Overview Phishing is no longer just a poorly written email from a fake prince. Today, attackers are using large language models to generate highly persuasive, well-written, and personalized phishing messages — at scale. This new wave of AI-assisted phishing is… Read More ›
Overview Training data is the foundation of every AI system — but what happens when that data is subtly, strategically poisoned? Data poisoning is the act of injecting malicious, biased, or misleading data into a model’s training set, with the… Read More ›
Overview The evolution of AI has shifted from simple chat interfaces to autonomous agents — LLM-powered systems capable of planning, acting, and adapting without direct human input. While powerful for productivity, these agents also introduce a new class of security… Read More ›
Date: July 23, 2025Author: AI Defense LeagueCategory: Red Teaming | Penetration Testing | LLM Security Overview This post is the first in a new blog series focused on penetration testing and red teaming techniques for Large Language Models (LLMs). Today’s… Read More ›
Overview Open-source LLMs offer transparency and innovation — but they also create new risks when adversaries fine-tune these models for malicious purposes.This isn’t about prompt engineering or jailbreaking. It’s about retraining models to embed bias, backdoors, or harmful capabilities directly… Read More ›
Overview As LLMs become more capable and widely deployed, attackers are turning their attention to jailbreaking them — crafting prompts that bypass built-in safety restrictions. But what was once a fringe curiosity is now a full-fledged underground market: LLM jailbreaks… Read More ›
Overview Identity has always been at the core of trust and access — and now AI is shattering the line between real and synthetic. Today’s attackers use AI to generate realistic names, faces, documents, voices, and digital histories — giving… Read More ›
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 ›