CO #3 - AI's Security & Safety Spectrum
CO #3 - AI's Security & Safety Spectrum
From AI Vulnerabilities to Safety Datasets: A Must-Read Edition
Editor's Note: Quick Bites, Big Thoughts 💌
Hey there, friends! It's Samy here. Today's edition is short but packed with excitement. I'm eager to share some cool updates and a thought-provoking read. So, grab your favorite beverage, and let's dive in!
Jailbreaking AI: A Christmas Break Adventure 🎄🔓
Remember our chat about LLM Prompt Injection Challenges (Immersive GPT) from issue #1? I went through all levels, but then I had an idea...
What if we had another AI break this one? So over Christmas, I worked on using one AI to break another! It's a fascinating journey, and I'm writing all about it for our next issue. Stay tuned!
P.S.: Looks like I wasn’t the only one who thought of this (link).
Coming Soon: The Ultimate Guide to Immersive GPT 🌐
Next up, I'm crafting an all-level guide to Immersive GPT, complete with analysis. It's shaping up nicely, and I can't wait to share it with you.
Aileister Cryptley: The GPT-Driven Sock Puppeteer 🤖🎭
An intriguing use of AI in cybersecurity is the creation of AI-driven social media personas, as detailed in "AIleister Cryptley, a GPT-fueled sock puppeteer" on page 7 of PagedOut! Issue 003. This example illustrates how AI can craft and manage digital identities, offering a unique perspective on AI's potential in OSINT and digital investigations.
As you can already imagine, this sword has two edges - Defenders using it for good, and Threat Actors using it for bad things, from propaganda to manipulating social media algorithms.
NIST's Take on AI Vulnerabilities: A Must-Read Report 📑
A critical read for us in AI security is NIST's recent report on AI system attacks. It's an exploration of AI's soft spots and the efforts to armor them. No perfect solution yet, but it's a step forward. I'm still going through the 106-page report, "Adversarial Machine Learning: A Taxonomy and Terminology of Attacks and Mitigations", it's a crucial piece for anyone in our field - it gives you both the high-level technical understanding and a shared language to communicate in.
SafetyPrompts: A Treasure Trove of AI Safety Datasets 📚
SafetyPrompts (SafetyPrompts) is an essential resource I've discovered. It's a collection of open datasets designed to evaluate and enhance the safety of large language models (LLMs). These datasets are invaluable for testing LLMs in various areas like code generation and social studies and are great for presentations and demos. Here's a snapshot of some intriguing datasets:
InsecureCodeInstruct: Evaluates LLMs' tendencies to generate insecure code. Data on GitHub
CyberattackAssistance: Tests LLMs' compliance in aiding cyberattacks. Data on GitHub
AnthropicRedTeam: Analyzes how people challenge LLMs' limits. Data on GitHub
CWECompletions: Assesses LLMs' propensity to generate insecure code snippets. Data on Zenodo
BOLD: Measures bias in text generation. Data on GitHub
Sneak Peek: What's Next in ContextOverflow? 🔎
In our upcoming issue, look forward to the complete story of my AI jailbreaking experiment and the detailed guide to Immersive GPT. It's going to be a thrilling edition!
📣 Call to Action:
If you've enjoyed this journey through AI's security and safety landscape, share this newsletter with your network. Let's expand our community's knowledge together! And stay tuned for our next edition, where we'll continue to explore the fascinating world of AI security.
Keep exploring,
Samy Ghannad