CyberToolKit

Looking at the news of the current year, I was triggered to know that, as per multiple cyber security reports, 2025 has already seen hundreds of deepfake incidents across the globe , with losses in the hundreds of millions of dollars. Deepfake is projected to grow from 500,000 shared files in 2023 to 8 million by 2025.   DeepStrike . While deepfakes started as entertaining experiments in AI, today they are one of the most disruptive forces in cyber security . Among these incidents, two stand out: The Most Shocking Case: Arup’s $25 Million Scam in Hong Kong In early 2025, an employee at the multinational engineering giant Arup attended what seemed like a routine video call with senior executives, including the CFO. During the call, he was instructed to transfer over US$25.6 million to external accounts. The horrifying twist: every single participant on that call was a deepfake avatar —their faces and voices generated by AI CNN . This case shattered assumptions about digital tru...

  I have come across two terms that often sound similar but actually mean very different things: AI for cyber security and AI security . At first, I found them confusing, but after reading resources like Microsoft’s What is AI Security? and KPMG’s insights on AI in Cybersecurity , I’ve started to understand the distinction more clearly. Here’s my explanation. What I Learned About AI Security AI security is basically about protecting the AI systems themselves. Since AI models are trained with huge amounts of data, attackers can try to mess with this process or even use the model against us. For example: Data poisoning : where someone adds bad data to corrupt how the AI learns. Adversarial attacks : where small changes in input data can fool the AI completely. Model inversion : where attackers try to pull sensitive information out of the model. According to Microsoft, the key ideas here are confidentiality, integrity, availability, and accountability....