How AI Can Help with Security Alert Correlation

As cybersecurity threats grow more complex, the volume of alerts facing security teams has skyrocketed, putting a strain on security operations. Managing these alerts effectively is crucial for timely and accurate incident response. Alert correlation plays a key role in this process, helping to connect the dots between related events and enhancing overall security operations. By effectively correlating alerts, security teams can enhance their operations, improve incident response times, and better protect their organizations.

Understanding Alert Correlation

First, let’s define alert correlation. Correlation analyzes and links seemingly disparate alerts to uncover broader patterns, connections, or incidents. This is a process that goes beyond simple alert aggregation, which groups similar alerts together. This deeper analysis for correlation enables security teams to identify and prioritize threats that might otherwise go unnoticed when alerts are viewed in isolation.

3 Types of Correlations

1. Temporal Correlation: This type of correlation connects events based on their occurrence over time. For example, a series of failed login attempts followed by a successful login from the same IP address could be temporally correlated to suggest a potential brute force attack.
2. Contextual Correlation: Contextual correlation links alerts based on shared contextual data, such as IP addresses, user behavior, or device information. For instance, multiple alerts originating from the same IP address or involving the same user account may indicate coordinated or targeted activity.
3. Pattern-Based Correlation: Pattern-based correlation involves identifying sequences or patterns in alerts that signify a specific attack technique or methodology. This could include recognizing a pattern of lateral movement within a network that aligns with known advanced persistent threat (APT) behaviors.

Why Correlation Matters

Alert correlation is crucial for both alert triage and more complex security operations tasks, such as threat hunting. By correlating alerts, security teams can:

• Speed Up Mean Time to Detect (MTTD) and Mean Time to Respond (MTTR): Correlation helps in quickly identifying sophisticated threats that might produce low signals individually. However, when these signals are correlated, they reveal a more significant threat, allowing for faster detection and response.
• Reduce Dwell Time: Correlating alerts helps to identify benign activity and false positives more quickly, reducing the time that security teams spend investigating non-threats. This efficiency is vital in preventing real threats from slipping through the cracks.

Challenges and Considerations

Despite its importance, effective alert correlation presents several challenges:

Skill Shortage

Conducting accurate and meaningful correlations often requires highly skilled analysts who can identify complex patterns. However, in many SOCs, junior analysts are tasked with initial alert triage, which increases the risk of missing critical correlations at the earliest stages of an investigation. This can prevent more experienced analysts from ever seeing these potentially significant patterns.

Time Consumption and Scalability

While thorough correlation analysis for every alert during the initial triage process would be ideal, the reality is that the sheer volume of alerts makes this impossible for most security teams to handle manually. Without the help of advanced technology and automation, conducting correlations at scale is unfeasible, leading to potential gaps in security coverage.

How Intezer Can Help with Alert Correlations

Intezer addresses the challenges of alert correlation with its autonomous SOC solution. This solution automates the correlation of complex alerts, enhancing both the initial alert triage process (SOC L1) and AI-driven decision-making. Additionally, Intezer provides enrichment for each alert based on correlated information, expediting more advanced investigations, such as those involving escalated alerts and threat hunting activities.

Intezer’s solution can correlate alerts by various factors, including:

1. User: Analyze alerts based on user activity.
2. Device: Correlate alerts originating from specific devices.
3. File (hash): Track and link alerts related to specific file hashes.
4. Process Path: Correlate alerts based on the execution path of processes.
5. Time: Utilize temporal correlations to connect events over time.
6. IP Address: Link alerts associated with particular IP addresses.
7. URL: Correlate alerts related to specific URLs.
8. Threat Actor and Malware Family: Identify patterns associated with known threat actors or malware families.

Enriched Information for Correlated Alerts

Intezer enriches correlations with additional data to provide deeper insights:

• User Info: Fetch user details, including name, role, team, department, and office location from identity solutions such as Microsoft Entra or Okta.
• User Risk: Calculate user risk based on recent alerts related to that user.
• Endpoint Risk: Assess endpoint risk by analyzing recent alerts linked to the device.

Effective alert correlation is essential for managing the overwhelming volume of alerts and enhancing security operations. However, the challenges of skill shortages, time consumption, and scalability necessitate the use of advanced tools and automation. Intezer’s autonomous SOC solution provides the necessary capabilities to conduct sophisticated alert correlations, enabling security teams to respond more quickly and effectively to emerging threats.

If you’re interested in seeing how Intezer can transform your security operations through advanced alert correlation, you can book a demo now.

The post How AI Can Help with Security Alert Correlation appeared first on Intezer.