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Cyber AI Chronicle
By Simon Ganiere · 17th November 2024
Welcome back!
Project Overwatch is a cutting-edge newsletter at the intersection of cybersecurity, AI, technology, and resilience, designed to navigate the complexities of our rapidly evolving digital landscape. It delivers insightful analysis and actionable intelligence, empowering you to stay ahead in a world where staying informed is not just an option, but a necessity.
Table of Contents
What I learned this week
TL;DR
I’m starting a mini-series of 3 articles related to vulnerability management. The first one (this very newsletter), will focus on what is vulnerability management and what are the current challenges and priorities. The second article will cover how AI can help vulnerability management and show case a small tool I have developed to provide good context. The third and last part will be looking at the vendor side and what’s happening on the market. Let’s start with the beginning! » READ MORE
OWASP has published several AI security guidance documents: DeepFakes, Building an Ai Security Center of Excellence, and a Gen AI Security Solutions Guide. If you jump into the “Worth a full read” section you can get the details and a high-level summary.
The Google Cloud security team had a busy week with the release of a couple of really good report. The first one reaches the obvious conclusion that companies don’t need more security product but they need more secure products. Very much align to last week newsletter analysis. The second one is their Cyber Security Forecast for 2025. Highly recommend to read this one.
OpenAI has released a new version of their ChatGPT Mac application, that enable a better integration with the developer tools. No need to copy-paste code, you can give ChatGPT access to Xcode and from there it can read the code and help the developer. Not a perfect integration (yet) as in the video you still need to do some copy paste but its getting better for sure.
Lots of discussion about when AGI will come, you can find some recent Youtube/Podcast interview of both Sam Altman and Dario Amodei (Anthropic CEO) where they talk about AGI and the next steps for AI at large. Time will tell but one thing is for sure…the AI innovation and adoption is not stoping anytime soon…you better be ready!
Vulnerability Management 101 – The Foundation of a Secure Environment
This is part one of a three-part series on vulnerability management and how AI is reshaping this crucial area of cybersecurity. This article introduces the essentials, explaining why a modernized approach to vulnerability management is no longer optional. Part two will dive into a practical tutorial on using AI to gain real-time context on exploited vulnerabilities, while part three will examine the vendor landscape and the ways AI can streamline vulnerability and patching.
The State of Vulnerability Management Today
If you work in cybersecurity, especially within larger organizations, you've likely been tasked with implementing or enhancing vulnerability management. Maybe you’re motivated by a passion for security or driven by regulatory requirements, audit findings, or recent security incidents. Either way, the landscape is evolving rapidly, and traditional approaches are struggling to keep up.
Here’s the uncomfortable truth: the time-to-exploit window has shrunk drastically. What used to take attackers months now takes days. According to Mandiant, the average time-to-exploit has plummeted from 63 days to a mere 5 days in 2023. Even more alarming is the rise in targeted attacks on edge technologies—network devices, VPN concentrators, and remote access solutions. These vulnerabilities are the keys to your kingdom, sitting exposed right on your perimeter.
This shift isn’t just a statistical change; it’s a fundamental transformation in the way we respond to vulnerabilities. Early in my career, monthly patching cycles were considered diligent. Now, that same approach could leave your systems exposed for weeks, well after attackers have weaponized a vulnerability.
The Reality of Modern Attack Surfaces
Identifying vulnerabilities isn’t as straightforward as it used to be. The “perimeter” is now a sprawling network of on-premises systems, cloud services, remote work solutions, and IoT devices. Each one represents a potential entry point.
What’s particularly concerning is the trend in edge device exploitation. These aren’t hypothetical vulnerabilities; they’re actively being exploited in the wild, often before organizations have a chance to patch. According to recent findings, 70% of the vulnerabilities tracked by Mandiant in 2023 were zero-days—meaning attackers exploited them before patches were even available. This is also confirmed by the recent report released by CISA, 10 of the 15 most frequently exploited vulnerabilities last year were initially zero-days and with an obvious trend towards exploitation of enterprise and network perimeter devices.
Moving Beyond Traditional Scanning
Here’s where many organizations fall short: they’re treating vulnerability management as if it’s still 2010. Weekly scans, monthly reports, and quarterly patching cycles no longer suffice. Too many organizations suffer breaches through edge vulnerabilities while dashboards proudly display data from last week’s scans.
What Modern Vulnerability Management Needs
To counter today’s threats, vulnerability management must be:
Real-Time and Continuous: Attackers can weaponize vulnerabilities within days, so exposure needs to be monitored continuously, especially for internet-facing systems. In the next article, we’ll explore how AI makes this real-time awareness possible.
Edge-Aware: VPN concentrators, firewalls, and remote access gateways need particular attention.
Intelligence-Driven: Waiting for vendor advisories isn’t enough. You need insight from the broader threat intelligence ecosystem. AI is proving incredibly effective here, and we’ll cover how in part two.
Making Prioritization Work in Practice
Let me outline a common scenario: A critical vulnerability is discovered in a widely-used VPN. The security team wants an immediate patch, but business units push back, as it’s essential for remote work. Sound familiar?
Here’s how I recommend prioritizing:
Assess Immediate Exposure: Prioritize internet-accessible vulnerabilities on edge devices regardless of CVSS score.
Consider Exploitation Activity: If similar vulnerabilities are actively exploited, treat yours as a high-risk.
Factor in Business Impact: Sometimes, a “high” vulnerability in a remote access system is riskier than a “critical” one in an internal application.
Evaluate Remediation Complexity: Sometimes the fastest way to reduce risk is through compensating controls while planning a permanent fix.
Making It Work in Practice
Here’s what I’ve found most effective:
Maintain a Living Inventory of Edge Devices and Internet-Facing Systems: Many organizations lack visibility here.
Implement Continuous Monitoring for Critical Systems: With a 5-day exploit window, you can’t wait for the next scan.
Develop Emergency Patching Procedures for Edge Devices: When critical vulnerabilities emerge, speed is essential.
Build Clear Communication Channels with Business Units: They need to understand why that VPN patch can’t wait.
Looking Ahead: The Power of AI in Vulnerability Management
The trends we’re seeing aren’t going to reverse—if anything, they’ll accelerate. Zero-day exploits are becoming more common, time-to-exploit windows continue to shrink, and attack surfaces keep expanding. But these trends also offer an opportunity to evolve our approach.
This article covered the foundational elements of vulnerability management: processes, priorities, and practices. But this is just the beginning. Artificial intelligence is transforming our ability to identify and respond to vulnerabilities in ways that were unimaginable a few years ago.
In part two, we’ll explore how to:
Use AI-powered tools to identify zero-day vulnerabilities before they become public.
Leverage machine learning for real-time threat intelligence analysis.
Implement AI-driven prioritization that considers context beyond CVSS scores.
Automate threat data correlation to speed up response.
In part three, we’ll examine the landscape of AI-enhanced vulnerability management tools. We’ll cover:
How leading vendors integrate AI into their platforms.
Real-world comparisons of AI-powered solutions.
Practical guidance on choosing and implementing these tools.
Emerging trends in AI-driven vulnerability management.
For now, focus on modernizing your vulnerability management practices, especially around edge devices. This groundwork will set you up to leverage AI-enhanced capabilities effectively.
Remember, the goal isn’t to overhaul vulnerability management overnight but to evolve in line with modern threats while preparing for advanced tools in the near future. Stay tuned for part two, where we’ll dive into AI’s role in vulnerability management.
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Worth a full read
OWASP: Guide for Preparing and Responding to Deepfake Events
Key Takeaway
Deepfake detection technologies are quickly outdated, emphasizing process adherence over detection.
Cybersecurity strategies should prioritize robust authentication and verification.
Adherence to established processes is crucial in mitigating deepfake attacks.
Awareness training should focus on adhering to processes rather than spotting deepfakes.
Layered security controls offer resilience against evolving deepfake threats.
Regular updates to incident response plans enhance effectiveness against deepfakes.
Human psychology is exploited in deepfake attacks through urgency and pressure.
Identity verification in remote hiring is vital to prevent deepfake-driven fraud.
Effective incident response requires comprehensive documentation and analysis.
Organizations must balance security with accessibility for candidates using assistive technologies.
OWASP: LLM and Generative AI Security Center of Excellence Guide
Key Takeaway
Multidisciplinary collaboration is crucial for effective AI security strategies and solutions.
Regular training enhances team communication, fostering innovative AI security solutions.
Ethical guidelines and audits ensure responsible AI technology deployment.
Proactive risk management protects against AI-related security breaches.
Stakeholder engagement builds trust, enhancing AI security acceptance and support.
Phased COE implementation ensures smooth integration of AI security measures.
Emerging AI security trends require adaptive and robust defense strategies.
AI systems' performance must balance with comprehensive security measures.
Continuous improvement keeps COE updated on evolving AI security challenges.
Transparent communication enhances stakeholder trust in AI security initiatives.
Research Paper
Hacking Back the AI-Hacker: Prompt Injection as a Defense Against LLM-driven Cyberattacks
Summary: The paper introduces Mantis, a defensive framework leveraging prompt injection to counter LLM-driven cyberattacks by exploiting adversarial inputs to misdirect or compromise attackers' systems, achieving over 95% effectiveness in experiments.
Published: 2024-10-28T10:43:34Z
Authors: Dario Pasquini, Evgenios M. Kornaropoulos, Giuseppe Ateniese
Organizations: George Mason University
Findings:
Mantis achieves over 95% effectiveness against LLM-driven attacks.
Prompt injections can be used defensively against AI-driven cyberattacks.
Mantis can autonomously hack back attackers using decoy services.
Final Score: Grade: A, Explanation: High novelty and empiricism with open-source transparency and no conflicts detected.
Wisdom of the week
I am not impressed by money, social status or job title. I’m impressed by the way someone treats other human beings
Contact
Let me know if you have any feedback or any topics you want me to cover. You can ping me on LinkedIn or on Twitter/X. I’ll do my best to reply promptly!
Thanks! see you next week! Simon