AI security

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Runaway Foundation Models Prove We Must Prepare For A Sci-Fi Cyber Disaster

ai, AI (Artificial Intelligence), AI guardrails, AI security, anthropic, Artificial Intelligence, cybersecurity, data breach, hugging face, Mtea, OpenAI, Rob Enderle, sandbox

When an autonomous AI escapes its sandbox to hack a major tech company, science fiction becomes science fact. It is time for executives to take rogue foundation models incredibly seriously. I have spent decades analyzing the technology industry, observing the […] The post Runaway Foundation Models Prove We Must Prepare For A Sci-Fi Cyber Disaster […]

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The Shadow AI Beneath the Surface: Finding Unsanctioned Agents Before They Bite

agent discovery, ai, AI (Artificial Intelligence), AI security, Artificial Intelligence, credential exposure, machine identity, shadow AI

TL;DR Shadow AI is not merely unapproved software. An unsanctioned agent, copilot, script, or autonomous workflow can authenticate as a machine identity, call a model provider, read enterprise data, invoke tools, modify systems, and create spend without appearing in a centralized AI inventory. The practical discovery method is evidence correlation. Start with model-provider traffic, provider

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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

Adversarial Testing, ai, AI (Artificial Intelligence), AI Application Testing, AI Governance, AI Product Quality, AI Quality Assurance, AI security, AI Security Testing, AI Testing, Artificial Intelligence, Bias Testing, Generative AI, Generative AI Testing, Hallucination Testing, IMDA LLM Testing Starter Kit, LLM Testing, Prompt injection testing, QA Best Practices, QA Engineering, Quality Assurance, Red Teaming, Responsible AI, Semantic Similarity Testing, Software Testing, Spritle Blog, SpritleSoftware

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

Agentic AI security, ai, AI (Artificial Intelligence), AI Assurance, AI assurance framework, AI Governance, AI governance and compliance, AI red teaming, AI Risk Management, ai safety testing, AI security, Artificial Intelligence, Enterprise AI assurance, Large Language Models (LLMs), LLM testing best practices, OWASP Top 10 for LLMs, Prompt injection testing, Responsible AI, Spritle Blog, SpritleSoftware

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.

agentic ai, ai, AI (Artificial Intelligence), AI Agents, AI Business Strategy, AI Governance, AI in Action, AI Infrastructure, AI Market Trends, AI security, Artificial Intelligence, Enterprise AI, Featured News, Gemini, google cloud, Google Cloud Next, Governance, Regulation & Policy, Inside AI

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

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Anthropic’s Mythos AI model sparks fears of turbocharged hacking

ai, AI (Artificial Intelligence), AI security, anthropic, Artificial Intelligence, cybersecurity, Mythos

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

agentic ai, ai, AI (Artificial Intelligence), AI and Us, AI Business Strategy, AI Cybersecurity, AI in Action, AI security, amazon web services, anthropic, Artificial Intelligence, Claude Mythos, CrowdStrike, cybersecurity, Cybersecurity AI, Google, Human-AI Relationships, Inside AI, Microsoft, nvidia, Open Source Security, Palo Alto Networks, Project Glasswing, vulnerability, zero-day

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

agentic ai, ai, AI (Artificial Intelligence), AI and Us, AI Business Strategy, AI Cybersecurity, AI in Action, AI security, amazon web services, anthropic, Artificial Intelligence, Claude Mythos, CrowdStrike, cybersecurity, Cybersecurity AI, Google, Human-AI Relationships, Inside AI, Microsoft, nvidia, Open Source Security, Palo Alto Networks, Project Glasswing, vulnerability, zero-day

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

ai, AI (Artificial Intelligence), AI Auditability, AI Compliance 2026, AI Data Privacy, AI Governance, AI Governance & Compliance, AI Quality Assurance, AI Regulations, AI Risk Assessment, AI Risk Management, AI security, AI Testing, Artificial Intelligence, Continuous Compliance, Enterprise Technology, Ethical AI, EU AI Act, QA in AI, Quality Assurance, Responsible AI, Software Testing, Spritle Blog, SpritleSoftware

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

ai, AI (Artificial Intelligence), AI language models, AI security, Artificial Intelligence, Biz & IT, ChatGPT, chatgtp, deepseek, Distillation, Gemini, Google, Google Gemini, Large Language Models, LLMs, Machine Learning, OpenAI

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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