Tackling Alert Fatigue in Security Operations

In every security program, risk discovery is one of the first milestones. Once teams have the ability to detect abnormal events on their systems, the flow of operational alerts begins. But this ability comes with the burden of manual analysis and it’s hard to do well.

No organisation can feasibly review every collected security event to determine if it’s malicious. The Security Operations Center (SOC) model, often with a tiered-analyst structure, was created to centralise monitoring, triage and response. Through 24/7 operations and structured workflows, SOCs enable organisations to detect and respond to threats systematically. However, a significant gap often exists between desired state and the reality faced by analysts.

For most SOCs the challenge is simple: too many alerts, too few humans. When overloaded, SOCs experience alert fatigue, a state where analysts and engineers get flooded with thousands of low-signal alerts that impede their stated mission of detecting and mitigating threats.

Tooling fragmentation makes it worse. Many SOCs rely on 20 or more disconnected tools, each producing its own narrowly focused alerts that fail to account for broader operational landscape. As a result, false positives and benign true-positive events dominate the workload, often making up 95% of alerts. Your analysts become exhausted, desensitised, and risk missing important alerts buried in the daily cruft.

The Discovery-Mitigation Imbalance

In detection and response, your goal is to allocate limited resources effectively. Alert fatigue arises from a fundamental imbalance: finding risks is far easier than fixing them.

Take vulnerability hunting. An hour spent finding vulnerabilities can translate into weeks of remediation work for other teams. Similarly, creating a detection rule might take minutes, but a poorly crafted one can impost a flood of downstream alerts that overwhelm operational capacity.

This is the "lever effect" in action: a small, seemingly innocuous action—like an overly broad detection rule—can generate disproportionate amounts of work for your teams. Your SOC, already spread thin, is left to deal with a cascade of low-value signals that detract from focusing on higher-value signals.

Growing Complexity

As a security program matures, complexity grows. Telemetry forms the foundation of monitoring, translating raw activity into insights of what’s happening across an environment. Logs are the cornerstone of this visibility.

Over time, you add new logs, detection rules, and threat intelligence feeds are added to expand coverage. While these additions improve visibility, they also increase operational complexity, which further amplifies alert fatigue. Your SOC analysts, tasked with sorting alerts as benign or malicious, face an ever-increasing volume.

Alerts themselves are often wide-ranging in scope, covering everything from potential threats, compliance violations and misconfigurations. Many lack sufficient context or clarity, forcing analysts to piece together fragmented data from disconnected tools. Without robust detection standards, investigations stall, clogging workflows and burning analyst time.

False Negatives

The lack of clarity, combined with alert volume, drives fatigue. Teams routinely sift through thousands of alerts each day, manually prioritising a subset for deeper scrutiny. This often requires hours of investigation, spread across disconnected tools. False positives and benign alerts dominate the workload, accounting for over 90% of processed alerts. While false positives can be reduced with robust detection engineering frameworks, they still consume time and effort.

False negative sensitivity looms large. Unlike false positives, which scale linearly, false negatives carry an inherently non-linear impact. Missed threats cascade unpredictably, often leading to severe incidents such as Merck’s $1.3 billion breach. And while frustrating, false positives remain necessary—efforts to eliminate them entirely risk blinding your SOC to meaningful signals.

Your SOC analysts find themselves trapped in this balance: new data sources and telemetry generate more alerts, increasing complexity and investigation volume. This pressure stretches your timelines—with some teams averaging four days to analyse an issue and over 25 days to remediate it.

Without deliberate intervention, this cycle continues unchecked, pushing analysts toward burnout and diminishing their ability to effectively respond to threats. Breaking free requires a holistic approach: better engineering standards, and tooling designed to support humans at the centre.

Breaking the Cycle

Having spent over a decade building and iterating on detection and response programs, I’ve found success leveraging the following strategies:

1. Automate and Enrich: Leverage automation as a foundational strategy. Enrich alerts with context, integrate threat intelligence, and automate context collection so analysts don’t have to perform manual looks across multiple tools. Freeing up this time allows your analysts to focus on pressing investigations.
2. Rigorous Rule Reviews: Treat detection rules like code. Require peer reviews to ensure quality and minimise false positives. Your engineers should eat their own dogfood and be held accountable for the impact of their rules, preventing poorly calibrated detections from causing unnecessary churn.
3. Make Time for Hunting: Not every alert needs immediate responses. Let your detection teams demote low-confidence alerts into hunting exercises. This gives analysts space to creatively engage with your environment, rather than constantly firefighting.
4. Feedback Loops: Track why your alerts get closed. Was it a false positive? Did it lack justification? Use this data to refine rules and reduce noise.
5. Engage End Users: Sometimes the fastest route to context is direct engagement with your employees. A quick check about a suspicious login can save hours of analysis.
6. Accountability Through Metrics: Track your false positives and noise levels. Hold teams accountable and optimise continuously. Monthly stakeholder reviews drive clarity and improvement.

Weve's Role in an AI-Driven SOC

At Weve, we think a lot about how to make security operations sustainable for the humans in the loop. Today's SOCs are stretched thin, drowning in alerts from increasingly complex environments. Traditional automation hasn't lived up to the promise.

We use advanced language models to handle the repetitive, time-consuming tasks analysts face daily. This lets them focus on what matters: investigating real risk and driving response.

The timing couldn't be better. Cloud adoption, custom development, and regulatory pressure keep adding complexity. Meanwhile, adversaries aren't slowing down.

Weve was built to address these challenges. By combining decades of operational experience with advanced tooling, we help your SOC transcend low-value, repetitive alert tasks and focus higher-order work.