Prompt Injection
An attack that manipulates an AI system's behavior by embedding malicious instructions in its input.
Definition
What is Prompt Injection?
Prompt injection is the #1 vulnerability in the OWASP LLM Top 10 — an attack technique where malicious instructions are embedded in content processed by an LLM, causing the model to override its original instructions or take unintended actions. Direct prompt injection occurs when a user directly manipulates the model's instructions through the interface. Indirect prompt injection — significantly more dangerous — occurs when malicious instructions are embedded in external content that the LLM processes (websites it browses, documents it summarizes, database records it retrieves), causing the model to act on attacker-controlled instructions without the user's knowledge.
Why It Matters
Prompt injection is difficult to fully prevent because LLMs do not maintain a hard separation between 'instructions' and 'data' — both arrive as natural language. As enterprises deploy AI agents with access to email, calendar, file systems, databases, and external APIs, indirect prompt injection becomes a severe threat: an attacker can send a malicious email that, when processed by an AI assistant, causes the assistant to exfiltrate data, send unauthorized messages, or modify records — all without any visible attack.
How It Works
Prompt injection defenses include: input validation and sanitization, structured output formats that resist instruction injection, privilege separation (limiting what tools an LLM agent can access), human confirmation requirements for consequential actions, monitoring LLM inputs/outputs for injection patterns, and canary tokens in system prompts to detect exfiltration attempts.
Our Approach
Paxanimi's Approach to Prompt Injection
Paxanimi's AI security engineers test enterprise AI deployments for prompt injection vulnerabilities using both automated scanning and manual adversarial testing. We implement defense-in-depth architectures — input validation, output filtering, tool access controls, and behavioral monitoring — to reduce prompt injection risk while maintaining AI system utility. Our AI security assessments specifically target indirect injection through RAG retrieval pipelines, email integrations, and document processing workflows.
Quick Reference
- Category
- AI Security
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- Cybersecurity ServicesSoftware Development
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