LLM and its new role in cybersecurity

A recent study showed that large linguistic models (LLMs), especially GPT-4, are able to autonomously exploit 1-day vulnerabilities in real-world systems with a success rate of up to 87% when given CVE descriptions, a capability that cannot be achieved by other systems. . Open source models or vulnerability scanners. Without CVE descriptions, the effectiveness of GPT-4 drops dramatically to 7%, indicating that it requires detailed information about vulnerabilities for successful exploitation. The research highlights significant progress in use artificial intelligence (Amnesty International) in cybersecurity, which poses potential risks and benefits. The findings call for a re-evaluation of the use of these capable people Amnesty International– Agents in the field of cybersecurity, taking into account their ability to exploit vulnerabilities independently. Ethical considerations are discussed, with an emphasis on responsible use and the importance of safe use of LLM techniques in sensitive environments.

The paper titled “LLM Agents Can Autonomously Exploit Single-Day Vulnerabilities” by Richard Fang, Rohan Bindu, Akul Gupta, and Daniel Kang examines the capabilities of large language models (LLMs), especially GPT-4, to exploit “single-day vulnerabilities.” (i.e., one-day vulnerabilities) to independently exploit daily vulnerabilities in real systems. The study is important because it highlights the advanced capabilities of LLM not only in benign applications, but also in potentially malicious operations, such as cybersecurity exploits.

Key findings from the study show that master's degree holders, particularly GPT-4, have a high success rate (87%) in exploiting “one-day vulnerabilities” from a dataset when given a detailed CVE description. In contrast, other models and tools have not shown any success, highlighting the advanced potential of GPT-4.

Applications of LLM and its new role in cybersecurity

The background section explains the concept of computer security and the role of LLM agents. He points out that previous research has mostly involved “gaming problems” or controlled environments, but this study uses real-world scenarios to test the effectiveness of MBA hacking. This section sets the stage by discussing the broader context of LLM applications in various fields and its emerging role in cybersecurity.

Standard 15 vulnerabilities in the real world, for one day

The post describes a methodology that involves creating a benchmark of 15 real-world vulnerabilities for a single day. These vulnerabilities come from the Common Vulnerabilities and Exposures (CVE) database and academic papers, with an emphasis on those that can be reproduced in a controlled environment. The LLM agent used in the study, equipped with access to CVE descriptions and various tools, demonstrates the simplicity and at the same time effectiveness of using such models for cybersecurity tasks.

Results and analysis

Key results show that GPT-4 successfully exploited 87% of vulnerabilities when given CVE descriptions, a significant achievement compared to other models and tools such as ZAP and Metasploit, which achieved 0% success. The significant decrease in the success rate (to 7%) without CVE description demonstrates the importance of detailed vulnerability information for successful exploitation by LLMs.

Downside and Upside Risks of LLM Technologies

The Discussion section reflects the implications of these capabilities, considering both the potential misuse of LLM techniques in malicious contexts and the opportunities to improve cybersecurity defenses by understanding and anticipating such exploits. The ability of LLMs to perform complex tasks independently raises important questions about the use and control of these technologies in sensitive environments.

Ethical considerations

The Ethics Statement addresses the potential negative uses of LLMs in piracy and emphasizes the importance of responsible use and further research to mitigate the risks associated with piracy. Amnesty International– Skills related to cyber security. The research adheres to ethical guidelines, with experiments conducted in isolated environments to avoid real-world harm.

Conclusion

In summary, the paper provides a comprehensive examination of the independent capabilities of LLMs such as GPT-4 in exploiting cybersecurity vulnerabilities, showcasing both technological advances and associated risks. It is an invitation to Amnesty International– and cybersecurity communities, in developing robust security measures and ethical guidelines for their use Amnesty International– Cooperation techniques in sensitive areas.