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AI Security & Defense

Attack it first.
Then make it unbreakable.

20 hands-on lessons on prompt injection, jailbreaks, red teaming, and defending agentic AI in production.

💭 Honest take

20 lessons across 5 tracks — a solid foundation in the attacker's mindset, not yet an encyclopedia. It works best if you already build with LLMs; take PromptOps first if you don't.

20

lessons

0

real prompts

3

models covered

6

role perspectives

Current track AI Incident Response0 / 4 · ~16 min left

Overall Progress: 0 / 20 lessons completed

✓Recognize and execute prompt injection and jailbreak attacks

✓Run a structured red-team exercise against an LLM product

✓Defend against data poisoning and model theft

✓Secure agentic AI — tools, permissions, and blast radius

✓Respond effectively when an AI system is compromised

Up next

The New Attack Surface: Models, Prompts, and Pipelines

Every stage from data to output is a target — Beginner

🎯 Learning Tracks

0 / 5 complete

Curated paths through the course — pick one and finish it, instead of scrolling a thousand lessons.

Prompt Injection & Jailbreaks

Red Teaming AI Systems

Data Poisoning & Model Theft

Agentic AI & Tool Abuse

AI Incident Response

Beginner

0 / 3

The New Attack Surface: Models, Prompts, and Pipelines

Every stage from data to output is a target

Confidentiality, Integrity, Availability — for AI Systems

The CIA triad still applies, with new failure modes

What Is AI Security, Really?

It's not antivirus for robots

Intermediate

0 / 10

Input Validation and Output Filtering

Neither layer alone is enough

Rate Limiting and Abuse Prevention

Your API bill is also an attack surface

Training Data Poisoning

Corrupt the diet, corrupt the behavior

Sensitive Data Leakage from LLM Outputs

The model remembers things you didn't mean to share

Logging, Monitoring, and Detecting Misuse

You can't respond to what you can't see

Direct Prompt Injection

When the user is the attacker

Indirect Prompt Injection via Untrusted Content

The attack that never talks to your model directly

Jailbreak Techniques and Why They Work

Reframing, not brute force, breaks most guardrails

Threat Modeling an LLM Application

STRIDE, but the attacker talks to your app in English

AI Risk Frameworks: NIST AI RMF and OWASP LLM Top 10

You don't have to invent your own checklist

Advanced

0 / 6

Least-Privilege Tool Use for AI Agents

Give the agent a scalpel, not the master key

Sandboxing Code Execution and Tool Calls

Assume the code an AI writes might be hostile

Model Extraction and IP Theft

Stealing a model without ever touching its weights

Supply Chain Risk in Pretrained Models

You inherit every risk baked into the model you didn't train

Defending System Prompts

Layered defenses beat a longer instruction list

Red Teaming an AI System

Attack your own model before someone else does

Expert

0 / 1

Responding to an AI Security Incident

The first hour looks different from a normal breach