Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

AI systems learn from vast amounts of data and then generalize. That power is useful and also risky. Sensitive data can slip into prompts. Proprietary datasets can be memorized by models. Attackers can steer models to reveal secrets or corrupt results. Meanwhile, your company is probably experimenting with multiple AI tools at once. That creates hidden data flows and inconsistent controls. “Traditional” app security isn’t enough.

In 2025, machine identities outnumber human identities by a factor of 40 to 1. Every connected sensor, gateway, vehicle, and robot depends on a digital credential to prove its authenticity and secure its data. These digital credentials serve as unique identifiers for devices, enabling secure communications and access control.

A new survey found that 50% of UK residents aged 16 to 34 cite deepfake nudes as their top worry related to AI technology, SecurityBrief reports. The survey, published by VerifyLabs, found that 35% of Brits across all age groups said sexualized deepfakes of themselves or their children were their top concern. “The study indicated that more than one in three respondents (36%) are also worried about the impact deepfakes could have on their family and friends,” SecurityBrief writes.

CYJAX has identified a growing trend of AI-based tools being developed and shared across threat actor forums for fraudulent and cybercriminal purposes, highlighting the need for proactive monitoring and defence against evolving AI-driven threats.

In late 2022, AI exploded into the mainstream with OpenAI’s ChatGPT, starting an AI-fuelled shift in both everyday life and the cyber threat landscape. Just as quickly as everyday users rushed to adopt the technology, so did threat actors. From generating phishing pretexts to writing malware and crafting deepfakes, AI systems have become both a new tool and a new target.