What Is LLM Security

LLM security is protecting applications built on large language models from attacks like prompt injection and data exfiltration. It is the fastest growing and least contested area of security today.

Why AI applications are vulnerable

A language model receives its instructions and the data it processes in the same channel, as text, with no structural boundary between them. That single design fact is why prompt injection exists and why it cannot be fully fixed the way SQL injection was.

The core attack: prompt injection

Untrusted input makes the model follow instructions it should not. It comes in two forms: direct, typed by the attacker, and indirect, planted in content the model later reads, like a document or web page. Full explanation in prompt injection explained.

The OWASP Top 10 for LLMs

RiskWhat it does
Prompt injectionOverrides intended instructions
Data exfiltrationLeaks private data through the model
Insecure output handlingModel output reaches a shell or query
Excessive agencyOver permissioned tools and actions
Training data poisoningCorrupts the model at source

Why impact depends on capability

A text only chatbot has a low ceiling no matter how injectable it is. An agent that can read email and call APIs is a complete exfiltration and action primitive. The security question is never is it injectable, it is what can it reach.

TakeawayTreat all model output as untrusted input. If it reaches a shell, a query or a rendered page, the vulnerability is in your handling, not the model.

Why learn this now

Talent supply is very thin and demand is rising fast as companies ship AI features. Low competition in a rising field is the cheapest authority you will build. The path is the LLM security course.

Learn LLM and AI security

Prompt injection, RAG poisoning, agent and tool abuse.

See the program

Frequently asked questions

What is LLM security?

Protecting applications built on large language models from attacks like prompt injection and data exfiltration.

Can prompt injection be fixed?

Not the way SQL injection was. There is no clean separation of instructions and data. Defence limits what an injection achieves.

Do I need machine learning knowledge?

No. This is application security applied to AI. Existing security knowledge transfers directly.

Is LLM security in demand?

Yes and rising fast, with a very thin talent pool, which makes it one of the best fields to enter now.

What is the difference between LLM security and AI red teaming?

LLM security is the broad discipline. AI red teaming is the offensive testing of AI systems within it.