How to Secure AI APIs in Production | Quiz

[WHY] The article states you can achieve 95% risk reduction with three controls: token budgets – prompt guards – and output filtering. [CONTEXT] Starting with token-based rate limiting makes everything else easier because you control the economics of abuse. [REMEMBER] Token budgets plus prompt guards plus output filtering.

[WHY] This is indirect prompt injection where malicious instructions are hidden in content the model retrieves – the model cannot distinguish document content from commands. [CONTEXT] Indirect injection differs from direct injection because the user does not type the malicious instructions. [REMEMBER] Hidden instructions in retrieved content equals indirect injection.

[WHY] The article lists high query volume – template probing with minor variations – broad semantic coverage across unrelated domains – and high output to input token ratio as extraction indicators. [CONTEXT] Model extraction looks like normal high-volume usage to traditional tools. [REMEMBER] High volume plus template probing plus broad coverage.

[WHY] Output minimization means returning only the final answer – not intermediate steps or confidence scores or excessive metadata. [CONTEXT] This is the primary defense against both data leakage and model extraction – never return more data than strictly necessary. [REMEMBER] Never return more than necessary.

[WHY] Denial-of-wallet is abusing API access to run up enormous bills – a compromised API key used for bulk text generation can cost tens of thousands of dollars in hours. [CONTEXT] Some attackers do not want your data – they want your compute budget. This is a financial attack disguised as legitimate usage. [REMEMBER] Attackers drain your budget – not your data.

[WHY] The article organizes threats into traditional API risks – AI-specific threats – and resource abuse with financial impact. [CONTEXT] Understanding these three categories helps security teams apply appropriate controls at each level. [REMEMBER] Traditional plus AI-specific plus resource abuse.

[WHY] Traditional API security focuses on the pipe (network and access) but AI API security must also secure the water (prompts and responses) and the valve (model logic). [CONTEXT] Standard API tools are blind to AI-specific threats in the content flowing through the API. [REMEMBER] Pipe plus water plus valve – not just the pipe.