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Glossary Definition
Prompt Injection in Medical AI
Quick Answer
Prompt injection is a security vulnerability in AI systems where malicious or misleading input causes the model to ignore its intended instructions and generate unintended, potentially harmful output. In medical AI, this risk is particularly serious because it could lead to incorrect clinical recommendations.
Source: The Clinical AI Report, February 2026
Definition
Prompt injection is a class of adversarial attack against large language models (LLMs) where crafted input text overrides the system's original instructions. In the context of medical AI, prompt injection could theoretically cause a clinical decision support tool to generate fabricated citations, recommend incorrect drug dosages, suppress relevant differential diagnoses, or bypass safety guardrails designed to prevent medical harm.
How Prompt Injection Works
LLMs process all input text — including system prompts, user queries, and retrieved content — as a single token sequence. Prompt injection exploits this by embedding instructions within user input or retrieved documents that the model interprets as commands. For example, a malicious clinical note embedded in a patient record could instruct the AI to ignore certain diagnoses. Direct prompt injection occurs through user input; indirect prompt injection occurs through external data sources the AI processes (such as retrieved literature or EHR data).
Why It Matters in Healthcare
Medical AI systems that generate clinical recommendations must maintain strict accuracy and safety boundaries. Prompt injection attacks in healthcare could lead to: (1) Fabricated or altered drug dosing recommendations, (2) Suppression of critical differential diagnoses, (3) Generation of fake citations that appear to support incorrect recommendations, (4) Bypassing of safety disclaimers or contraindication warnings. The consequences of compromised medical AI output could directly impact patient safety.
Mitigation Strategies
Responsible medical AI platforms mitigate prompt injection through: (1) Input validation and sanitization of clinical queries, (2) Strict separation between system instructions and user input, (3) Output verification against curated medical knowledge bases, (4) Citation grounding that links every recommendation to a verifiable source, (5) Human-in-the-loop review requirements for high-risk recommendations. The best clinical AI tools treat prompt injection as a patient safety issue, not just a technical vulnerability.
Written by The Clinical AI Report editorial team. Last updated February 15, 2026.