How to Solve the Problem of Alert Fatigue

Security Operations Centre (SOC) analysts are at the forefront of cybersecurity defence, managing thousands of alerts every day. The overwhelming volume of these notifications makes it increasingly difficult to distinguish legitimate threats from false positives, leading to analyst burnout and operational inefficiencies. Studies show that up to 62% of alerts are ignored, resulting in missed threats and the further weakening of an organisation’s security posture. Consequently, this can lead to an increased risk of significant cyberattacks occurring. 

Understanding alert fatigue: the human factor

This type of fatigue creates a cyclical problem, one where analysts become desensitised to the volume of alerts. As a consequence, legitimate threats can be missed amid a large number of alerts. Alerts generated by various tools, including firewalls, intrusion detection systems, endpoint protection platforms, and cloud security, require constant triage and investigation. This persistent workload places substantial cognitive strain on security teams, increasing the likelihood of errors and reducing operational efficiency.

“We are getting too many alerts, many of which are false positives, meaning our team is wasting time investigating the wrong things, and things are slipping through the net“ CYJAX customer’s previous experience 

A key driver of alert fatigue is the high number of false positives that are produced by security tools which prioritise caution over precision. Redundant notifications, which are triggered across multiple platforms for the same potential threat, compound this issue. Furthermore, many alerts lack meaningful context, compelling analysts to spend additional time and resources on manual investigations. This often results in an increased operational burden on security teams.

Research reveals that up to half of all security alerts are false positives, resulting in the misallocation of valuable resources and time. A substantial proportion of SOC teams acknowledge that the volume of alerts is substantial enough that they are forced to ignore certain notifications. Consequently, organisations waste thousands of hours annually addressing alerts that do not present a genuine threat.

Real world examples 

The consequences of alert fatigue are not just hypothetical, and they have led to major cybersecurity breaches with serious financial, reputational, and regulatory implications. Several high-profile incidents underscore the critical need to address alert overload and improve alert management strategies:

• Sellafield (2024): UK-based nuclear site Sellafield faced serious cybersecurity lapses after security teams ignored crucial alerts amid receiving such a high volume. Investigations revealed that outdated systems and ineffective alert management allowed potential vulnerabilities to go unnoticed for years.
• T-Mobile data breaches (2023): T-Mobile suffered multiple breaches in 2023 when attackers exploited vulnerabilities which triggered alerts but were overlooked. The organisation’s security teams faced a significant number of notifications, leading to slow response times and increased exposure.
• SolarWinds supply chain attack (2020): This SolarWinds attack involved sophisticated malware that evaded detection, resulting in a major supply-chain breach. Security teams received alerts about unusual activity but dismissed them as false positives, allowing the attack to persist for months.
• Capital One data breach (2019): Capital One suffered a major data breach which affected over 100 million customers. Security alerts were triggered by unusual access patterns, but due to high alert volumes and a lack of effective prioritisation, the breach remained undetected for months.
• Equifax breach (2017): The Equifax breach exposed the personal information of 147 million people. Security teams received alerts about an unpatched vulnerability but failed to act in time due to alert overload and poor risk prioritisation.

Reducing alert fatigue

As the complexity of cyber threats increases, organisations must implement more effective strategies for managing the volume of security alerts. Threat intelligence offers a critical solution by enhancing alert contextualisation, prioritisation, and automation. By leveraging this strategy, security teams can focus on the most pressing threats, reduce false positives, and improve response times. The following strategies illustrate how threat intelligence can alleviate alert fatigue and bolster cybersecurity resilience:

1. Contextualisation and enrichment

Threat intelligence allows security teams to differentiate between genuine threats and false positives. By enriching alerts with data such as IP reputation scores, historical attack context, and associations with specific threat actors or attack campaigns, threat intelligence can provide a clearer understanding of the threat landscape. This context allows analysts to focus on high-risk incidents rather than spending time on low-priority alerts.

2. Prioritisation and risk scoring

Through threat intelligence, organisations can rank alerts based on their severity, likelihood, and potential impact. Risk-based prioritisation ensures that high-risk alerts can be addressed immediately, whilst less critical issues are deferred. Additionally, threat attribution, which links alerts to specific threat actors, helps analysts understand the motivations behind an attack, further refining prioritisation efforts.

3. Automation and correlation

Integrating threat intelligence with Security Information and Event Management (SIEM), Security Orchestration, Automation, and Response (SOAR) systems, and Endpoint Detection and Response (EDR) solutions facilitates automated alert suppression. This reduces duplicate or low-priority alerts. Cross-platform correlation enhances visibility by connecting alerts from different security tools, while AI-driven triage uses machine learning to more accurately flag true positives. As such, human error can be minimised and cognitive load can be alleviated.

Future trends in threat intelligence and alert management

The future of alert management will be increasingly shaped by the application of artificial intelligence (AI) and machine learning (ML) to dynamically filter and prioritise alerts. Moving beyond signature-based detection, behavioural analytics will allow organisations to identify anomalies which signal potential threats. Additionally, context-aware security orchestration, which automates threat response based on real-time intelligence, will streamline incident management and reduce response times.

AI-driven threat intelligence will not only help minimise false positives but will also improve alert prioritisation and automate threat response, thus enhancing operational efficiency.

To effectively combat alert fatigue, organisations must invest in high-quality threat intelligence feeds, whether they be open-source like OSINT, commercial, or industry-specific. Integrating this into existing security tools and continuously fine-tuning alert thresholds will significantly reduce the impact of irrelevant alerts without compromising security. Alert fatigue can lead to compromises in cybersecurity defences. As such, organisations should begin by evaluating current security infrastructures and incorporating threat intelligence into SOC workflows as a key component of cybersecurity strategies. Discover how adopting a threat intelligence-driven approach to alert management helps security teams regain control of their operations, respond more swiftly, and mitigate the risk of costly breaches here.