AI security

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QA Engineer

Testing Beyond Pass or Fail: A QA Engineer’s Lessons from IMDA’s LLM Testing Starter Kit at Spritle

I’ve been in QA for a few years now. I know how testing works. You write a test case. You define the expected result. You run it. It either passes or fails. Simple. So when our team started working on an AI-powered feature, I thought, okay, same process. Different kind of input, but same idea. […]

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IMDA

Lessons from IMDA’s LLM Testing Starter Kit: An AI Assurance Perspective

Quality Assurance has always been about understanding risk and validating systems before they reach production. After more than eight years in QA and now working in AI security, governance, and red teaming, I often compare traditional testing practices with the challenges introduced by AI systems. While the risks have evolved from software defects to hallucinations,

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Google made agentic AI governance a product. Enterprises still have to catch up.

Two weeks ago at Google Cloud Next ’26 in Las Vegas, Google did something the enterprise AI industry has been dancing around for the better part of two years: it made agentic AI governance a native product feature, not an afterthought. The centrepiece announcement was the Gemini Enterprise Agent Platform, pitched as the successor to Vertex AI

Google made agentic AI governance a product. Enterprises still have to catch up. Read More »

Anthropic’s Mythos AI model sparks fears of turbocharged hacking

Anthropic’s new Mythos AI model is raising concern among governments and companies that it could outpace current cyber security defenses, turbocharge hacking, and expose weaknesses faster than they can be fixed. The San Francisco-based startup released a cyber-focused model this month, which has shown the ability to detect software flaws faster than humans but also

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Anthropic locked down its most powerful AI Model over cybersecurity fears–then put it to work

Anthropic’s most capable AI model has already found thousands of AI cybersecurity vulnerabilities across every major operating system and web browser. The company’s response was not to release it, but to quietly hand it to the organisations responsible for keeping the internet running. That model is Claude Mythos Preview, and the initiative is called Project Glasswing.

Anthropic locked down its most powerful AI Model over cybersecurity fears–then put it to work Read More »

Anthropic keeps new AI model private after it finds thousands of external vulnerabilities

Anthropic’s most capable AI model has already found thousands of AI cybersecurity vulnerabilities across every major operating system and web browser. The company’s response was not to release it, but to quietly hand it to the organisations responsible for keeping the internet running. That model is Claude Mythos Preview, and the initiative is called Project Glasswing.

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AI Risk & Compliance in 2026: Why QA Teams Must Lead the Shift

Artificial Intelligence is no longer a futuristic concept or an experimental capability. In 2026, AI has firmly embedded itself into core business operations—powering decisions in hiring, finance, healthcare, customer experience, and beyond. This shift brings a fundamental change: AI risk is now business risk. For Quality Engineering teams, especially QA leaders, this marks a turning

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Attackers prompted Gemini over 100,000 times while trying to clone it, Google says

On Thursday, Google announced that “commercially motivated” actors have attempted to clone knowledge from its Gemini AI chatbot by simply prompting it. One adversarial session reportedly prompted the model more than 100,000 times across various non-English languages, collecting responses ostensibly to train a cheaper copycat. Google published the findings in what amounts to a quarterly

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AI companies want you to stop chatting with bots and start managing them

On Thursday, Anthropic and OpenAI shipped products built around the same idea: instead of chatting with a single AI assistant, users should be managing teams of AI agents that divide up work and run in parallel. The simultaneous releases are part of a gradual shift across the industry, from AI as a conversation partner to

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The rise of Moltbook suggests viral AI prompts may be the next big security threat

On November 2, 1988, graduate student Robert Morris released a self-replicating program into the early Internet. Within 24 hours, the Morris worm had infected roughly 10 percent of all connected computers, crashing systems at Harvard, Stanford, NASA, and Lawrence Livermore National Laboratory. The worm exploited security flaws in Unix systems that administrators knew existed but

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