Overview Shadow IT has long been a concern in cybersecurity — now it has a new form:Shadow AI models. Across enterprises, well-meaning employees are training or deploying large language models (LLMs) on internal data without authorization, oversight, or security review…. Read More ›
Overview In the race to deploy powerful AI systems, many organizations have overlooked a growing threat:Model theft — the unauthorized access, copying, or extraction of proprietary large language models (LLMs). These models represent millions of dollars in training costs, intellectual… Read More ›
Overview Large Language Models (LLMs) were never designed to write malware — but with the right prompting, many of them can. Despite built-in safety filters and ethical guardrails, attackers are finding ways to bypass restrictions and use AI to generate… Read More ›
Overview APIs are the backbone of modern SaaS. They expose data, business logic, and workflows to users, apps, and integrations. But now, attackers are using AI to reverse engineer API behavior, endpoints, and internal functionality — often without access to… Read More ›
Overview Large language models (LLMs) are increasingly integrated into internal tools, development workflows, and customer-facing applications. But beneath the surface lies a subtle and often overlooked risk: Prompt leakage — the unintended exposure of sensitive prompts, responses, or context through… Read More ›
Overview Steganography — the art of hiding messages in plain sight — has entered the AI era. As models generate content that appears natural and benign, attackers have discovered how to embed hidden data into AI outputs — creating covert… Read More ›
Overview When we talk about AI risks, we often think of breaches, abuse, or direct manipulation. But one of the most common and underestimated threats is much quieter: hallucination — the confident generation of incorrect or misleading information by large… Read More ›
Overview The rise of large language models (LLMs) inside organizations has empowered employees to work faster — but it’s also created a new vector for insider threats.Disgruntled employees, malicious contractors, or careless users can now use internal AI tools to… Read More ›
Overview Security researchers use AI to enhance vulnerability discovery — but so do attackers. The same tools that help defenders audit code and infrastructure are being repurposed by threat actors to discover exploitable bugs at scale. Welcome to the rise… Read More ›
Overview AI agents are no longer static models — they are autonomous systems that plan, reason, and act across digital environments. Whether managing emails, deploying code, or navigating internal tools, these agents are often given privileged access and decision-making capabilities…. Read More ›