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| Src | Date (GMT) | Titre | Description | Tags | Stories | Notes |
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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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2024-04-25 10:00:00 | Pole Voûte: cyber-menaces aux élections mondiales Poll Vaulting: Cyber Threats to Global Elections (lien direct) |
Written by: Kelli Vanderlee, Jamie Collier
Executive Summary The election cybersecurity landscape globally is characterized by a diversity of targets, tactics, and threats. Elections attract threat activity from a variety of threat actors including: state-sponsored actors, cyber criminals, hacktivists, insiders, and information operations as-a-service entities. Mandiant assesses with high confidence that state-sponsored actors pose the most serious cybersecurity risk to elections. Operations targeting election-related infrastructure can combine cyber intrusion activity, disruptive and destructive capabilities, and information operations, which include elements of public-facing advertisement and amplification of threat activity claims. Successful targeting does not automatically translate to high impact. Many threat actors have struggled to influence or achieve significant effects, despite their best efforts. When we look across the globe we find that the attack surface of an election involves a wide variety of entities beyond voting machines and voter registries. In fact, our observations of past cycles indicate that cyber operations target the major players involved in campaigning, political parties, news and social media more frequently than actual election infrastructure. Securing elections requires a comprehensive understanding of many types of threats and tactics, from distributed denial of service (DDoS) to data theft to deepfakes, that are likely to impact elections in 2024. It is vital to understand the variety of relevant threat vectors and how they relate, and to ensure mitigation strategies are in place to address the full scope of potential activity. Election organizations should consider steps to harden infrastructure against common attacks, and utilize account security tools such as Google\'s Advanced Protection Program to protect high-risk accounts. Introduction The 2024 global election cybersecurity landscape is characterized by a diversity of targets, tactics, and threats. An expansive ecosystem of systems, administrators, campaign infrastructure, and public communications venues must be secured against a diverse array of operators and methods. Any election cybersecurity strategy should begin with a survey of the threat landscape to build a more proactive and tailored security posture. The cybersecurity community must keep pace as more than two billion voters are expected to head to the polls in 2024. With elections in more than an estimated 50 countries, there is an opportunity to dynamically track how threats to democracy evolve. Understanding how threats are targeting one country will enable us to better anticipate and prepare for upcoming elections globally. At the same time, we must also appreciate the unique context of different countries. Election threats to South Africa, India, and the United States will inevitably differ in some regard. In either case, there is an opportunity for us to prepare with the advantage of intelligence. |
Ransomware Malware Hack Tool Vulnerability Threat Legislation Cloud Technical | APT 40 APT 29 APT 28 APT 43 APT 31 APT 42 | ★★★ |
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2022-11-29 15:00:00 | Vol décentralisé: disséquer le piratage du pont nomade et suivre l'argent Decentralized Robbery: Dissecting the Nomad Bridge Hack and Following the Money (lien direct) |
Dans cet article de blog, Mandiant jette un aperçu plus approfondi de la façon dont le contrat de contrat de Nomad Bridge a été exploité et analyse les transactions en chaîne post-compromis à l'aide de la société de prévention de la cybercriminalité Cyber Cyber Cyber Cyber Cyber Cyber.Équipe Six \'s (CT6) Blockchain Investigative Software, cryptovoyant.
arrière-plan
Début août 2022, le public a observé une autre attaque de pont, cette fois contre le pont tokad - un "pont" permet d'interopérabilité entre deux blockchains et est décrit plus en détail dansce post.Dans ce cas, une mise à jour du contrat intelligent du pont \\ a conduit à un état où transactions spécialement conçues
In this blog post, Mandiant takes a deeper look into how the Nomad bridge smart-contract was exploited and analyzes the on-chain transactions post-compromise using cybercrime prevention company Cyber Team Six\'s (CT6) blockchain investigative software, CryptoVoyant. Background In early August 2022, the public observed yet another bridge attack, this time against the Nomad token bridge-a “bridge” allows interoperability between two blockchains and is further described in this post. In this case an update to the bridge\'s smart contract led to a state where specially crafted transactions |
Hack | ★★★★ |
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