2) server using what appeared to be a harmless HTTPS connection. The C2 traffic was cleverly hidden using steganography, making detection even more challenging. The threat actors then remotely controlled the malware through their C2, affecting up to 200 organizations. While this incident led to widespread IT infiltration, it did not directly affect OT systems. In contrast, other attacks have had direct impacts on OT. In 2014, a malware known as Havex was hidden in IT product downloads and used to breach IT/OT firewalls, gathering intelligence from OT networks. This demonstrated how a compromised IT product in the supply chain could lead to OT consequences. Similarly, in 2017, the NotPetya malware was concealed in a software update for a widely-used tax program in Ukraine. Though primarily affecting IT networks, the malware caused shutdowns in industrial operations, illustrating how a corrupted element in the supply chain can have far-reaching effects on both IT and OT systems. These real-world incidents emphasize the multifaceted nature of cybersecurity risks within interconnected ICS/OT systems. They serve as a prelude to a deeper exploration of specific challenges and vulnerabilities, including: Malware attacks on ICS/OT: Specific targeting of components can disrupt operations and cause physical damage. Third-party vulnerabilities: Integration of third-party systems within the supply chain can create exploitable weak points. Data integrity issues: Unauthorized data manipulation within ICS/OT systems can lead to faulty decision-making. Access control challenges: Proper identity and access management within complex environments are crucial. Compliance with best practices: Adherence to guidelines such as NIST\'s best practices is essential for resilience. Rising threats in manufacturing: Unique challenges include intellectual property theft and process disruptions. Traditional defenses are proving inadequate, and a multifaceted strategy, including technologies like Content Disarm and Reconstruction (CDR), is required to safeguard these vital systems. Supply chain defense: The power of content disarm and reconstruction Content Disarm and Reconstruction (CDR) is a cutting-edge technology. It operates on a simple, yet powerful premise based on the Zero Trust principle: all files could be malicious. What does CDR do? In the complex cybersecurity landscape, CDR stands as a unique solution, transforming the way we approach file safety. Sanitizes and rebuilds files: By treating every file as potentially harmful, CDR ensures they are safe for use while mainta | Malware Vulnerability Threat Industrial Cloud | NotPetya Wannacry Solardwinds | ★★ |
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