AI Jailbreaking
23 articles
Many-Shot Jailbreaking Technique 2026 — How Context Window Size Defeats Safety Training
Many-shot jailbreaking technique in 2026 — the repetition that breaks Claude, GPT-4, and Gemini safety filters. How it works and…
LLM01 Prompt Injection 2026 — Complete Attack Guide | AI LLM Hacking Course Day4
Master LLM01 prompt injection in 2026. Direct injection, indirect injection, jailbreaks, filter bypasses and bug bounty payloads — complete OWASP…
OWASP LLM Top 10 — The Complete Hacker’s Guide to Every Vulnerability | AI LLM Hacking Course Day3
Master all OWASP LLM Top 10 vulnerabilities. Prompt injection, data poisoning, excessive agency and more — with exploit examples, real…
How LLMs Work — Transformer Architecture, Tokens & Context Windows | AI LLM Hacking Course Day2
Understand how LLMs work from a hacker's perspective. Tokens, attention, context windows, system vs user messages — the architecture that…
The AI Security Landscape 2026 — Why Every Ethical Hacker Needs to Learn LLM Hacking Now | AI LLM Hacking Course Day 1
The AI security landscape in 2026 is the biggest opportunity in ethical hacking. Learn the attack surface, OWASP LLM Top…
Model Poisoning Attacks 2026 — How AI Models Get Hacked From Inside
Model poisoning attacks 2026 silently manipulate AI systems. Learn how attackers corrupt training data and control AI decisions without detection.
Gemini Advanced Prompt Injection Vulnerabilities 2026 — Research Findings
Gemini Advanced prompt injection vulnerabilities 2026 — published research on indirect injection, tool misuse, and multi-modal attack surfaces in Google's…
AI Jailbreaking Research 2026 — How Researchers Study LLM Safety Robustness
AI jailbreaking research 2026 — how security researchers study LLM safety robustness, published findings from Anthropic and academic labs, detection…
AI Red Teaming Guide 2026 — How Security Teams Test LLM Applications
AI red teaming guide 2026 — how security teams stress-test LLM applications for prompt injection, data leakage, misuse, and unsafe…