Leveraging Generative AI: Transforming Your Security Operations Center

Generative AI’s Role in the Security Operations Center (SOC)

The Impact of Generative AI in IT Security

Generative AI, coupled with large language models (LLMs), is causing a significant shift in the IT security industry. Vendors, including Microsoft and Google, are investing millions of dollars in generative AI and LLM training for diverse use cases. While ChatGPT is a widely discussed generative AI model, its potential in the security space is currently limited due to access restrictions to the live Internet and safety tuning. However, security practitioners operate in a fast-paced environment characterized by zero-day threats and constantly evolving tactics. To harness the full potential of generative AI, it is crucial to connect it to the local enterprise data store and grant access to the Internet. Leading security providers are embracing this approach by enabling Internet access, providing APIs to security-specific generative AI solutions, and training LLMs using vast amounts of security intelligence.

The Benefits of Generative AI for Different SOC Team Members

Generative AI holds significant potential for enhancing the capabilities of various roles within a Security Operations Center (SOC).

Level 1: Cybersecurity Specialists

Cybersecurity specialists at the entry-level in the SOC are responsible for triaging alerts generated by the technology when identifying unusual behaviors or predefined alert conditions. Their tasks include confirming true positives and filtering out false positives. Generative AI can greatly assist these specialists in understanding the implications of an alert and making informed decisions on whether to escalate the issue. With the ability to explain atomic events and sequences of events, generative AI can shed light on specific device vulnerabilities. Automating certain tasks such as triaging and prioritizing alerts is also within the realm of possibilities. Additionally, generative AI allows specialists to ask questions and receive more comprehensive responses compared to traditional search engines.

Level 2: Cybersecurity Analysts

Cybersecurity analysts take over from Level 1 specialists, validating true positives, gathering relevant data, and investigating incidents. In managed security service environments, challenges arise from dealing with multiple and diverse customer environments. This limits the practicality of having numerous specialists available 24/7. Generative AI can serve as an invaluable resource for parsing sequences of events, providing quick and efficient explanations of incidents, threat nature, and vulnerability. Rather than specializing in specific tech stacks that evolve over time, Level 2 analysts must develop deep expertise in utilizing generative AI. “Prompt engineering,” or the skill of structuring prompts to obtain optimized responses from the AI, becomes critical. After all, the answers lie within the data, and formulating the right questions is an art form.

Level 3: Analysts

The most sophisticated users of generative AI within the SOC are the analysts at Level 3. They leverage AI capabilities to accelerate threat response, forensics, and threat hunting. Analysts can utilize generative AI’s scripting and search query generation features to delve deeper into investigations. This level of usage enables analysts to extract maximum value from generative AI in their work.

Other Applications of Generative AI in the SOC

Aside from its direct impact on SOC roles, generative AI also finds application in various other areas within the Security Operations Center:

– SOC Engineering: Generative AI can assist in identifying vulnerable configurations and detecting issues that could impact hardware performance or uptime in managed service environments.
– Threat Content Management: The technology can be leveraged to capture new threat intelligence and seamlessly integrate it into the platform.
– Customer Support: Generative AI can aid individuals who may not possess strong writing skills in creating informative, concise, and technically precise email communications to keep customers informed about events in their infrastructure.

Generative AI’s Potential and Limitations

Generative AI holds the promise of significantly reducing the mean time to detect and respond to threats, becoming a primary objective for every security team. Enhanced accuracy and cost reduction follow as immediate benefits. However, it is important to acknowledge certain caveats associated with the technology. Cybercriminals may exploit generative AI to develop more sophisticated threats and probe code for vulnerabilities. Furthermore, the effectiveness of generative AI relies heavily on the quality and timeliness of the data on which it is trained. Incorrect or biased results are possible, and the value of the answers received is contingent upon formulating the right questions.

Generative AI effectively addresses pain points in the cybersecurity industry, including the shortage of skilled professionals and the growing complexities of infrastructure protection. However, it is important to note that generative AI is not intended to replace human expertise. Used correctly, it can empower security professionals to be more effective, productive, and well-equipped to combat evolving threats.