Attackers are moving faster than ever with AI and automation—achieving lateral movement in under 20 minutes on average. Meanwhile, security teams are averaging 3 hours just to detect a threat. When seconds matter, traditional detection methods leave businesses dangerously exposed.
To keep up, security operations need more than fragmented workflows and manual processes—they need a detection strategy designed to scale with their business and outpace attackers.
Why Traditional Detection Is Leaving You Exposed
Threat detection is critical to security operations, but it’s getting harder in the face of fast-moving threats and data that’s sprawled across hybrid infrastructures.
Typically, organizations write detection rules in individual technologies. This approach seems logical, but it also means rules operate independently, leaving defenses uncoordinated as businesses grow and tech stacks expand. As a result, security operations teams struggle to track threats as they move across the network, giving attackers the upper hand as they exfiltrate data, deploy malware, and cause damage.
Fragmented Detection Operations
Creates Several Critical Challenges:
Disrupted Detection Coverage
Swapping technologies means rules need to be migrated manually—a time-consuming process that can disrupt detection coverage and leave gaps in protection, making it impossible to scale quickly.
SIEM Delays
Relying on a SIEM for threat detection introduces latency from ingest and index processing, often delaying detection by an average of 3 hours. Misconfigurations can further hinder access to critical data, leaving you slow and blind to threats.
Slow and Manual Updates
Outdated rules need to be updated one at a time, piling extra work onto security operations teams that are already overstretched.
Specialized Expertise Requirements
Every tool requires dedicated expertise, making it harder to manage resources and adding unnecessary complexity to detection processes.
Delayed Deployment
Manual workflows across multiple technologies slow down rule implementation, leaving threats undetected for longer—a serious disadvantage against speedy attackers.
Uncoordinated Testing and Measurement
Without centralized control, testing and monitoring rule performance is inconsistent, which can lead to unreliable rules that miss critical alerts.
A Better Strategy: Detection for Every Threat, Everywhere
Tackle detection holistically by creating detections once in a centralized location and deploying them remotely wherever your data goes—whether in a SIEM, at the source, or in transit. This means you can stop threats earlier, before they ever reach storage, reducing dwell time and increasing efficiency. This method allows security teams to add and remove technology without compromising detection coverage in the process, so your detection scales with your business.
Get Faster by Detecting Without Limits
Bypass storage tools like SIEMs and data lakes by detecting where data lives –directly at the source technology or in transit to its end destination. By detecting closer to the source, you can cut delays and speed up your mean time to detect (MTTD)—a crucial advantage when working against an 18-minute countdown. Skipping the SIEM layer also reduces data ingestion and storage costs, so your detection is both faster and more cost-effective.
Build a Detection Strategy That Adapts
Centralization is just the first step. A truly effective solution requires a structured and adaptive detection strategy that is designed to continuously outpace attackers. This strategy should incorporate:
Research and Development: Identify potential threats using threat intelligence, MITRE ATT&CK, historical data, etc., and develop detections tailored to your environment.
Pre- and Post-Deployment Testing: Ensure rules are accurate and effective by carrying out syntax validation, data visibility verification, attack simulations, and operational validation before and after deploying rules.
Continuous Measurement: Measure rule performance and analytics continuously, tracking false-positive and -negatives rates, accuracy, response times, and testing results. Together, these processes ensure precise rule performance and continuous improvement to reliably defend against advancing threats, ultimately driving down your MTTD.
Why Security Providers Are Solving the Wrong Problems
Many security providers claim to solve the challenges with detection, but they’re still relying on the outdated detection methodologies that cause those challenges in the first place. Their solutions typically fall into at least one of two categories:
1. Taking control of your data to handle detection building, deployment, and management for you.
2. Offering tools that detect threats within a single technology, such as endpoints, network traffic, firewalls, or cloud environments
These approaches, while well-intentioned, don’t address the root problems and create even more challenges:
Lack of Transparency: Many providers use a black-box approach, keeping you in the dark about how your detections work and how well they’re performing.
Costly Data Centralization: Sending all your data to a provider is time consuming and expensive, and it becomes even more costly as data ingest grows.
Siloed Rules: The provided detection technologies often don’t talk to each other, so the rules built and managed by providers are still uncoordinated across technologies, slowing response times.
Neglected Rule Management: Providers rarely monitor, test, or share the performance of their rules, leaving you uncertain about their reliability.
To outpace threats and gain confidence in your detection strategy, your organization needs a fundamentally different approach. ReliaQuest built its GreyMatter agentic AI security operations platform with this approach in mind.
Rethink Detection with ReliaQuest GreyMatter
As the first line of defense, your security team has to detect threats with precision, confidence, and the agility to adapt to the challenges of today and tomorrow. With the ReliaQuest GreyMatter agentic AI security operations platform, you can achieve detection excellence while minimizing complexity.
Manage all detection logic directly within GreyMatter and deploy it effortlessly across all your tools—either through a storage layer, directly at the source, or while data is in motion. This streamlines deployment, reduces threat dwell time, and ensures faster detection. Ensure peak performance with transparent, continuous, and automated validation. Built on the industry-leading detection engineering lifecycle, GreyMatter helps your security operations team stay ahead of threats.