Current status of LLM in Cybersecurity
Gen AI systems like LLM and GPT-4 have sparked debate over their potential capabilities in cybersecurity, particularly their ability to hack systems autonomously.
Fortunately, these AI models have demonstrated impressive capabilities in natural language processing and code generation, but their application to autonomous hacking remains limited and largely theoretical.
“Currently, that’s not possible. LLMs like GPT-4 and Microsoft’s Co-Pilot are powerful tools for natural language processing (NLP) and generation,” Dustin says, “but they are not inherently designed to autonomously execute complex attacks like hacking or SQL injection.”
This clearly demonstrates that while LLM is capable of generating code snippets for common exploits when prompted, it lacks the inherent ability to autonomously execute complex cyber attacks.
However, in analyzing advanced LLM’s key capabilities in vulnerability discovery and exploitation, Dustin points out that “LLM cannot currently discover or exploit vulnerabilities autonomously. However, LLM can assist in gathering information about potential vulnerabilities by summarizing known exploits, providing details on how a particular vulnerability can be exploited, and suggesting tools and techniques to use in penetration testing.”
“This means they rely on external scripts or human operators to perform actions on real-world systems, limiting their ability to exploit vulnerabilities autonomously.”
This highlights that LLM currently serves as a supporting tool rather than an autonomous hacking agent: it can provide valuable information and suggestions, but cannot execute complex attacks on its own.
Strengthening your skills through an LLM
However, potential misuse of LLM by threat actors is a concern.
“Threat actors can leverage LLM’s capabilities to aid in the creation of exploits to amplify their malicious activity,” Dustin said. “Take SQL injection as an example: a threat actor might instruct LLM to generate different payloads to test for SQL injection vulnerabilities in different input fields of a web application.”
“Attackers can also use these payloads on targeted web applications to analyze the response. If the response changes in a way that indicates a successful injection, further exploitation may be possible,” he explains.
This scenario illustrates that malicious actors may use LLM to enhance their attack strategy, even when the model itself is not capable of autonomously executing the attack.
LLM vs Traditional Cybersecurity Tools
Humans still play a vital role in cybersecurity today, as it is unlikely that AI will be able to autonomously hack systems without human intervention or knowledge of vulnerabilities in the near future.
“Currently, LLM cannot produce results similar to other automated forms of reverse engineering or exploit development. For example, fuzzing is a better technology than LLM for finding bugs in closed source applications.”
This comparison highlights that established cybersecurity techniques and tools are still superior to LLMs in real-world application.
Looking to the future, Childs suggests a more likely scenario for the application of the LLM in cybersecurity.
“LLMs can be trained to review code for issues before it ships to the market. This form of code review will likely become commonplace before LLMs gain the ability to find vulnerabilities autonomously.”
This perspective highlights the potential for LLMs to contribute positively to cybersecurity by improving code quality and identifying vulnerabilities before they are exploited.
While LLMs have demonstrated impressive capabilities in language processing and code generation, their ability to autonomously hack systems remains limited. Value in cybersecurity today lies in augmenting human expertise and automating benign tasks, rather than leveraging autonomy.
“A combination of technical controls, ethical guidelines, and continuous oversight can help us leverage the benefits of LLM while minimizing the risks associated with its misuse in autonomous hacking and other malicious activities,” Dustin concludes.
As these technologies continue to evolve, it will be important to implement safeguards and ethical guidelines to ensure their responsible use and prepare for adversarial use in the field of cybersecurity.
******
Check out the latest version Cyber Magazine Also, register for our Global Conference Series. Technology and AI Live 2024
******
Cyber magazine is BizClick brand
