Security teams are drowning in tools. According to research from Gartner, organizations use an average of 45 different cybersecurity tools. Each tool promises to solve a specific problem. Each vendor claims their solution is essential. Yet breaches keep happening, and when they do, security teams face a frustrating reality: they have more data than ever but less understanding of what actually occurred.
The fundamental problem isn’t that we lack security tools. The problem is that we’re approaching cybersecurity wrong.
The Illusion of Complete Coverage
Walk into any Security Operations Center (SOC) and you’ll see the same pattern. Endpoint protection here. Network monitoring there. SIEM (Security Information and Event Management) aggregating logs from dozens of sources. Cloud security tools watching virtual infrastructure. Identity management systems tracking access. Each tool operating in its own silo, with its own dashboard, its own alerts, and its own incomplete view of the environment.
Security teams convince themselves that if they just add one more tool, patch one more gap, integrate one more data source, they’ll finally achieve comprehensive coverage. But this approach creates a patchwork quilt of security, not a cohesive defense strategy.
The harsh truth? Attackers don’t operate in silos. They move laterally across your entire environment, exploiting the gaps between your tools, leveraging the blind spots that emerge when systems don’t communicate effectively.
When a sophisticated attacker compromises an endpoint, pivots to a cloud workload, exfiltrates data through a seemingly legitimate API call, and covers their tracks by manipulating logs across multiple systems, your collection of disconnected tools sees fragments of the story. None of them see the complete attack narrative.
The Context Crisis
Context matters more than raw data. Security teams already have too much data. What they desperately need is understanding.
Consider a typical security incident. Your endpoint detection tool flags suspicious PowerShell execution. Your network monitoring solution notices unusual outbound traffic. Your SIEM generates alerts about failed authentication attempts. Are these three separate incidents or one coordinated attack? Which happened first? How are they connected? What’s the actual blast radius?
Without holistic context spanning your entire environment, answering these questions requires manual correlation across multiple tools. A skilled analyst might piece together the attack timeline after hours of investigation. But by then, the attacker has likely achieved their objective and moved on.
The industry’s response to this problem has been more integration, more correlation rules, more automation that attempts to connect dots across disparate systems. Yet this approach still fundamentally treats security as a collection of parts rather than a unified whole.
What we actually need is a solution that understands your environment as a complete ecosystem from the start, not one that attempts to stitch together fragments after the fact.
The Forensics Time Trap
The pain becomes acute after a confirmed breach. This is when organizations need answers immediately. What did the attacker access? How did they get in? What data was compromised? How long were they present in the environment?
Current forensics solutions are incredibly expensive and painfully slow. According to the IBM Cost of a Data Breach Report 2024, organizations take an average of 194 days to identify a breach and 64 days to contain it. Even after detection, understanding what actually happened requires forensic specialists spending days or weeks manually analyzing logs, disk images, memory dumps, and network traffic.
These investigations consume enormous resources. Forensics teams pore over terabytes of data, manually reconstructing attack timelines, identifying affected systems, and determining the scope of compromise. The process is methodical but glacially slow.
Meanwhile, executives and board members demand immediate answers. Regulatory bodies require prompt notification. Customers need reassurance. The PR team needs talking points. Everyone is waiting for the forensics report that won’t be ready for weeks.
This delay isn’t just inconvenient. It’s dangerous. Without understanding what the attacker accessed, organizations can’t adequately protect affected customers, secure compromised systems, or prevent similar attacks. The forensics time gap represents a period of continued vulnerability.
What security teams desperately need is a solution that provides comprehensive incident reports automatically, showing the complete attack narrative across all environments without requiring weeks of manual investigation.
Why Signatures and Rules Keep Failing
For decades, cybersecurity has relied on signatures and rules. The model is simple: identify known bad things, create rules to detect them, and block anything that matches. This approach works reasonably well against known threats following predictable patterns.
The problem? Modern attackers don’t follow rules.
With ransomware attacks demonstrating an 81 percent year-over-year increase from 2023 to 2024, and cybercrime costs projected to reach $10.5 trillion in 2025, it’s clear that signature-based detection isn’t keeping pace with evolving threats.
Consider how attackers operate today. They use legitimate tools already present in your environment, a technique known as “living off the land.” They blend malicious activity with normal user behavior. They constantly evolve their tactics to bypass known detection patterns. By the time your security vendor updates their signature database with a new threat pattern, attackers have already moved on to something different.
Rules-based systems face a similar challenge. Every rule requires someone to anticipate a specific attack pattern and explicitly program detection logic. This reactive approach means you’re always defending against yesterday’s threats, not tomorrow’s.
The fundamental limitation of signatures and rules is that they require prior knowledge. They can only detect what someone has already seen and documented. Novel attacks, zero-day exploits, and creative variations on known techniques slip through undetected.
What Actually Works: Understanding Normal to Detect Abnormal
The future of effective cybersecurity lies in systems that understand what normal looks like across your entire environment and can identify deviations without relying on predefined rules or signatures.
This requires a fundamentally different approach built on deep learning and contextual understanding. Instead of asking “does this match a known bad pattern?” the question becomes “does this behavior make sense given everything else happening in the environment?”
Such systems need to continuously learn from your actual environment, adapting to your organization’s unique patterns and legitimate activities. They need to provide holistic context spanning endpoints, networks, cloud infrastructure, and identity systems. They need to automatically construct complete attack narratives showing how an incident unfolded across all these domains.
Most importantly, they need to work at machine speed, providing answers in minutes rather than weeks, enabling security teams to respond effectively while attacks are still unfolding rather than long after the damage is done.
Moving Forward
The cybersecurity industry needs to move beyond the tool accumulation mindset. Adding more point solutions won’t solve the fundamental problem of fragmented visibility and missing context.
Organizations need solutions that provide unified understanding across all environments, that learn continuously rather than relying on static rules, and that deliver actionable intelligence automatically rather than requiring weeks of manual forensics work.
The technology exists to make this shift. Deep learning models can understand complex patterns across massive datasets. Modern architectures can process security data at the scale and speed required. The question isn’t whether holistic, context-aware security is possible but whether organizations will recognize that their current patchwork approach fundamentally cannot protect against modern threats.
Your 45 security tools aren’t making you safer. They’re making you blind to the attacks that matter most. It’s time for something completely different.
