AI in cyber defence: Trend Micro flags rising risks

Trend Micro finds that 81% of global firms now use AI in cybersecurity, but 94% worry it may expand their threat surface. The report urges integrating security from day one.

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AI in cyber defence Trend Micro flags rising risks

AI in cyber defence: Trend Micro flags rising risks

AI is becoming central to cybersecurity strategies, but it’s also raising new alarms. According to a recent study by Trend Micro, 81% of global organisations are already using AI-based tools to bolster their cyber defences. An additional 16% are exploring its potential. However, the same study shows rising unease about how AI might also widen the attack surface.

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Sharda Tickoo, Country Manager for India & SAARC, Trend Micro, commented, “AI can transform cyber defence — from detecting anomalies faster to automating routine tasks. But it must be secured from the outset, or the risks could outweigh the benefits.”

The report highlights that more than half of respondents use AI for asset discovery, risk ranking and anomaly detection. Automation and AI are now top priorities for 42% of organisations looking to strengthen their cybersecurity posture over the next year.

Yet optimism is tempered by caution. A significant 94% of respondents believe that AI will increase their cyber risk exposure within the next three to five years. Many expect more complex AI-driven attacks to emerge, forcing security leaders to rethink strategies. Key concerns include data processing transparency, risks from untrusted models, and regulatory challenges due to the growing use of APIs, endpoints and shadow IT.

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The study also uncovered seven zero-day vulnerabilities across major AI frameworks. Notably, the NVIDIA Triton Inference Server drew the most attacks. Other exploited platforms included Chroma, Redis and the NVIDIA Container Toolkit, with some compromised using a single flaw.

As enterprises continue integrating AI into their IT environments, Trend Micro urges organisations to embed robust security measures early in the AI lifecycle, not as an afterthought. 

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