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 ›
Cybersecurity Blog
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 ›
Hijacking AI Agents — From Helpful Assistant to Autonomous Threat
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 ›
Exfiltration via AI Channels — Hiding Data in AI Prompts and Outputs
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 ›