Why AI Security Matters

Cross-Platform Note: All code in this course works on Windows, macOS, and Linux. We use Python for all operations to ensure compatibility.

AI applications are fundamentally different from traditional software. They accept natural language input, make autonomous decisions, and often have access to sensitive tools and data. This creates unique security challenges.

The New Attack Surface

Traditional applications have well-defined inputs: form fields, API parameters, file uploads. LLM applications accept any text as input, and that text directly influences behavior.

# Traditional application - predictable input
def search_products(category: str, max_price: float):
    # Input is structured and validatable
    return db.query(category=category, price_lte=max_price)

# LLM application - unpredictable input
def chat_assistant(user_message: str):
    # ANY text can influence the model's behavior
    response = llm.generate(
        system="You are a helpful shopping assistant.",
        user=user_message  # Attack vector
    )
    return response

Real-World Incidents

Year	Incident	Impact
2023	Bing Chat system prompt leaked	Revealed internal instructions
2023	ChatGPT plugins exploited	Unauthorized data access
2024	Customer service bots manipulated	Gave unauthorized discounts
2024	Code assistants tricked	Generated insecure code

Business Impact

Security failures in AI applications can cause:

• Data breaches: LLMs can be tricked into revealing training data or user information
• Financial loss: Manipulated AI can approve unauthorized transactions
• Reputation damage: Jailbroken assistants produce harmful content
• Regulatory penalties: GDPR, HIPAA, and other regulations apply to AI systems

Why Traditional Security Isn't Enough

Traditional Security	AI Security Challenge
Input validation	Natural language has no fixed schema
Access control	LLM decides what actions to take
Output encoding	LLM generates dynamic content
Rate limiting	Attacks can be slow and subtle

Key Takeaway: AI security requires new tools and techniques. Traditional security practices are necessary but not sufficient. :::