Cybersecurity AI

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How multi-agent AI economics influence business automation

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Managing the economics of multi-agent AI now dictates the financial viability of modern business automation workflows. Organisations progressing past standard chat interfaces into multi-agent applications face two primary constraints. The first issue is the thinking tax; complex autonomous agents need to reason at each stage, making the reliance on massive architectures for every subtask too […]

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State-sponsored hackers exploit AI for advanced cyberattacks

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State-sponsored hackers are exploiting AI to accelerate cyberattacks, with threat actors from Iran, North Korea, China, and Russia weaponising models like Google’s Gemini to craft sophisticated phishing campaigns and develop malware, according to a new report from Google’s Threat Intelligence Group (GTIG). The quarterly AI Threat Tracker report, released today, reveals how government-backed attackers have

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Google, Sony, and Okta back Resemble AI’s push into deepfake detection

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Resemble AI has raised US$13 million in a new strategic investment round for AI deepfake detection. The funding brings its total venture investment to US$25 million, with participation from Berkeley CalFund, Berkeley Frontier Fund, Comcast Ventures, Craft Ventures, Gentree, Google’s AI Futures Fund, IAG Capital Partners, and others. The funding comes as organisations are under

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Anthropic just revealed how AI-orchestrated cyberattacks actually work—Here’s what enterprises need to know

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For years, cybersecurity experts debated when—not if—artificial intelligence would cross the threshold from advisor to autonomous attacker. That theoretical milestone has arrived.  Anthropic’s recent investigation into a Chinese state-sponsored operation has documented the first case of AI-orchestrated cyberattacks executing at scale with minimal human oversight, fundamentally altering what enterprises must prepare for in the threat landscape ahead. The campaign,

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Adversarial learning breakthrough enables real-time AI security

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The ability to execute adversarial learning for real-time AI security offers a decisive advantage over static defence mechanisms. The emergence of AI-driven attacks – utilising reinforcement learning (RL) and Large Language Model (LLM) capabilities – has created a class of “vibe hacking” and adaptive threats that mutate faster than human teams can respond. This represents

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