The Best AI Security Platform for LLM Agents in 2026

In 2023, a single malicious input crashed a popular chatbot, exposing sensitive user data to the public, and it took the developers weeks to identify and patch the vulnerability. The Problem from flask import Flask , request import torch from transformers import AutoModelForSeq2SeqLM , AutoTokenizer app = Flask ( __name__ ) model = AutoModelForSeq2SeqLM . from_pretrained ( " t5-small " ) tokenizer = AutoTokenizer . from_pretrained ( " t5-small " ) @app.route ( ' /chat ' , methods = [ ' POST ' ]) def chat (): user_input = request . get_json ()[ ' input ' ] inputs = tokenizer ( user_input , return_tensors = " pt " ) output = model . generate ( ** inputs ) response = tokenizer . decode ( output [ 0 ], skip_special_tokens = True ) return { ' response ' : response } In this example, an attacker could craft a malicious input that exploits the model's vulnerabilities, causing it to produce a harmful or sensitive response. The output might look like a normal response, but it could contain sens