In a previous blog, we covered how generative AI is enhancing the speed and effectiveness of security operations, particularly through data synthesis and summarization. However, as threats evolve, security operations teams need to lean on the most advanced tools to contain threats as efficiently and swiftly as possible. Fortunately, one of the newest tools is also one of the most effective. 

AI agents, or agentic AI, perform tasks autonomously, leveraging generative AI to interpret data, make informed decisions, and execute actions without human intervention. In this blog, we’ll explore how agentic AI works within security operations, from planning to execution. We’ll also discuss the importance of choosing a security operations provider with the technical expertise to help you leverage AI capabilities to mature your security program. 

Rapid, Tailored, and Efficient Security Operations 

Agentic AI takes the outcomes of generative AI, like alert data collection and synthesis, and puts them to work, autonomously managing and mitigating threats in real time. Its speed, accuracy, and efficiency lead to faster threat detection and response, ultimately allowing organizations to: 

• Contain threats in minutes: Agentic AI can instantly analyze data, identify threats, and take containment actions without waiting for human input. This rapid response capability is crucial in minimizing the impact of security breaches. 

• Reduce Tier 1 and Tier 2 tasks: SecOps teams spend too much time on mundane activities like monitoring alerts, conducting initial investigations, and performing routine tasks. Agentic AI can take over these manual, time-intensive activities, reducing burnout and allowing human analysts to focus on more strategic and proactive activities, like threat hunting.  

• Achieve business-specific security outcomes, at machine speed: Responses lacking business-specific context can generate false positives and miss critical threats. Agentic AI should tailor its responses to accurately identify and mitigate threats, ensuring that critical issues specific to the business are promptly addressed. 

From Planning to Execution: The Agentic AI Decision-Making Workflow 

Agentic AI systems are specifically designed to replicate human decision-making processes. When applied to security operations, the agentic AI system can plan and formulate investigation steps based on its knowledge of the alert type and any information specific to an organization. It then executes these plans using appropriate generative AI tools for each step. If a step of the plan fails or the agent receives new information, the AI agent can adjust its plan on the fly.  

For example, let’s look at the steps an AI agent might take in the event of an “impossible travel” alert. First, the system would develop a plan using generative AI tools to query security tools for user login information and analyze their login locations. If it identified impossible travel patterns, the agent would then decide whether to reach out to the user. If the user confirmed the travel, the system would update its records and resolve the alert. However, if the user denied travel, the system could execute automated response actions, such as locking the account. Throughout this process, the system would dynamically adjust the plan based on real-time information, like the response from the user.  

This entire process, which could take hours if done manually, can be completed in minutes by an AI agent. 

Not All AI Agents Are Created Equal 

The true effectiveness of agentic AI hinges on the quality of the security operations provider delivering it. A provider with domain-specific knowledge is more likely to deliver and train an agent that can help your security operations reach peak performance. The most advanced AI agents are built with these design principles in mind: 

• Transparency into the agent’s decision-making process so you can understand its reasoning and refine it over time using human feedback, fostering trust in the AI system. 

• Access to real-time internal and external data to reduce hallucination. Providers should augment static training data with external information to produce timely, accurate results.  

• Data privacy: An advanced provider will fully segment customer data and ensure that its AI agent maintains operations strictly within the boundaries of a customer environment, avoiding contamination with other data.  

ReliaQuest: Setting the Standard for Agentic AI with Technology, Experience, and Expertise 

ReliaQuest has produced a first-of-its-kind AI Agent for security operations that eliminates the mundane Tier 1 and Tier 2 tasks keeping your analysts from upskilling themselves and your security program. It autonomously analyzes, investigates, and acts on alerts, allowing security teams to contain threats in minutes instead of hours or days.   

Built within the GreyMatter security operations platform, the ReliaQuest AI Agent is uniquely suited for customers looking to augment their security operations teams, thanks to:  

• Security operations expertise: ReliaQuest has the experience and domain knowledge needed to continuously evaluate and refine the AI Agent’s performance. This feedback loop improves the agent’s logic to reduce false positives over time, resulting in faster, more precise detection, investigation, and response. 

• Comprehensive, up-to-the-minute data access: Through the GreyMatter platform, the AI agent has access to real-time data from any security operations tool in your environment, providing complete alert context almost immediately after detection and enabling fast, thorough investigations. 

• Over a decade of incident response data: The ReliaQuest AI Agent is trained on a proven and extensive cyber analysis methodology (CAM) built on data from years of performing threat detection, investigation, and response for our customers.  

Next in Our Series: AI Use Cases for Security Operations 

In the next blog of this series, we will explore specific use cases for AI in security operations. It will detail how AI solutions can be applied in real-world scenarios across security operations and help defend against things like business email compromise and phishing.