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 ›
Overview Modern security teams monitor emails, file uploads, and network traffic for signs of exfiltration — but AI models open up a new covert channel. By embedding data inside prompts or manipulating model outputs, attackers can sneak information out of… Read More ›
Overview AI was once a tool for defenders — helping classify malware, detect anomalies, and improve SOC workflows. But now, attackers are embedding language models directly into malware, enabling dynamic payloads, evasive scripting, and autonomous decision-making during intrusions. This new… Read More ›
Overview Denial-of-service attacks are a classic threat to servers and web infrastructure — but as AI models are deployed across APIs, apps, and agents, they too have become targets of disruption. Model Denial of Service (MoDoS) refers to attacks that… Read More ›
Overview Deploying an AI model through a public or private API can deliver massive value — enabling chatbots, recommendation engines, fraud detection, and countless other services. But exposing your model through an API also creates a tempting attack surface. Model… Read More ›