The Chief Information Security Officer (CISO) role has transformed from being purely technical to becoming a strategic business leader. Today's CISOs must balance defending against an ever-evolving threat landscape with demonstrating ROI and aligning security with organizational goals. The majority say the role has evolved so drastically since they first took the position—it feels like an entirely different job!
CISOs are emerging as strategists and leaders who have a louder voice in the boardroom. A growing number of them report directly to their CEO. This has led to the rise of the business-minded CISO, a person for whom budget efficiency and ROI are critical—more so than implementing a patchwork of bleeding-edge security tools.
That said, the CISO's most critical priorities still revolve around defending the organization against an increasingly complex threat landscape. Even with a newfound interest in boardroom reporting, they still must adapt to try and stay ahead of cyber attackers. Regardless of how well they perform this goal, however, they aren't getting much sleep at night. Too many of the tools being used to defend the organization have critical gaps in coverage, limiting the ability of security operations center (SOC) teams to effectively monitor critical systems for compromise.
So, although CISOs continue to invest in mitigating surging threat levels through targeted tools and investing in talent, they still struggle to maximize the value of the solutions they already have, such as managed detection and response (MDR), which hinders SOC performance and overall security posture.
Over the past year, we interviewed over 75 CISOs, CIO’s and CTO’s from across 25 different industries including banking, insurance, retail, media, and healthcare. This article explores the key challenges they encounter when implementing MDR and offers insights and actionable best practices to enhance your strategy.
Traditional MDR struggles with overwhelming alert volumes and increasing attack sophistication. Alerts often lack the context needed to distinguish real threats from noise, leading to analyst burnout and missed critical signals. Each alert has to be investigated and triaged to determine whether it's a real attack or an employee performing an action that skirts security guidelines.
“Attackers have moved beyond simple signatures. What's killing us is the lack of context when alerts pour in at 2 a.m.”
As one CISO said, “Attackers have moved beyond simple signatures. What's killing us is the lack of context when alerts pour in at 2 a.m.” The flow of data into the SOC is unlikely to abate, especially in light of the global rise in malware. Beyond analyst fatigue, the real threat lies in critical alerts being buried in noise, causing genuine threats to slip through undetected. The real issue? SOCs lack insight into what's happening across their environment.
Rather than decreasing alerts, our recommendation is to increase signals: and with signal analytics, add more context around the data analysts receive. Adding ‘situational awareness' with increased visibility by environment, diversity, attack surfaces, and business context provides a nuanced understanding of risk. It captures improvements from new data sources and analytics in scoring the board can understand—something that can prove immensely powerful for CISOs in their enhanced roles.
Data silos in security operations hinder threat detection and analysis because they limit visibility across the technology infrastructure. Unfortunately, every new security tool you implement to monitor creates its own silo, each with distinct formats and limited retention. Data lakes unify disparate data sources, preserving relationships and context to enable predictive analytics and automated responses. For example, an advanced data lake can identify anomalous user behavior across siloed applications, flagging potential insider threats before they escalate.
“Data lakes are not just storage solutions; they are foundational to automated response and predictive analytics…”
“Data lakes are not just storage solutions; they are foundational to automated response and predictive analytics, turning overwhelming logs into actionable insights," one CISO told us recently. A well-designed data lake that preserves relationships and context allows automated response and predictive analytics, enabling proactive MDR operations. This is incredibly valuable for security operations teams. Ultimately, it's not just about collecting more data. It's about connecting the dots—linking behaviors, understanding patterns, and acting on the most menacing risks effectively.
By enriching alerts with business context—such as asset criticality, user roles and likelihood of impact—SOC teams gain the clarity needed to prioritize mission-critical threats. For example, an alert targeting financial systems before payroll is far more urgent than generic malware on a low-priority server. This is the core of situational awareness in security operations, wherein the alert data received in MDR is enriched with the needed data, such as likelihood and impact, that ensures SOC teams can make better decisions.
“It's not just about spotting an intrusion; it's about knowing which ones are mission-critical and which ones are noise.”
One CISO commented, “We need systems that tell us: This isn't just malware—it's malware targeting your finance department right before payroll. That's actionable.”
Another told us, “It's not just about spotting an intrusion; it's about knowing which ones are mission-critical and which ones are noise. That's where we need clarity.”
Providing situational awareness starts with an engineering-first approach that dynamically adjusts to threats based on contextualized data. MDRs collect a lot of data every day, in volumes that are unlikely to abate any time soon. There’s so much data, in fact, that the problem is understanding how these pieces of information fit together. That’s how you achieve real situational awareness with a unified perspective. You continuously correlate data across your environment, show why these events matter, and how they could escalate.
Traditional MDR is limited in threat prioritization as well as response times. The reason for this is a lack of contextualized intelligence – something that makes it incredibly hard to judge which potential threats need to be resolved and which ones might be lower priority or even irrelevant. This lack of insight into which threats really need to be targeted also makes response times far longer than they should be.
“We had MDR in place, yet we missed lateral movement in our network. That's unacceptable in today's stakes.”
As one CISO said, “We had MDR in place, yet we missed lateral movement in our network. That's unacceptable in today's stakes.” Another noted that “The attacker exploited a vulnerability that was flagged months ago. We assumed the patch was applied, but it never reached production. Traditional systems didn't verify.”
It’s a well-known fact that not all threats are created equal. MDR needs to be able to determine quickly that a threat is or isn’t going to move laterally and cause more damage. The way to truly do this is through unified data that has the necessary context included. MDR needs to include contextualized data – whether signal or noise – to be truly effective. Data provided in context makes it easier for SOC teams to decide where they need to act.
AI-driven systems can process millions of data points in real time, correlating signals to detect sophisticated, coordinated attacks. For example, by mapping anomalies across user behavior, network activity, and file access, AI can flag advanced persistent threats (APTs) with high accuracy. Organizations that leverage these tools can add context to the noisy data they receive, scaling up their operations quickly and offering needed insight to SOC teams.
“When AI enriches alerts with context, it's a game changer.”
“When AI enriches alerts with context, it's a game changer. It's not about fewer alerts; it's about meaningful ones,” one CISO told us. Adaptive systems that leverage AI tooling to analyze data at scale ultimately help organizations become more resilient. Context at the level AI can provide, especially with automatically flagging data and adding business intelligence, can more readily inform SOC teams and ensure better outcomes.
CISOs need to adapt their use of MDR to ensure that it's relevant to their business context. MDR is a hugely valuable component of security operations, expanding the capabilities of internal teams that have limited resources. Unfortunately, traditional MDR faces the challenge of a signal-to-noise ratio that reduces its effectiveness.
To truly be effective, MDR needs to access contextualized data with enhanced visibility into the entire environment. Adding this context informs decision-making, which is vital when SOC teams need to make fast decisions about defending the organization.
Moreover, this should be tied to business goals to ensure that SOC teams defend the most critical infrastructure from attack. As one CISO said, “If you're not aligning MDR with your business's risk profile, you're fighting blind.”
AI is also vital. As one CISO commented, “Autonomous systems, enriched with situational awareness and contextual intelligence, offer the proactive approach we need. They adapt dynamically, evolving as threats emerge and change.”
In other words, CISOs should prioritize MDR solutions that deliver the following:
The challenges of modern threats, alert fatigue, and gaps in traditional MDR call for a forward-looking, adaptive solution. MDR must evolve to incorporate situational awareness, be data-driven, and adapt dynamically to shifting threat landscapes. Moreover, it also needs to focus on providing insight to SOC teams to ensure that they have the intelligence they need when they need it.
“The future of MDR isn't static—it's about adaptability.”
A CISO recently told us that “The future of MDR isn't static—it's about adaptability. Every threat brings new variables, and we need systems that learn and adjust in real-time.”
From a solution perspective, this means adaptive MDR powered by AI and contextual intelligence. This type of solution is designed to offer detection and actionable insights and align security with business outcomes. The end result is a more robust and resilient enterprise that's protected from advanced threats.
To find out more, explore Netenrich's adaptive MDR solutions, which prioritize situational awareness and actionable intelligence.