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How to detect and prevent attackers from using these various techniques Obfuscation is an important technique for protecting software that also carries risks, especially when used by malware authors. In this article, we examine obfuscation, its effects, and responses to it. What Is Obfuscation? Obfuscation is the technique of intentionally making information difficult to read, especially in computer coding. An important use case is data obfuscation, in which sensitive data is made unrecognizable to protect it from unauthorized access. Various methods are used for this.  For example, only the last four digits of a credit card number are often displayed, while the remaining digits are replaced by Xs or asterisks. In contrast, encryption involves converting data into an unreadable form that can only be decrypted using a special key. Obfuscation In Code When computer code is obfuscated, complex language and redundant logic are used to make the code difficult to understand. The a...

Google has developed a new framework called Project Naptime that it says enables a large language model (LLM) to carry out vulnerability research with an aim to improve automated discovery approaches. "The Naptime architecture is centered around the interaction between an AI agent and a target codebase," Google Project Zero researchers Sergei Glazunov and Mark Brand said . "The agent is provided with a set of specialized tools designed to mimic the workflow of a human security researcher." The initiative is so named for the fact that it allows humans to "take regular naps" while it assists with vulnerability research and automating variant analysis. The approach, at its core, seeks to take advantage of advances in code comprehension and general reasoning ability of LLMs, thus allowing them to replicate human behavior when it comes to identifying and demonstrating security vulnerabilities. It encompasses several components such as a Code Browser tool...

Every week seems to bring news of another data breach, and it's no surprise why: securing sensitive data has become harder than ever. And it's not just because companies are dealing with orders of magnitude more data. Data flows and user roles are constantly shifting, and data is stored across multiple technologies and cloud environments. Not to mention, compliance requirements are only getting stricter and more elaborate.  The problem is that while the data landscape has evolved rapidly, the usual strategies for securing that data are stuck in the past. Gone are the days when data lived in predictable places, with access controlled by a chosen few. Today, practically every department in the business needs to use customer data, and AI adoption means huge datasets, and a constant flux of permissions, use cases, and tools. Security teams are struggling to implement effective strategies for securing sensitive data, and a new crop of tools, called data security platforms, have appear...