From Noise to Knowledge: Making Threat Intelligence Actually Work
Cybersecurity teams today live in a paradox. They’ve invested in firewalls, intrusion detection, endpoint security, SIEM platforms, and entire Security Operations Centers—yet breaches continue to rise across every industry. The reality is stark: while defenses have multiplied, adversaries have outpaced them. The missing ingredient isn’t more tools—it’s smarter, more actionable threat intelligence.
This dives into why traditional approaches fall short, what’s broken in the way organizations use intelligence, and how to measure and apply intelligence so it actually prevents breaches.
The Current Problem: Strong Defenses, Weak Outcomes
Organizations pride themselves on “layered defense.” Firewalls block traffic, intrusion detection systems flag suspicious activity, antivirus tools catch malware, and endpoint agents try to remediate infections. On top of that, SIEMs and SOCs aggregate alerts and coordinate response.
So why do we still see headlines about billion-dollar breaches?
Because most of these tools are reactive. They detect, log, and investigate after an attacker is already inside. By then, damage is measured in hours of downtime, lost data, or millions in regulatory fines.
Defenders aren’t failing because they’re under-resourced. They’re failing because their defenses lack foresight.
The Intelligence Gap: The Missing Layer
Threat intelligence is supposed to close that gap—yet adoption remains alarmingly low. Only 20% of organizations use any form of threat intelligence. That leaves the majority flying blind against adversaries who move faster and share better than defenders do.
Consider two uncomfortable truths:
- 99% of exploited vulnerabilities were already known to security professionals for at least a year.
- Over 90% of successful breaches stem from already-known locations, not novel “zero-day” exploits.
In other words, defenders are being beaten not by unknowns, but by knowns that weren’t operationalized and actionably applied.
The Intelligence Challenge: Too Little vs. Too Much
Even when organizations do use intelligence, they often face a double-edged sword.
- Too Little Intelligence creates blind spots. Gaps in coverage mean adversaries slip through unnoticed. Analysts miss early warning signs, leading to false negatives.
- Too Much Intelligence creates a different problem: noise. SOCs drown in redundant alerts and low-value data. Analysts chase false positives, leading to fatigue and wasted resources. This is the “paradox of plenty”—having more information but less clarity.
The challenge isn’t access to data. It’s transforming raw intelligence into balanced, prioritized, and actionable signals.
A Framework for Measuring Intelligence Quality
Not all intelligence is created equal. To understand quality, we can measure it across three dimensions:
1. Intelligence Breadth (Coverage)
- Coverage: How wide is the net? Are you seeing threats across geographies, industries, and attack surfaces?
- Pioneering: What percentage of intelligence is first discovered (non-redundant, unique)?
- Entropy: Is intelligence evenly distributed, or do providers cluster around the same small slice of threats?
Example: If one provider reports thousands of phishing domains but none on ransomware infrastructure, you’ve got breadth gaps.
2. Intelligence Depth (Understanding)
- Overlap: How many signals are validated by multiple providers? Redundancy here builds trust.
- Temporal Persistence: How long does intelligence remain relevant before it decays?
- Context & Relationships: Are threats enriched with links between IPs, domains, hashes, and campaigns?
Key insight: Research shows that only 4% of intelligence overlaps within one day, and 7% within 128 days. This suggests intelligence “lifetimes” are short—and keeping it current is critical.
3. Actionability Matrix
By plotting breadth and depth, we can categorize intelligence into four types:
| Type | Breadth | Depth | Result |
|---|---|---|---|
| Optimal | High | High | Actionable intelligence, ready to enforce |
| Tunnel Vision | Low | High | Deep context but narrow scope |
| Noisy | High | Low | Many signals, but low quality/context |
| Weak | Low | Low | Poor coverage and low reliability |
The lesson: actionable intelligence isn’t about having the most—it’s about having the right mix of breadth and depth
Real-World Impact: Case Example
The risks of inadequate intelligence are not abstract. Consider CVE-2025-24893, a critical XWiki vulnerability.
At publication:
- 40% of related Indicators of Compromise (IoCs) were already known to providers.
- Organizations without sufficient breadth and depth had 30% less coverage of the relevant IoCs.
This meant attackers exploiting the vulnerability had a wide open path into underprepared organizations—even though much of the necessary intelligence was already available.
The Path Forward: From More Tools to Smarter Intelligence
The future of cybersecurity doesn’t hinge on layering yet another tool into the stack. Instead, it requires a shift in mindset: from reactive defense to proactive prevention powered by intelligence.
Key elements of that future include:
Scalability
The ability to process and curate billions of IoCs without overwhelming analysts.
Quality
Continuous measurement of breadth and depth to filter noise and surface real threats.
Integration
Intelligence that directly fuels firewalls, EDR, SIEMs, and SOC workflows—turning static defenses into adaptive ones.
Feedback Loops
Intelligence that updates dynamically based on what’s working and what’s missed.
Trust
Reliance on validated, unbiased sources to avoid false confidence or skewed coverage
Cybersecurity has reached a turning point. Every breach proves the same truth: firewalls, EDR, SIEMs, and layered defenses alone cannot keep pace with adversaries who adapt in seconds. What separates successful defenders isn’t the number of tools they stack, but the quality of intelligence fueling those defenses.
Centripetal believes the future belongs to intelligence-driven defense—one where trusted, validated intelligence is operationalized in real time, at internet speed, and at a scale no human team could achieve alone. But scale alone isn’t enough. The real advantage comes when human ingenuity, strategic judgment, and contextual awareness are combined with artificial intelligence and vast streams of threat intelligence. Together, they create a defense model that is both unrelenting in speed and discerning in precision—turning overwhelming data into proactive protection.
This means:
- Stopping threats before they reach the network, not after the alert.
- Transforming billions of global indicators into actionable enforcement, continuously updated
- Relieving security teams from chasing noise so they can focus on what truly matters.
The end of reactive security promises is here. The organizations that embrace intelligence as the engine of their defense will be the ones that shift from surviving breaches to preventing them altogether.