I'm interested in the "red teaming" capabilities of Generative AI (ChatGPT, Gemini). Can these models be used to simulate advanced persistent threats or to automatically suggest patches for zero-day vulnerabilities in real-time?
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The role of Generative AI (ChatGPT, Gemini) in Cyber Security is evolving toward a "co-pilot" model for security analysts. For red teaming, these models can generate highly convincing phishing emails or help craft complex scripts for penetration testing. On the defensive side, we are seeing them used to analyze logs at scale and suggest firewall rules or code patches for known vulnerabilities. However, automated patching is still risky because a patch that fixes a security flaw might break the application's functionality. I believe we are still a few years away from fully autonomous patching, but the AI's ability to prioritize which vulnerabilities to fix first is already saving SOC teams a massive amount of time.
Deborah, will the rise of Generative AI (ChatGPT, Gemini) in security lead to an "arms race" where hackers use it to find bugs faster than we can patch them?
It’s also excellent for translating complex threat intelligence reports into actionable summaries for non-technical executives.
Exactly, Paul. Getting budget for security upgrades is much easier when the AI can clearly explain the business risk of a specific technical vulnerability in plain English.
Steven, that arms race is already happening. Malicious actors are using generative tools to automate the creation of malware and discover vulnerabilities in open-source libraries. This is why it’s critical for security professionals to master these AI tools as well. We need to use the generative power of these models to build more resilient, self-healing systems that can detect and respond to these AI-driven threats in milliseconds rather than hours or days.