Prompt Injection is a cybersecurity attack technique in which maliciously crafted inputs manipulate AI models—particularly Large Language Models (LLMs)—to produce harmful, misleading, or confidential outputs. By cleverly altering context or slipping in hidden commands, attackers can bypass content filters, reveal private data, and create biased or offensive results.
How It Works:
- Context Manipulation: Attackers modify the context or background information of a prompt to influence the model’s output in undesirable ways.
- Command Insertion: Malicious instructions are hidden within seemingly benign requests, prompting the AI to perform unintended actions or expose sensitive content.
- Data Poisoning: Harmful data is introduced during the model’s training phase, skewing its responses to align with the attacker’s goals.
Why It Matters:
Prompt Injection poses significant risks, ranging from compromised brand reputation and personal data leaks to spreading misinformation and fueling societal unrest. Understanding and mitigating this threat is critical for maintaining trustworthiness, reliability, and safety in AI-driven applications.
