Drowning in False Positives? Your Detections Probably Suck

Being on a security team these days can be brutal. There is more data to monitor than ever, and hackers are developing attacks using sophisticated social engineering tactics. Not to mention the omnipresent “rise of AI” that spawns new, emerging threats to try to stay ahead of. And you’re supposed to do it all with technology that is old enough to drink.

SIEM vendors are letting security teams down, but let’s focus right now on one specific feature they lack: flexible detections. We all know that inflexible detections suck. We’ve weathered the alert storms they generate and wasted too much time cleaning up the aftermath. It’s time to evolve beyond these legacy SIEMs that set us up for headaches. Security teams deserve better than these outdated solutions to meet the realities of modern-day challenges.

The Pitfalls of Inflexible Detections:

• Vague detections that cannot be tuned or edited lead to a barrage of false positives and alert storms that your team has to deal with instead of focusing on legitimate alerts.
• Teams leave critical gaps in their threat coverage without the option to write custom detections.
• The limitations of basic detection logic limit rule efficacy and lead to numerous detections to replicate the impact of a single detection built with advanced features.
• Incident response times increase when analysts don’t have access to adequately enriched alerts and have to hunt down critical alert context.

Don’t Get Caught in an Alert Storm

Every security analyst has dealt with it: alert fatigue. Security engineers writing inflexible detections set their analysts up for a bad time. When your detection quality is poor, your alert quality will also be poor. You know the saying: garbage in, garbage out. Your team will be hammered by high volumes of false positive alerts and forced to spend valuable time wading through them instead of focusing on high-value alerts in the first place. This ultimately drives up the cost of securing your organization by requiring more butts in seats to get enough eyes on glass. It’s either that or risk not triaging all your alerts and potentially missing legitimate threats.

CYA and Plug Those Gaps

Each security team has a unique environment and its own set of needs to meet with its SIEM. Rigid, predefined rule logic is going to lead to poor threat coverage. Most legacy OOTB rules aren’t customizable, and at worst, you have no visibility into how they were constructed, leading to a black box effect that only exacerbates coverage gaps. Even when you get some coverage, however weak, from OOTB rule sets, what about your custom log sources? Most teams will have at least one custom log source to ingest and monitor, and legacy SIEMs rarely offer the flexibility to create custom rules to cover that data. Leaving log sources unsecured defeats the entire purpose of having a SIEM and leaves teams vulnerable to attacks.

OOTB rules are an OK starting point, but they won’t provide enough threat coverage alone. Tuning existing rules or creating new high-fidelity rules is the best way to plug the gaps in your coverage and reduce false positive alerts. Restrictive query languages, like LogScale’s LQL, can make it challenging to create high-quality detections that actually deliver the threat coverage you’re trying to achieve with a SIEM. You could spend extra time creating multiple, redundant rules, needlessly increasing the complexity of your environment and generating redundant alerts, further burdening your analyst team.

The Clock’s Ticking

During a potential incident, every second counts, and inflexible detections will eat up a lot of valuable seconds. The limitations of basic detection features result in poor alert quality compared to detections built with advanced features like enrichment and actor profile context. The more detail your alerts can deliver to your analysts up front, the easier it is for them to triage the alert and investigate the related events appropriately. For even faster alert remediation, contextually enriched alerts pair wonderfully with a SOAR platform that can automate incident response for low-level alerts, freeing up your team’s time to focus on higher-priority work.

Evolve Your Team with Flexible Detections

Flexible detections help your team:

• Reduce false positive alerts with high efficacy, properly tuned, and customized rules
• Deliver advanced features like dynamic severities, alert enrichment like GreyNoise and actor profiles, rigorous unit testing, and lookup tables
• Scale security operations without requiring an ever-increasing headcount
• Improve threat coverage with customizable OOTB detections and the ability to create from-scratch new detections
• Speed up incident response and investigations with contextually enriched alerts to help your analysts move faster

As organizations wrestle with the increasing volume of data to monitor, inflexible detections trip up otherwise effective security teams. With the rise of hackers employing sophisticated social engineering tactics and emerging threats like AI-based attacks, the need for agility and adaptability in detections becomes more critical. Security teams that step into the future and embrace flexible detections will enhance their security posture, reduce false positives, minimize gaps in threat coverage, and expedite incident response efforts.