Your Security Information and Event Management (SIEM) platform aggregates log data from every corner of your organization and analyzes it for signs of unauthorized activity. When observed activity matches a preconfigured detection rule, it triggers an alert which prompts an investigation. 

Every time that happens, there is a chance that the investigation uncovers genuine threats that could lead to catastrophic damage. But for many security teams, the majority of investigations do not uncover real threats—they result in false positives. 

What are false positives? 

A false positive is an alert that mistakenly assigns risk to a legitimate activity or process. This causes a security analyst to spend time investigating an alert that does not correspond to malicious activity. In a busy security environment with a backlog of alerts to address, might mean missing the chance to investigate true positives that represent serious security threats. 

False positives are a problem for analysts because they can contribute to alert fatigue. If analysts spend most of their day investigating positive alerts that turn out not to be malicious, they have a much higher risk of accidentally overlooking an actual attack. At the same time, these irrelevant alerts drag down productivity and make the security team operate with less efficiency.  

In many if not most instances a misconfiguration in the configured sending source, or even in the detection methodology causes false positives. Security leaders that run SIEM operations using the platform's default configuration are likely to run into this problem because every organization is unique. Default detection rules will not correspond to the way your organization does business. 

False positives can also occur when custom detection rules are improperly implemented. Crafting reliable and accurate alerts is a technical challenge that demands specialist product expertise. 

Few security teams have the background and knowledge necessary to create and deploy high quality custom SIEM rulesets. This is a task best suited for a dedicated teams such as ones you will find in a Security Operations Center (SOC) staffed with professionals with a proven track record of crafting successful security rules.   

Challenges of dealing with false positives 

Alert fatigue is one of the biggest problems security leaders face due to false positives. Its impacts include: 

• Overwhelming backlogs. When there are more alerts than analysts can quickly address, a backlog builds up. This backlog impacts key performance metrics like Mean Time-to-Detect (MTTD) and Mean Time-to-Respond (MTTR). 

• Wasted time and inefficiency. Every false positive requires time and security resources that should have gone towards addressing real cyber-attack risks. Removing false positives from the alert backlog helps security leaders use analyst time effectively. 

• Increased risk from undetected actual threats. False negatives are potential threats that go undetected despite having the appropriate rules in place. When analysts fail to investigate security threats in time, there is a much higher chance that detectable risks will slip through the organization's defenses. 

Sometimes, false positives can be difficult to identify and control without investing in additional security capabilities. Reducing false positives means gaining deeper insight into security events at a crucial time—after detection but before investigation. 

Strategies for reducing false positives 

When it comes to reducing false positives, SIEM configuration is the single most important factor security leaders have control over. When security teams implement SIEM platforms but leave them in their default configuration, the result is often a surge in false positives. 

Fine-tuning alert rules and thresholds is one of the best ways to reduce false positives. This can be a complex task, but it pays impressive dividends over time. 

Every organization has unique operational characteristics and business logic. A properly configured SIEM must take those factors into account when analyzing log data and triggering alerts. 

For example, many SIEMs trigger alerts when users log in from unusual geographical regions by default. This makes sense in a traditional business with on-site employees. In a fully remote working environment staffed by employees from all over the globe, it may not produce meaningful results. 

Security leaders will also need to implement new technologies and capabilities as they are made available. Insights from User Entity and Behavioral Analytics (UEBA) tools and contextualized alert data can significantly reduce the number of false positives that occur in an enterprise environment. 

Best practices for effective security alert management 

Reducing false positives is an ongoing process. Security leaders must commit resources to conducting regular reviews of alert investigations and look for opportunities to improve them. Analyzing false positives can help paint a picture of where the organization's security controls and policies fall short. 

Here are some things you can do to improve the management of security signals in your SIEM: 

• Deploy custom detection rules. Customization helps security leaders improve alert quality by drawing information from real incidents and using it to contextualize malicious behavior when detected. 

• Use behavior-based detection rules. UEBA-enhanced SIEMs distinguish between normal activities and cybersecurity threats based on user behaviors. This dramatically improves the organization's security posture and gives analysts fewer alerts per day to address. 

• Contextualize security alerts with data from other tools. Your Endpoint Detection and Response (EDR) or Network Detection and Response (NDR) may offer valuable perspective on a detected security event. That context can mean the difference between an accurate detection event and a false positive. 

• Implement automation in incident response workflows. Security Orchestration, Automation, and Response (SOAR) technology helps consolidate security incident response and improve the effectiveness of security measures. 

• Automate SOC operations to improve investigation times. SOC automation solutions like Lumifi Shieldvision™ give analysts access to valuable contextual data on cybersecurity incidents in near real-time. Detect threat actor activity and respond to critical incidents with unlimited visibility into your environment while reducing false positives in security alerts.  

Improve detection quality and security monitoring performance with Lumifi 

Reducing false positives does not always require drawing in-house security practitioners away from their daily responsibilities. Managed detection and response vendors like Lumifi can provide on-demand access to proven SIEM expertise. 

Having product experts identify detection rules and security policies that are contributing to analyst fatigue frees up security talent to focus on high-impact strategic initiatives. Lumifi can provide guidance on how to reduce false positives while improving incident response outcomes and optimizing SIEM performance. 

Find out how your organization can achieve operational security excellence with faster incident response, greater visibility into security events, and highly automated incident response plans powered by some of the most advanced technologies in the industry. Schedule a demo to find out more.