Researchers have noted the growing influence of large language models (LLMs) in the cybersecurity field, with both positive and negative implications for vulnerability research and exploit development. While LLMs have shown promise in accelerating vulnerability discovery and assisting in exploit writing, there are concerns about their reliability and the potential for malicious actors to exploit these tools for nefarious purposes.
In a recent interview, cybersecurity expert Niță highlighted his use of LLMs for researching specific topics and generating payloads for brute-forcing. However, he also cautioned that the models are still inconsistent in targeting specific types of flaws. Despite their limitations, many vulnerability researchers have found LLMs to be valuable in various aspects of their work, including accelerating the discovery of vulnerabilities, re-engineering malicious payloads for evasion, and automating the creation of vulnerability disclosure reports.
On the flip side, there is evidence to suggest that malicious actors are also utilizing LLMs for their own purposes. Microsoft and OpenAI recently released a report detailing how some well-known advanced persistent threat (APT) groups have been leveraging LLMs for reconnaissance, scripting techniques, anomaly detection evasion, and vulnerability research. This raises concerns about the potential use of LLMs by threat actors to enhance their capabilities and stay ahead of defenders.
The adoption of LLMs and generative AI among threat actors is likely to continue to grow, posing a challenge for organizations and security teams. It is essential for defenders to keep pace with these advancements and leverage similar tools to enhance their own capabilities in detecting and defending against cyber threats. By understanding the potential risks and benefits of LLMs in the cybersecurity landscape, organizations can better prepare themselves to combat evolving threats.
Overall, while LLMs have shown promise in improving the efficiency and effectiveness of vulnerability research and exploit development, they also present challenges in terms of reliability and the potential for misuse by malicious actors. As the cybersecurity landscape continues to evolve, it is crucial for researchers, organizations, and security teams to stay vigilant and adapt to the changing threat landscape by embracing new technologies and strategies to protect against cyber threats.