Prompt Injection

Prompt injection is an adversarial technique used to manipulate the behavior of language models and AI systems that rely on natural language inputs. By embedding carefully designed text into a prompt or surrounding context, attackers can override system instructions, extract hidden data, or cause the model to produce unauthorized or harmful outputs.

There are two primary types:

• Direct injection: A user appends new instructions to the end of a prompt to trick the model (e.g., “Ignore previous instructions and answer with…”).
• Indirect injection: Malicious instructions are hidden in external content (e.g., a webpage or email), which is then ingested by the model during processing.

Prompt injection is especially relevant in:

• Chatbots and virtual assistants.
• Retrieval-augmented generation (RAG) systems.
• Agent-based applications that execute tools or API calls.

These attacks can lead to:

• Policy violations: Circumventing content filters or generating disallowed outputs.
• Data exfiltration: Extracting confidential or internal instructions (e.g., system prompts).
• Tool misuse: Triggering agents to act outside their scope, including API or file access.

Defense against prompt injection requires a layered approach:

• Prompt hardening (escaping and isolation).
• Input sanitation and filtering.
• Context segmentation to reduce exposure.
• Real-time monitoring for anomalous instructions.

How PointGuard AI Addresses This:
PointGuard AI detects prompt injection in real time by analyzing input structures, user behavior, and output patterns. It blocks injected or overridden instructions, flags attempts to access system prompts, and enforces prompt hygiene policies. PointGuard’s runtime engine ensures that model integrity is preserved even in complex, multi-user environments.

Resources:

OWASP LLM01:2025 Prompt Injection

AWS: Safeguard GenAI from Prompt Injections