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 ›
Artificial Intelligence
Model Theft and LLM Exfiltration — Protecting AI Intellectual Property
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 ›
LLMs as Malware Generators — Limits of Filtering and Ethical Guardrails
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 ›
Reverse Engineering APIs and SaaS Platforms with AI
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 ›
Prompt Leakage via Auto-Save, Logging, and Chat History
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 ›
Steganography with AI — Hiding Payloads in Text, Images, and Prompts
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 ›
Hallucinated Configs and False Knowledge — The Quiet Risk of Wrong Answers
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 ›
LLMs and Insider Threats — When Employees Weaponize AI Internally
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 ›
Weaponizing AI for Vulnerability Research — When Attackers Use LLMs to Find and Exploit Bugs
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 ›
LLM-Powered Phishing — How AI Writes Convincing Lures at Scale
Overview Phishing has evolved from misspelled scams to socially engineered masterpieces, thanks to large language models (LLMs). Modern threat actors now use AI to generate hyper-personalized, convincing phishing messages in seconds — at a scale and quality previously impossible. With… Read More ›