The modern enterprise security operations center (SOC) is under siege. Not by a direct cyberattack, but by an unrelenting deluge of security alerts, many of which prove to be false alarms. Industry studies paint a stark picture: a typical SOC can be inundated with upwards of 3,000 security alerts daily. This overwhelming volume, coupled with a high rate of false positives, is creating a critical bottleneck, leading to alert fatigue among security analysts and potentially masking genuine threats.
A recent study by Vectra AI highlighted the growing challenge of cyber resilience in the age of artificial intelligence, with enterprises struggling to keep pace with sophisticated threats. Compounding this issue, a survey conducted by the SANS Institute revealed that a staggering 73% of these incoming alerts are false positives. This means that for every four alerts a SOC analyst receives, three are benign, requiring valuable time and resources to investigate and dismiss. This constant "cat-and-mouse battle" with non-existent threats comes with a significant financial burden, with U.S. costs estimated at $3.3 billion annually for the manual triage of these alerts.
The core problem lies in the sheer difficulty of discerning genuine threats from the background noise. For SOC team members, the most challenging aspect of their daily fight is directing their attention to the valid alerts amidst the cacophony of false positives. This relentless exposure can lead to desensitization, a phenomenon where analysts, constantly chasing phantom threats, may overlook or downplay actual malicious activity.
In an effort to dampen this overwhelming noise, alert tuning—the process of refining alert rules to reduce false positives—has become a major requirement and a significant challenge for SOC teams. However, this practice, while seemingly necessary, carries its own set of unexpected and often detrimental consequences. Every tuning decision is, in essence, a gamble: the signal being dampened might be the very one an attacker will exploit next. This delicate balancing act plays out daily in SOCs, a "maddening ballet" of risk management.
Mika Ayenson, threat research and detection engineering team lead at Elastic, articulated this persistent struggle in an interview with The New Stack. "These are the things that SOC analysts struggle with on a daily basis," Ayenson stated. "People think that you can keep tossing more tools and more rules at this problem, but fundamentally, the questions here get to what the engineers must do to address the root causes."
The Hidden Costs of Aggressive Alert Tuning
The pressure to manage hundreds or thousands of incoming alerts daily often leads SOC analysts to resort to aggressive tuning and the implementation of numerous rule exceptions. This is a direct consequence of operational demands and the very real impact of fatigue. "Fatigue is a real thing," Ayenson explained. "And for them, alert suppression traditionally may feel like it’s the only way to stay functional. It solves that queue management piece of the pie, but it does not necessarily address the risk management piece."
While adding new alert exceptions and raising thresholds can reduce the immediate alert volume, it often comes at the cost of security. These actions represent a trade-off, where operational efficiency is prioritized over comprehensive risk management. This can lead to security gaps that go unnoticed, effectively creating blind spots within the organization’s defense posture.
The fundamental issue with aggressive tuning is that it directly impacts an organization’s visibility into potential threats. Every adjustment, every reduction in an alert threshold, presents an opportunity to lose sight of incoming threats. "You’re wagering your bets that a weak threat signal you’re tuning out no longer matters," Ayenson warned. "And along the way, you might create these coverage gaps that you don’t know exist."
This loss of visibility can desensitize analysts to subtle threats, particularly those operating in low-signal environments where they can remain hidden and thrive. The most insidious danger is not the alerts that are seen, but the ones that have been deliberately tuned away. As Ayenson put it, "The biggest risk is not the alerts you see. It’s really the one that you tuned away."
Less mature security teams, in particular, often fall into the trap of optimizing for what is immediately visible in the alerts, rather than for what could be missed. This can be particularly problematic in the context of sophisticated attackers who employ subtle tactics designed to appear benign. For instance, attackers might mask sensitive file access within normal activity generated by legitimate AI tools like Generative AI capabilities such as Claude, Cursor, Copilot, or Codex. These seemingly innocuous actions can be easily overlooked if the alert rules have been aggressively tuned to ignore low-level anomalies. Such incidents are often only uncovered when an insightful security analyst can connect these seemingly small anomalies to form a larger pattern of malicious intent.
Attackers are continuously evolving their methods, striving to operate without triggering any alerts. With the advent of AI, their speed and sophistication have increased dramatically. In some of the most recent supply chain attacks, the focus has shifted from stealth to a more brazen approach. Attackers are making their presence known, confident in their ability to execute their objectives and disappear before defenses can effectively respond, often employing loud and noisy tactics because they can.
The Pitfalls of Creating Blind Spots
The act of tuning alerts, while intended to streamline operations, can inadvertently create significant security blind spots. This occurs when rules are modified or suppressed without a thorough understanding of the potential ramifications. Mika Ayenson emphasizes that tuning decisions must be measurable, contextual, and reversible. "The tuning steps must also be reversible in case they are found to be wrong," he added. "We must do all these things to ensure that we’re reducing that fatigue without also creating blind spots along the way."
This means moving beyond simply suppressing alerts. Every tuning decision needs to be evaluated from both a performance and efficacy standpoint, with a deep understanding of the specific threats it relates to. When rules are adjusted to exclude certain types of activity, the risk is that these adjustments inadvertently create gaps in coverage, leaving the organization vulnerable to attacks that exploit those specific, now-unmonitored, behaviors.
Consider a scenario where an organization tunes out alerts related to unusual file access patterns because they have historically generated too many false positives. If an attacker then uses a novel method to exfiltrate sensitive data that mimics legitimate user activity but deviates slightly from the newly tuned-out baseline, the SOC might miss it entirely. The analyst, desensitized by previous false alarms, might not flag the subtle indicators that a more comprehensive rule set would have captured.
This is particularly concerning when dealing with "quiet threats"—malicious activities that are designed to be subtle and operate below the radar of standard detection mechanisms. These threats often thrive in environments where alert fatigue has led to a general lowering of vigilance.
Towards a More Strategic Approach to Alert Management
Given the inherent risks associated with aggressive alert tuning, a more strategic and nuanced approach is required. Instead of viewing tuning solely as a means of noise reduction, organizations must reframe it as a critical risk management exercise. Ayenson suggests that tunings are not just about reducing noise; they can also be about increasing coverage and efficacy. This requires a delicate balance.
"Sometimes tunings are about increasing coverage and efficacy, and you have to do that in a way that isn’t risky to the point where you’ve expanded the scope of a rule, and now it’s being flooded," Ayenson explained. "The problem is that as you increase the scope of a rule, it might also increase the risk of false positives. So, you have to weigh the change, collect that data, perhaps make another subsequent tune, roll it back altogether, and make a more tactical change."
This tactical approach, exemplified by Elastic’s methodology, focuses on establishing critical behavioral baselines to detect threats. Rather than suppressing weak signals, the emphasis shifts to understanding and correlating them. "We try to fundamentally replace alert suppression with better understanding, focusing on correlation and connecting all those weak signals, instead of just removing them," Ayenson stated. "It’s about keeping the right signals in the detection process."
This involves observing unusual behaviors across various systems and then bringing them together for deeper analysis. For instance, identifying a user credential being accessed from an unfamiliar cloud endpoint at an unusual hour, especially if it’s a behavior never before exhibited by that user for that specific resource, can be a critical indicator. By correlating multi-domain analytics, security teams can piece together these seemingly isolated events to uncover sophisticated attacks.
Reducing Alert Fatigue Without Sacrificing Visibility
In an era of increasingly sophisticated and AI-driven cyberattacks, SOC teams must shift their perspective on alert tuning. It needs to be viewed as a strategic risk decision, not merely a tactical maneuver to combat alert fatigue. The ultimate goal is not to generate fewer alerts, but to achieve "fewer regrets."
"The goal isn’t creating more alerts," Ayenson emphasized. "It’s having fewer regrets. You want to reduce fatigue without reducing visibility. You want higher confidence alerts. You want to preserve coverage across different attack stages. You want to talk with analysts to know when they see alerts that they’re actually looking at an impending attack and real threat, not just noise."
To achieve this, security analysts must proactively question which areas of coverage are being weakened before they suppress alerts. This requires thorough documentation, regular review, and rigorous testing of any changes made, ideally against past attack simulations or actual incidents. This ensures that the impact of tuning is understood and that potential vulnerabilities are not inadvertently introduced.
The synergy between human intuition and AI capabilities is crucial in this endeavor. "Humans have the instincts and the right mindset to question if things look normal, while AI can look at volumes of data across time," Ayenson noted. "That human insight can be used to second-guess and question and come up with a hypothesis that can then be validated and tested empirically to analyze if the threat signals are valid or not. That’s the name of the game, finding the right signals and using them to corroborate a bigger attack chain."
Achieving Precision and Success in Security Alert Tuning
Effectively addressing the complex challenges of alert tuning, especially in the face of increasingly stealthy criminal attacks, requires technology that enhances precision without introducing new blind spots. Elastic Security is positioned as a critical tool for SOC teams, focusing on the alerts, rules, and automated threat protection capabilities that are central to their enterprise security responsibilities.
At the core of Elastic Security lies Elastic Workflows, a solution designed to automate the entire alert lifecycle, from triage and enrichment to response, without the need for a separate Security Orchestration, Automation, and Response (SOAR) platform. When investigations require human judgment beyond scripted steps, AI agents are integrated to analyze complex scenarios, providing teams with both reliable execution and intelligent analysis within a unified platform.
"We’re writing rules based on the actual behaviors that are happening below the surface," Ayenson explained. "With the new agents and workflows, people can take the expertise of their teams and codify them into workflows using and backed by AI agents. It’s not enough just to maintain rules and create more rules. You must understand the threat piece as well so you’re not creating a bunch of weak protections. You must do both things together."
Ultimately, alert tuning must be approached as a comprehensive risk management exercise. For organizations aiming to bolster their cybersecurity posture in the age of AI, Elastic’s expertise in enterprise security, search, and observability offers the crucial components needed to strengthen their defenses against evolving threats. The future of effective alert management lies not in simply reducing the volume of noise, but in intelligently identifying and amplifying the signals that truly matter, ensuring that genuine threats are detected and addressed before they can inflict significant damage.
