Essential AI Red Teaming Tools & Techniques for Product Teams
This guide outlines the tools, datasets, and workflows you need to operationalize red teaming and embed safety into your product development process. Download the report to help your team to uncover vulnerabilities and strengthen safety before bad actors strike.
Overview
In this report, we cover:
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How to design threat models tailored to your product’s risk surface.
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Building attack libraries.
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Creating training and evaluation datasets that close safety gaps.
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Using simulation platforms to test models at scale.
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Turning results into actionable improvements and integrating testing into CI/CD.
Download this practical guide to building repeatable, high-impact AI red teaming workflows.
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What’s New from Alice
"Okay, Here is How to Build a Bomb": Millions Download Dangerous LLMs
Thousands of abliterated LLMs have flooded open-source platforms with millions of downloads. These models comply with virtually any request, from bomb-making to malware, and run fully offline on consumer devices.
Your LLM Has No Idea What It's Doing
Diana Kelley, CISO at Noma Security and former Cybersecurity CTO at Microsoft, joins Mo to work through the real mechanics of LLM risk: why the context window flattens the trust boundary between system instructions and user data, why that makes reliable internal guardrails essentially impossible, and why agentic AI is less a new threat category and more a stress test for the hygiene debt organizations never fully paid off.
Distilling LLMs into Efficient Transformers for Real-World AI
This technical webinar explores how we distilled the world knowledge of a large language model into a compact, high-performing transformer—balancing safety, latency, and scale. Learn how we combine LLM-based annotations and weight distillation to power real-world AI safety.
