In cybersecurity, it’s critical to understand your risk. This requires a clear understanding of your attack surface and vulnerabilities.
But an attack surface is not static—it grows and shrinks as new endpoints come online, legacy tools are offloaded, and attackers shift their strategies. At the same time, the threat landscape is evolving rapidly. According to CVE.org, hundreds of exploited vulnerabilities are recorded every day—over 40,000 in 2024 alone, a 38% increase from 2023.
To stay ahead, security teams need a new approach: continuous, automated validation.
Why You Can’t Rely on Prioritization Alone
Prioritizing vulnerabilities is a foundational step in managing exposure. But without validation, it falls short. Why? Because prioritization alone doesn’t reveal whether a vulnerability is truly exploitable or whether your defenses can stop an attack.
Consider this: CISOs and SecOps teams are inundated with a flood of exposures, often defaulting to the “loudest” CVEs—like those receiving the most press coverage. Yet these loud vulnerabilities might not even apply to their environment, while lesser-known threats that do pose a risk could go undetected.
Without real-world validation, teams waste valuable time addressing low-risk vulnerabilities, leaving critical gaps exposed.
The Need for Continuous, Automated Validation
Timing is critical when assessing exposures. Point-in-time assessments may give you a snapshot of your security posture, but threats evolve too quickly for periodic testing to keep up.
It’s like knowing a burglar is nearby but being unaware of an unlocked window. Without regular checks, you’re at risk of a break-in. Continuous, automated validation, as part of a broader exposure management strategy, ensures you always know the state of your defenses, identifying issues before attackers can exploit them.
Unlike traditional vulnerability scanning or penetration testing, continuous validation operates on an ongoing basis, adapting to changes in your environment. This approach ensures your organization maintains a real-time understanding of its security posture. By filtering out irrelevant CVEs, validation enables teams to cut through the noise and address actionable high-impact threats.
The Three Layers of Effective Validation
Modern validation goes beyond simple vulnerability scanning or periodic penetration testing. It employs three interconnected layers—continuous, automated validation; integration and automation; and detection engineering—that collectively provide a comprehensive view of your security posture.
1. Continuous, Automated Validation
Test your security defenses under real-world conditions to ensure exposures are detected and addressed in real time. Leverage automated breach-and-attack simulations (BAS) to run scheduled tests that provide a consistent, up-to-date view of your security posture.
Through continuous validation, teams can ensure their defenses are effective, and remediation efforts are targeted and impactful. Validation provides a closed-loop system to stay ahead of modern threats.
2. Integration and Automation
For validation to be truly effective, it must be deeply integrated into your security operations. Modern platforms like ReliaQuest GreyMatter achieve this through APIs, enabling automated testing, reporting, and feedback loops across your entire security infrastructure.
This interconnectedness is what makes continuous validation possible. Take immediate action on breach and attack simulation results and remediate detection gaps in your attack surface directly within GreyMatter, eliminating tool pivots and wasted analyst time.
By automating these processes, GreyMatter enables teams to stay ahead of emerging threats while reducing the operational burden on analysts.
3. Detection Engineering
Detection engineering ensures detection rules identify real threats without excessive false positives. Modern detection rules often involve multiple data sources and complex logic, requiring regular testing to remain effective.
Detection validation continuously tests specific rules against both legitimate activities and malicious behaviors, such as ransomware activity or supply-chain attacks. For example, if you’ve written a detection rule for ransomware, validation will test it against simulated ransomware operations and legitimate file system activities, ensuring it effectively fires the detection without triggering unrelated, noisy false positives.
Measuring Success
Detection accuracy evaluates how well your rules perform in identifying true threats while minimizing false positives. This metric ensures that your security tools are not only detecting threats but are doing so efficiently and with minimal noise.
- False-Positive Rate: False-positive alerts are those that have been adjudicated as 100% non-malicious and require rule tuning. The calculation is a percentage of all customer false-positive alerts compared to all escalated alerts.
- Anomalous-Safe Rate: Anomalous-safe alerts are those where the activity has been adjudicated as safe, but the same activity can sometimes be malicious. The calculation is a percentage of all customer anomalous safe alerts compared to all escalated alerts.
By tracking these metrics, organizations can identify gaps, optimize defenses, and ensure continuous improvement, translating into faster detection, fewer false positives, and stronger overall security.
Conclusion
In a world where attackers constantly adapt, organizations must evolve faster. Validation transforms exposure management from reactive to proactive by focusing resources on the most critical risks, ensuring security controls are functioning as intended, and maintaining continuous awareness of your security posture.
But the real key is what you do with your validation findings. How are you mobilizing on those insights? With tools like GreyMatter, you can:
- Validate your detection rules with precision
- Close detection gaps instantly, without leaving your SecOps platform
- Eliminate risks before they become threats
