Bot Abuse in AI APIs: Why Your LLM Endpoint Is a Target

A single, well-crafted prompt can drain your LLM endpoint's resources, costing thousands of dollars in mere minutes, and yet, most AI teams overlook this glaring security vulnerability. The Problem from flask import Flask , request , jsonify from transformers import AutoModelForCausalLM , AutoTokenizer app = Flask ( __name__ ) model_name = " your-llm-model " tokenizer = AutoTokenizer . from_pretrained ( model_name ) model = AutoModelForCausalLM . from_pretrained ( model_name ) @app.route ( " /generate " , methods = [ " POST " ]) def generate_text (): prompt = request . json [ " prompt " ] inputs = tokenizer ( prompt , return_tensors = " pt " ) output = model . generate ( ** inputs ) return jsonify ({ " text " : tokenizer . decode ( output [ 0 ], skip_special_tokens = True )}) if __name__ == " __main__ " : app . run ( debug = True ) This code block demonstrates a basic LLM endpoint that takes a prompt as input and returns generated text. However, an attacker can exploit this endpoint by