AI Application Security Best Practices

<p>Most companies shipping AI have never once tried to break it.</p> <p>Not because they don't care about security. Because they assume the model handles it. The model was trained

<p>Every prompt injection defense I’ve seen makes the same mistake. It asks the wrong question.<br /> The wrong question: “Does this prompt contain dangerous words?”<br /> The

<h2> The risk in one paragraph </h2> <p>Every time your team deploys software to AWS, a pipeline authenticates with credentials that can modify production infrastructure. In most

<h1> Static Analysis for LLM Prompt Security: A Methodology for Pre-Deploy Vulnerability Detection </h1> <p><em>How applying SAST principles to LLM prompt strings catches security

<h2> TL;DR </h2> <ul> <li>AI assistants trained on public repos reproduce hardcoded secrets because that's what they learned</li> <li>A pushed API key is effectively public even

<h1> Introduction¶ </h1> <p>Artificial intelligence now shapes access to credit, housing, employment, healthcare, and justice. In each of these domains, the decisions an algorithm

<p><em>Originally published on <a href="https://tamiz.pro/insights/prompt-injection-resilient-ai-applications" rel="noopener noreferrer">tamiz.pro</a>.</em></p> <p>The rapid

<p>On March 14, 2024, our production AI customer support chatbot leaked 1,247 unique PII records (including SSNs, unmasked credit card numbers, and internal API keys) to 892 end