AI Attacks
AI Attacks attack research · no vendor filter updated 2026-10-02
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Every model has an attack surface.

AI attack techniques against deployed LLMs and agents: jailbreaks, prompt injection, model extraction, evasion, and data poisoning. Every technique is documented from published research, disclosed incidents, and vendor documentation, with the source named so you can check it.

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Prompt Jailbreak Examples: 7 Patterns Explained

Attack Techniques

RAG Poisoning: Corrupting Retrieval and Embeddings

LLM Security

How Indirect Prompt Injection Works

Attack Techniques

LLM Jailbreak Defenses: Why Static Filters Fail

Defense

LLM Jailbreak Examples: 10 Documented Patterns

Attack Techniques

Adversarial Examples Explained: How Pixels Fool Models

Explainer

OWASP Top 10 LLM Explained: Every Entry and What to Fix

LLM Security

Evasion Attacks in Production ML: Malware, Spam, and Fraud

Adversarial ML

Web-Scale Dataset Poisoning: Split-View and Frontrunning

Adversarial ML

Adversarial Examples Against Vision Models in 2026

Adversarial ML

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