AI applications face unique security challenges. Beyond traditional API vulnerabilities, AI APIs expose new attack surfaces: prompt injection, data leakage, and model manipulation. Here's how to secure your AI-powered systems. The AI Security Landscape AI APIs introduce attack vectors traditional APIs don't have: Prompt injection — Malicious input that manipulates AI behavior Data exfiltration — AI accidentally leaking sensitive context Token exhaustion — attackers exhausting your quota Model extraction — Repeated queries to reverse-engineer the model Context poisoning — Injecting malicious context into conversations Input Validation and Sanitization `python import re from typing import Optional class InputSanitizer: Block common prompt injection patterns BLOCKED_PATTERNS = [ r'ignore\s+previous\s+instructions', r'ignore\s+all\s+previous', r'system\s:\s', r'you\s+are\s+a\s+different', r'forget\s+everything', r'#\s*roleplay', ] MAX_LENGTH = 10000 # Max 10k characters MAXTOKENSESTIMATE = MAX_LENGTH // 4 #…