AI is turning stealth attacks into the new normal, exposing hidden risks across systems, supply chains, and enterprise infrastructure at scale.

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Recently, Anthropic introduced Claude Mythos Preview, a general-purpose model with advanced coding and agentic capabilities, to select organisations as part of a new initiative called Project Glasswing. The model has the ability to autonomously find thousands of high-severity, zero-day vulnerabilities in major operating systems and web browsers. Obviously, the waves were felt in the cybersecurity space for better and for worse.

However, unlike the SaaSPocalypse, Claude Mythos is not going to replace cybersecurity professionals. While that is some good news in a world that is scared of AI replacing them or making their roles redundant, the ugly side is that the very tech will also amplify the scale of cyberattacks. 

This makes us ponder: how has AI increased security risks? And are these risks only restricted to models, or do they pose a more severe threat? If yes, how are we planning to deal with it? Let’s find out in this edition of The AI Shift.

The Silent Evolution Of Cyber Threats 

For years, cybersecurity evolved alongside infrastructure shifts — from web applications to cloud. With AI, that progression has taken a more complex turn.

Unlike earlier layers, AI is not just an interface sitting atop systems. It is deeply embedded in enterprise workflows, decision-making engines, and data pipelines. 

At the application layer, attacks such as prompt injection are already emerging, where malicious instructions are embedded into inputs to manipulate model behaviour. 

But as JP Mishra, founder and CEO of Deep Algorithms, an Indian cybersecurity company that primarily serves the BFSI sector, pointed out, the bigger concern is how invisible these attacks are.

But as JP Mishra, founder and CEO of Deep Algorithms, an Indian cybersecurity company that primarily serves the BFSI sector, pointed out, the bigger concern is how invisible these attacks are.

Unlike traditional exploits, these attacks don’t look malicious. They resemble normal text, documents, or queries, making it difficult for both humans and systems to distinguish intent. 

“The AI might treat something that looks harmless to us as a command,” he........

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