Advanced attacks on firmware and hardware

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Local LLMs
As computing power increases, the next generation of “AI PCs” will be able to run local large language models (LLMs) without having to rely on powerful external servers. This will allow PCs and users to take full advantage of AI, changing the way people interact with their devices.

On-premises LLMs promise to improve efficiency and performance, as well as provide security and privacy by operating independently of the Internet. However, on-premises models and the sensitive data they handle can make endpoints a big target for attackers if not properly protected.

Moreover, many companies are implementing chatbots philippines mobile database on LLM to improve the level and scale of customer service. However, AI technology can create new information security and privacy risks, such as potentially exposing sensitive data. This year, we may see cybercriminals attempt to manipulate chatbots to bypass security measures and gain access to sensitive information.
AI is helping to democratize technology by helping less-skilled users perform more complex tasks more efficiently. But while AI is improving organizations’ defenses, it can also help attackers launch attacks on lower system layers, such as firmware and hardware, which have been on the rise in recent years.

Historically, such attacks have required extensive technical knowledge, but AI is beginning to demonstrate the ability to lower these barriers. This could lead to more attempts by attackers to exploit low-level systems to gain a foothold below the operating system and industry-leading security software.