CO #9 - Fabric The Framework for Augmenting Humans, Hackbots, Air Canada's Chatbot, and Halvar Flake on AI
Hello, folks!
It's Samy here, and as usual, I've scoured the digital world to bring you the most intriguing updates on AI security, its use in cybersecurity, and how the security of AI itself is evolving. This week's edition is packed with insights that will not only fuel your curiosity but also provide you with valuable knowledge to navigate the complex landscape of AI and cybersecurity.
Before we dive into the heart of our newsletter, I wanted to share a personal update. I'm moving closer to Toronto, and if you're familiar with the Canadian housing market's challenges, you know it's been quite the journey.
Between being sick and juggling all the logistics of moving houses, I’m trying to finish a few posts that I’m excited about - bear with me a bit more!
Now, let's get into the meat of our newsletter.
Table of Contents:
🛠️ Harnessing AI for Human Augmentation with Fabric - How Fabric's open-source framework is changing the game.
🤖 Exploring the World of Hackbots - Unveiling AI agents with hacking capabilities.
✈️ AI Chatbots and Accountability: A Lesson from Air Canada - The implications of AI misinformation.
🔒 AI in Cybersecurity: Insights from Halvar Flake - Future applications in offensive, defensive, and optimization spaces.
🔬 Re-visiting AI in Security: Halvar Flake's Analysis - What's changed and what remains in AI and security.
1. 🛠️ Harnessing AI for Human Augmentation with Fabric
Daniel Miessler introduces Fabric, an open-source framework designed to seamlessly integrate AI into our daily lives. Fabric addresses AI's integration problem by enabling the application of AI in a modular fashion, leveraging crowdsourced AI prompts, or “Patterns”, for a variety of tasks.
Check out all the available Patterns here
My Thoughts: Daniel Miessler is one of my favorite people on the Internet, he never ceases to amaze me, and Fabric is no exception.
Fabric is like the GNU tools for AI, allowing for seamless processing, piping, and chaining of commands. With an array of patterns available and the ability to add your own, Fabric is a game-changer.
There are already a few patterns in the repo that focus on Cybersecurity:
Analyze Incident, Analyze Threat ( + trends), Explain Code, Extract POC, and Write Semgrep Rule are some examples.
You can watch analyze_threat_report in action. Go watch that then come back and tell me if it’s anything but amazing.
2. 🤖 Exploring the World of Hackbots
In All About Hackbots: AI Agents That Hack, rez0 delves into AI systems capable of identifying vulnerabilities in applications. Joseph covers what hackbots can do, their significance, and their potential to revolutionize cybersecurity by automating vulnerability detection by moving away from simple binary detections and more toward an intelligent method of testing - at scale.
My Take: Nothing excites me more than seeing these types of innovations i.e. actual uses in both red and blue sides.
The only problem is that they’re slow, but I promise you it’s temporary.
Last week we had groq.com pushing the speed limits, and this week we have phind.com adding a new record. The future looks bright (and fast) for hackbots.
3. ✈️ AI Chatbots and Accountability: A Lesson from Air Canada
The Washington Post reports a significant case where Air Canada had to honor a discount promised by its chatbot. The whole thing cost AirCanada only $602.8, but it had the potential to get out of control very quickly.
This incident underscores the growing pains of integrating AI into products and the importance of accuracy and accountability in AI-generated information.
What I Think: This incident serves as a critical reminder of the necessity for precision and reliability in AI communications. It's a mild case, but it highlights the broader implications for more critical areas such as medical or financial information. So far most of the defenses we have are either an adaptation of blocklist/allowlist of sort or using the same thing that couldn’t do the job right the first time i.e. the AI model, to assess the work of another model.
While these are all great, they’re not working as reliably as we need them to.
With all that being said, I have a hunch that we’re due a breakthrough this year.
4.🔒 AI in Cybersecurity: Insights from Halvar Flake
A recent Intel Business interview with Halvar Flake explores the use of AI in cybersecurity, touching on its potential applications in offensive and defensive operations, as well as software optimization. Flake's insights from 2018 about AI's effectiveness in stable versus rapidly changing or malicious distributions are particularly relevant today.
Listen to his thoughts here
My 2 Cents: Flake's perspective is interesting, especially his idea of using AI to generate "garbage data" as a defensive tactic - like a black hole honeypot where you feed the attacker an infinite stream of plausible and sensible data.
This reminded me of Operation Gold where the Soviets fed false data to MI6 and CIA for 11 months straight - imagine doing that to an attacker!
5.🔬 Re-visiting AI in Security: Halvar Flake's Analysis
Halvar Flake's enlightening presentation at RingZer0, titled "Re-visiting 2017: AI and Security, 7 years later - what changed, what endured?" delves into the practical applications and limitations of machine learning and LLMs in cybersecurity.
Starting with slide 10, he highlights the challenges of using machine learning for detection, labeling it as probably the least suitable application due to its violation of machine learning's underlying assumptions.
Slides 26 through 28 further explore LLMs, detailing their strengths in extracting structured data from unstructured sources, summarizing large text corpora, and generating plausible solutions to programming problems, while also noting their unpredictability with calculations and precise reasoning.
Slide 29 offers a fascinating insight into how prompts, even seemingly unrelated ones like "take a deep breath," can significantly impact LLMs' performance by directing them towards more accurate outputs.
See the slides here.
As we wrap up this edition of ContextOverflow, I hope you've found these insights as fascinating as I have. The potential of AI in cybersecurity is immense, but so are the challenges. As we continue to explore these technologies, let's remain mindful of their implications and strive for solutions that enhance security and trust.
📣 Call to Action: If you've enjoyed this read, don't keep it to yourself! Share this newsletter with friends and colleagues who share our passion for AI security.
Stay tuned for next week's edition, where we'll continue to dive deep into the world of AI and cybersecurity.
Stay secure and curious,
Samy