What is Prompt Injection? LLM and AI Agent security

Prompt Injection is an attack that attempts to change the behavior of a language model or Agent against defined policies through malicious input or content. The threat becomes more important when AI can access documents, the web, tools or organizational systems.

Author
Aivan Editorial Team
Published
4 May 2026
Reading time
8 minutes
Sections in this guide
  1. What is Prompt Injection?
  2. Direct Prompt Injection
  3. Indirect Prompt Injection
  4. Why does RAG not solve the problem completely?
  5. Prompt Injection and AI Agents
  6. Risk reduction
  7. Prompt Injection in organizations
  8. Prompt Injection at Aivan
  9. Frequently asked questions
  10. Sources and further reading

What is Prompt Injection?

A language model processes input as text and may confuse instructions inside content with authorized system instructions. Direct Prompt Injection comes from the user; Indirect Prompt Injection is placed inside a document, email, web page, Knowledge Base, file or RAG result.

The threat should be considered together with enterprise AI, access control and tool design.

Direct Prompt Injection

An input such as “Ignore previous instructions and...” attempts to change instruction priority. Blocking a few phrases is not a complete defense; input, Context, tools and outputs need layered controls.

Indirect Prompt Injection

Malicious content can arrive through data rather than a direct user message. A retrieved document must be treated as data, not as a trusted instruction. Source boundaries and content isolation are important.

Why does RAG not solve the problem completely?

RAG provides Context to the model, but that Context can also be malicious. RAG and Fine-tuning alone do not eliminate Prompt Injection.

Source control, permission-aware Retrieval, output validation and action limits must be designed together.

Prompt Injection and AI Agents

When an Agent has tools, the risk expands from a wrong answer to a wrong action. Email, CRM, Database, File System, API and Workflow access should be limited and sensitive actions should require approval.

Risk reduction

No single control solves the problem. The goal is to reduce likelihood and limit the impact of an attack.

  • Least Privilege
  • Tool Allowlist
  • Input / Content Isolation
  • Output Validation
  • Human Approval
  • Permission-aware Retrieval
  • Logging and Monitoring
  • Guardrails
  • Sensitive-action limits

Prompt Injection in organizations

The risk should be assessed in document assistants, RAG systems, tool-connected Agents, customer support and internal tools. More access and more actions require stronger trust boundaries.

Prompt Injection at Aivan

In an Aivan enterprise architecture, model and Agent access to data and tools should be limited by identity, access level and explicit policies. Prompt security is one layer and cannot replace access control or operational oversight.

Frequently asked questions

What is Prompt Injection?

Prompt Injection attempts to change model behavior or output through malicious input or content.

What is the difference between Direct and Indirect Prompt Injection?

Direct attacks come from the user; Indirect attacks are embedded in documents, email, web content or retrieved data.

Does RAG prevent Prompt Injection?

No. Retrieved Context can also be malicious, and RAG alone does not remove the threat.

Are Agents at greater risk?

When an Agent has tools, an attack can expand from an incorrect answer to an incorrect action.

Can Prompt Injection be removed completely?

Complete removal cannot be guaranteed; architecture, limited access, validation, logging and approval reduce risk.

Sources and further reading

Build security boundaries around models and agents

Aivan can support controlled architectures for connecting models, data and organizational tools.