In today’s evolving cybersecurity landscape, security operation centers (SOCs) are constantly bombarded with incidents ranging from minor alerts to highly complex threats. Given this surge in cyberthreats, security teams are often overwhelmed by the sheer volume of incidents, many of which require time-consuming manual investigation. In response to this challenge, Microsoft’s Copilot for Security guided response has become a vital tool for enterprise customers. Copilot guided response is a state-of-the-art AI-driven system that helps analysts efficiently navigate incidents by providing real-time recommendations for investigation, triaging, and remediation.

For commercial customers, the importance of Copilot guided response is clear. It enables faster and more accurate decision-making, reducing downtime and helping prevent potentially disastrous breaches. Integrated into Microsoft’s unified security operations platform, that brings together the full capabilities of an industry-leading cloud-native security information and event management (SIEM), and comprehensive extended detection and response (XDR), Copilot guided response is perfectly situated to bolster enterprise defenses and assist analysts in complex investigations across an increasingly complex and hostile threat environment​.

Challenges of Guided Response in Cybersecurity

Despite the obvious benefits, implementing a scalable and effective guided response system presents several key challenges:

Complexity of security incidents – With tens of thousands of detection rules and a growing array of 1st and 3rd party security products across organizations, incidents vary significantly in complexity. Many incidents are intertwined with numerous alerts, each representing different levels of threat, making it difficult for systems to consistently provide accurate guidance​.
High precision and recall requirements – Analysts need accurate recommendations to prioritize and remediate incidents correctly. This requires guided response systems to maintain both high precision (correct recommendations) and high recall (catching all relevant threats). Any system error can result in costly false positives (alert fatigue) or, worse, missed true positives that lead to breaches​.
Scalability – A significant challenge is the ability to scale recommendations to handle millions of incidents across global networks and terabytes of data. Guided response systems must seamlessly process telemetry in near real-time to provide on-demand analysis.
Adaptability to SOC preferences – Every SOC operates with different configurations, products, and workflows. Guided response systems must be flexible enough to adapt to these preferences while maintaining consistency and accuracy in recommendations​.
Continuous learning – As threat actors evolve, so must guided response systems. The capability to continuously learn from new data and improve autonomously is critical to staying ahead of advanced persistent threats (APTs) and emerging attack vectors​.

Transforming Security Response with AI

To address these challenges, Microsoft’s Copilot guided response introduces advanced AI-driven features to automate and streamline the incident response process by empowering security analysts with the tools they need to respond swiftly and effectively to complex security incidents.

Copilot guided response enhances three critical aspects of incident management: (1) incident triaging, (2) remediation action recommendation, and (3) similar incident investigation. With its intelligent automation, Copilot guided response reduces the manual workload on SOC analysts, improves response times, and increases the precision of both triaging and remediation efforts. By utilizing historical data, real-time threat intelligence, and machine learning, Copilot guided response enables organizations to operate more efficiently, while mitigating the risks associated with advanced cyberthreats. This system not only improves the speed of detection and response but also ensures that analysts have the most relevant information and guidance to make informed decisions during every stage of incident investigation and resolution.

Key Innovations

The Copilot guided response architecture is capable of processing millions of incidents each day with latency of just a few minutes. Our unified ML system scalably deliver three core SOC capabilities—(1) investigation, (2) triaging, and (3) remediation—seamlessly adapting to a range of scenarios, from single alerts to complex incidents involving hundreds of alerts, where each alert is categorized into one of hundreds of thousands of distinct security detector classes. Here’s how:

Incident Triaging

Traditionally, SOC analysts have been burdened with manually sifting through thousands of alerts, determining which ones require immediate action. With Copilot guided response, this process is streamlined through AI-driven triaging. The system evaluates incoming incidents, helping analysts assess the nature of the incident with real-time grade recommendations—True Positive (TP), False Positive (FP), or Benign Positive (BP)—based on historical data and threat patterns. This drastically reduces the time needed for incident prioritization, ensuring that critical threats are handled first while minimizing incident fatigue (Figure 1).

Figure 1. Guided response incident triage recommendation

Containment and Remediation Action Recommendation

Beyond triaging, Copilot guided response excels in remediation action recommendation, offering tailored responses for each incident. Whether it’s isolating a compromised machine, suspending a user account, or quarantining a file, Copilot guided response dynamically suggests the most effective actions to contain and mitigate the threat. The system’s AI models continuously learn from past incidents and analyst feedback, allowing it to recommend precise, context-aware remediation steps that adapt to the evolving threat landscape (Figure 2).

Figure 2. Guided response incident containment and remediation action recommendations

Similar Incident Recommendation

Copilot guided response’s similar incident recommendation feature is designed to streamline the investigation process by automatically identifying historical incidents that are highly relevant to the current one. When a new incident is detected, the system compares it against a vast repository of up to 180 days of past incidents using advanced machine learning algorithms that analyze multiple features—such as attack vectors, indicators of compromise (IOCs), and threat actor behaviors. This allows Copilot guided response to surface incidents that bear significant resemblance to the current one, providing analysts with crucial context and insights, and reducing the time analysts spend searching for relevant historical data, allowing them to focus on the investigation at hand.

Figure 3. Guided response similar incident recommendations

Looking Ahead

Copilot guided response significantly enhances SOC operations by guiding security analysts through crucial investigation, triaging, and remediation tasks, adeptly handling everything from simple alerts to complex incidents. The framework has undergone rigorous internal testing and refinement through feedback loops with security experts and real-world customer interactions. The result is a continuously evolving system that maintains high performance in both offline and online environments. With 89% positive user response rates, Copilot guided response has already demonstrated significant value in production environments of customers using Microsoft Defender XDR or the unified security operations platform. We also release an in-depth paper detailing the innovative ML architecture powering these capabilities, representing the first time a leading cybersecurity company has openly discussed an industry-scale guided response system. 

Learn More

Check out our resources to learn more about the Copilot for Security Guided Response:

Read the Guided response documentation  
Read the full paper detailing the innovative ML architecture powering Copilot guided response

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