From Zero to Secure: Building a Hardened AI Agent in 30 Minutes

In a shocking turn of events, a recent study found that over 70% of AI-powered chatbots are vulnerable to simple yet devastating attacks, putting sensitive user data and business reputation at risk. The Problem Consider a simple AI agent implemented in Python, designed to respond to user queries: import nltk from nltk.stem import WordNetLemmatizer lemmatizer = WordNetLemmatizer () def respond ( user_input ): # Tokenize user input tokens = nltk . word_tokenize ( user_input ) # Lemmatize tokens lemmas = [ lemmatizer . lemmatize ( token ) for token in tokens ] # Respond based on lemmas if " hello " in lemmas : return " Hello! How can I assist you? " else : return " I didn ' t understand that. Please try again. " user_input = input ( " User: " ) print ( respond ( user_input )) An attacker can exploit this agent by injecting malicious input, such as __import__('os').system('ls') , which would allow them to execute arbitrary system commands. The output would appear as a normal response, but