Digital Event Horizon
Generative AI has the potential to revolutionize red teaming operations, but concerns surrounding its maturity, explainability, and liability have raised questions about its suitability for use in information security applications.
Generative AI (Gen AI) is being explored for its potential applications in red teaming, a crucial aspect of information security operations. Gen AI can perform "the heavy lifting" required in red teaming operations, but its lack of transparency and explainability poses challenges for organizations to defend against attacks or provide evidence. The use of Gen AI in red teaming is still shrouded in uncertainty, with concerns raised about over-reliance on AI systems and their limitations. Regulations and policies are needed to govern the deployment of Gen AI in cybersecurity to prevent over-consumption and ensure responsible use. The maturity level of current Large Language Models (LLMs) is a concern for advanced red teaming operations, and liability concerns arise when using generative AI systems in penetration testing.
In the ever-evolving landscape of information security, technology has long been touted as a means to improve and enhance various aspects of cybersecurity. One such innovation that has garnered significant attention in recent times is generative AI (Gen AI). While Gen AI holds immense promise for revolutionizing numerous fields, its potential applications in red teaming – a crucial aspect of information security operations – are still shrouded in uncertainty.
Red teaming, also known as "white-hat hacking" or "penetration testing," involves simulating cyber attacks on an organization's systems to identify vulnerabilities. This process is essential for ensuring the robustness and resilience of an organization's cybersecurity posture. In recent years, red teams have begun experimenting with generative AI applications in their efforts to enhance their capabilities.
According to Laura Dobberstein, a security expert, Gen AI can indeed perform "the heavy lifting" required in red teaming operations. However, there is a crucial caveat: the lack of transparency and explainability surrounding the output of Gen AI systems can make it challenging for organizations to defend against potential attacks or provide evidence of an attack that has occurred.
The recent Canalys APAC Forum in Indonesia brought together panelists to discuss the use of generative AI in red teaming. The forum provided a platform for experts to share their perspectives on the benefits and challenges associated with integrating Gen AI into information security operations.
IBM's Red Team, which was present at the forum, reported using AI to analyze data from a major tech manufacturer's IT estate and discovered a critical flaw in an HR portal that allowed unauthorized access. According to Purushothama Shenoy, IBM's APAC Ecosystem CTO, this experience demonstrated how AI can accelerate red teaming operations by automating tasks such as analyzing multiple data feeds and applications.
However, concerns were raised about the risks associated with over-reliance on Gen AI systems. Mert Mustafa, an eSentire security expert, warned that organizations must be cautious not to overlook the potential pitfalls of their AI-driven solutions.
"AIs will replace some human tasks, but we don't want an over-reliance on them," he cautioned.
Furthermore, Kuo Yoong, head of cloud at Synnex's Australian operations, pointed out a critical limitation of Gen AI systems: their inability to provide detailed explanations for their actions or decisions. This lack of transparency can be problematic when dealing with governance professionals or in court.
"AI can't go on the stand and explain how it went through those activities to find threats," Kuo Yoong noted.
The debate surrounding the use of generative AI in red teaming operations has sparked discussions about the need for regulations and policies to govern its deployment. Nishant Jalan, Galaxy Office Automation's director of cybersecurity and networking, advocated for limits on the use of Gen AI in cyber security to prevent over-consumption.
Another expert, Kevin Reed, a CISO at Acronis, questioned whether generative AI is mature enough to be used by red teams. He suggested that current LLMs (Large Language Models) are not ready to handle the complexity and context required for advanced red teaming operations.
"The use of Gen AI for security operations is in the early stages," Reed noted. "Use cases will evolve, and new ones will emerge."
In addition, Bryan Tan, partner at tech-centric law firm Reed Smith, raised concerns about the liability associated with using generative AI systems in penetration testing. He suggested that the operator providing the pen testing service would be held responsible for any actions taken by the AI system.
"Who is responsible for the generative AI conducting the pentest?" Tan asked.
As the use of generative AI continues to evolve, it is essential for organizations and regulatory bodies to develop guidelines and frameworks for its deployment in information security operations. While Gen AI holds immense potential for enhancing red teaming capabilities, it also introduces new challenges that must be addressed through careful consideration and planning.
Related Information:
https://go.theregister.com/feed/www.theregister.com/2024/12/20/gen_ai_red_teaming/
Published: Thu Dec 19 22:17:46 2024 by llama3.2 3B Q4_K_M
