Swiss Cheese Security: How Detection Tuning Creates Vulnerabilities 

Security teams often work hard to build a robust organizational security perimeter. However, even with all security guardrails, the flood starts — false positives, fatigue and exceptions. Here’s what security teams often miss: Every time an exclusion is added to reduce false positives, it’s quietly drilling holes through that perimeter. What begins as a fortified defense slowly transforms into Swiss cheese — and when those holes eventually align, attackers gain a clear path straight through your defenses. 

This isn’t a failure of detection logic. It’s a fundamental flaw in how we approach organizational context. When teams build detection systems to be rigidly opinionated and deterministic, they encode assumptions about normal behavior into static rules. This unknowingly creates more exposure than protection.  This article will explore the dangerous tuning fallacy at the core of many security failures, and why dynamic context awareness is fundamentally resetting today’s security operations.  The Static Context Trap This problem isn’t unique to cybersecurity — it’s a pattern we see across every domain that relies on rule-based systems. Consider auto-scaling configurations designed to handle a temporary traffic spike but remain active months later, consuming unnecessary resources, or firewall rules created for a weekend maintenance window that become permanent fixtures, leaving behind persistent security gaps.  Cloud access policies written for a specific project team often outlive the project by years. The human brain simply isn’t designed to track every exception, remember every temporary rule or anticipate every future permutation that might require flexibility. Traditional security operations treat organizational knowledge like concrete data that can be permanently encoded into rules: Exclude alerts from the backup server Ignore after-hours access from the London office Suppress vulnerability scanner traffic from these IPs The problem, though, is that organizational context isn’t static — it’s a living, breathing entity that shifts constantly. Is that application suddenly business-critical because of a new product launch? Is Sarah actually traveling to Singapore this week, making her VPN connection legitimate? Is that port intentionally open for the new integration project? Has the backup server been compromised and is now being used for lateral movement? These contextual factors change daily, sometimes hourly. They’re exactly the information that security teams require to distinguish between genuine threats and benign business activity. Yet our detection systems remain blissfully unaware of these dynamics, lacking the dynamic context awareness needed to adapt to organizational reality. When Assumptions Become Vulnerabilities When we bake exceptions into our detection rules, we’re fossilizing assumptions about our environment. Six months later, that trusted backup server exclusion becomes the perfect blind spot for an attacker who’s compromised it. The London office travel exception remains active long after the employee has returned, creating a persistent gap in geographic anomaly detection. Consider this scenario: Your detection engineer creates an exclusion for John’s legitimate travel to the Tokyo office. Three months later, John’s credentials are compromised. An attacker in Tokyo now has a free pass because your system still remembers that John travels there, except John hasn’t been to Tokyo in months. Each tuning decision creates a small vulnerability. But vulnerabilities don’t exist in isolation; they compound. Attackers don’t need to find one perfect exploit; they need to chain together multiple small gaps in your detection coverage. The Advanced Threat Reality Many of the attacks today succeed not through single high-fidelity indicators, but by coordinating multiple low-level activities that individually might appear benign. When security teams tune out noisy signals to manage alert fatigue, they eliminate the very data points needed to detect advanced persistent threats and coordinated campaigns. Imagine an attacker who: Uses the compromised backup server (excluded from monitoring) Operates during London office hours (geographic exceptions active) Generates network traffic that mimics vulnerability scanning (suppressed alerts) Accesses systems using compromised credentials from a trusted location Of course, external attackers don’t start with a blueprint of your exceptions. But sophisticated threat actors invest months in reconnaissance, probing your defenses to map your blind spots. They send test traffic during different hours, from various geographic locations, using different techniques. They monitor your response patterns, noting what triggers alerts and what doesn’t. Over time, they reverse-engineer your tuning decisions simply by observing what you ignore. Your exceptions become their roadmap. Each action flies under the radar because of your tuning decisions. But together, they represent a sophisticated breach that your Swiss cheese security model can’t detect. The Dynamic Context Solution Instead of creating increasingly complex rule logic that attempts to predict every benign scenario, we need detection systems that can access live organizational intelligence: Current Travel Schedules: Is John actually supposed to be in Tokyo right now? Active Projects: Is that unusual port activity related to the new integration going live this week? Recent System Changes: Did IT just modify the backup server configuration? Did they open a relevant ticket?  Business Priorities: Is this application suddenly critical due to a product launch? Risk Tolerance Levels: Has the organization’s security posture shifted due to recent threats? This isn’t science fiction — it’s run-of-the-mill systems integration. Modern organizations already have this data scattered across dozens of platforms: HR systems track travel requests, project management tools monitor active initiatives, ITSM platforms log configuration changes and business intelligence dashboards reflect shifting priorities.  The challenge isn’t data availability, it’s creating API connections and integration frameworks that let your detection systems query this information in real-time. Instead of encoding static assumptions, your security tools can make dynamic API calls: Is employee X approved for travel to location Y between dates A and B? or Are there active change requests for system Z? This dynamic context awareness creates a living brain for security operations, one that understands the difference between John logging in from Tokyo when he’s on vacation versus when he’s supposed to be in the office. Preserving Signal, Not Noise With real-time organizational intelligence feeding your detection systems, the entire security engineering paradigm changes. No more debating whether to exclude the backup server or create time-based geographic exceptions. No more maintaining sprawling lists of environmental carve-outs that become technical debt. Detection engineers can return to what they do best: Identify the core patterns that separate malicious behavior from legitimate business activity, while allowing automated context queries to handle environmental noise. Think of it as the difference between a smoke detector that you’ve disabled because it goes off every time you cook, and one that knows when you’re cooking and adjusts its sensitivity accordingly. The first approach eliminates the nuisance but also eliminates protection. The second preserves security while reducing noise. Moving Beyond Swiss Cheese Your security detection system doesn’t have to look like Swiss cheese. By embracing dynamic context awareness instead of static rule exceptions, you can maintain comprehensive detection coverage while dramatically reducing false positives. The goal isn’t to create more sophisticated holes in your security blanket; it’s to weave a blanket that adapts to your organization’s changing needs without losing its protective power. In cybersecurity, the moment you stop seeing everything is the moment attackers start exploiting the gaps in your vision. Don’t let your quest for signal clarity create the very blind spots that sophisticated adversaries are looking for. 

About Author

AndyC

Andy Curtis is an award-winning security consultant, researcher and public speaker. He has been working in the computer security industry since the early 1990s, having been employed by state and federal government, leading healthcare and banking providers across three continents. He has given talks about computer security for some of the world’s largest companies, worked with law enforcement agencies on investigations into hacking groups, and is a regular voice on TV and radio explaining IT security threats.

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