Navigating the Journey from EDR to XDR: A Strategic Transition Plan

I’m often asked by CISOs and security teams for advice on evolving their defenses to meet modern threats. One key strategic move many are considering today is transitioning from traditional endpoint detection and response (EDR) to the more advanced extended detection and response (XDR).

Making this move can strengthen security visibility, detection, and response across the organization. However, it requires thoughtful planning and execution to maximize benefits and minimize disruption. In this post, I’ll share my view for guiding teams through a successful migration from EDR to XDR.

The Case for XDR

Before we dive into the transition plan, it’s important to review the rationale for XDR. Why consider moving from your current EDR implementation?

While EDR served organizations well in the past, it has notable blindspots:

• EDR is siloed, providing visibility at the endpoint layer only. It lacks context about threats affecting other parts of the environment.
• EDR relies on static, rules-based detection. This leaves gaps against new and advanced threats that don’t match known IOCs or behaviors.
• EDR focuses on detecting discrete threats on individual endpoints. But modern attacks chain across endpoints, networks, clouds, email, and more.
• EDR generates high volumes of low-fidelity alerts. This can overwhelm security analysts and cause threats to be missed.

XDR aims to solve these problems by unifying visibility, detection, and response across endpoints, networks, clouds, identities, and other data sources.

Benefits of XDR include:

• Broader visibility and detection: Correlating telemetry reveals threats that siloed EDR misses.
• Faster investigation: XDR provides a single pane of glass for analyzing threats across domains.
• Improved analytics: XDR uses advanced techniques like behavioral analytics, machine learning, and automation to detect sophisticated attacks.
• Higher efficiency: Consolidating tools onto a unified XDR platform reduces overhead for analysts and ops.
• Proactive hunting: XDR allows hunting across the entire infrastructure to uncover hidden threats.

For these reasons, XDR represents an evolution in security capabilities that organizations should proactively consider.

Creating an Effective Transition Plan

However, moving from EDR to XDR isn’t as simple as just “turning on” a new solution. A rushed or ad hoc transition risks disruption, gaps, and reduced visibility into threats.

That’s why I advise clients to take a phased, step-by-step approach:

1. Build the business case and get executive buy-in. Make XDR a strategic priority with budget and resources assigned. Brief leadership on costs, benefits, and risks.
2. Assess readiness. Inventory your EDR deployment - agents, integrations, policies, and use cases. Identify training and skill gaps. Define success criteria and KPIs.
3. Architect the solution. Determine priority use cases and data sources for XDR. Create an expansion roadmap balancing risk and resources.
4. Select a unified XDR platform. Assess top vendors based on detection, data integration, ease of use, and deployment options.
5. Deploy XDR incrementally. First, forward deploy XDR alongside EDR for parallel visibility. Next, shift use cases to XDR analytics and workflows. Finally, retire EDR once XDR coverage is confirmed.
6. Leverage a SOC platform. Automate manual tasks, streamline workflows, and provide playbooks to increase the value of XDR.
7. Refine through continuous improvement. Fine-tune over time, expand data sources, provide ongoing training, and monitor against KPIs. View XDR as an evolving platform.

This phased approach balances the need to drive progress while managing risk. It prevents a “rip and replace” approach that loses institutional knowledge and creates gaps. The focus is on smoothly evolving capabilities over time.

Now let’s examine each step of this methodology in more detail:

Building the Business Case

The first step is building an internal business case for XDR and getting executive buy-in. This involves several elements:

• Documenting the limitations of current EDR approaches - silos, gaps in detection, alerts overload, etc.
• Researching how XDR capabilities evolve security - emphasize how it addresses those EDR limitations.
• Making the case in business terms - reduced breach risk, improved resilience, higher operational efficiency. Use data from public breaches and industry reports.
• Estimating budget needs for licensing, deployment services, and internal personnel costs. Factor in potential cost savings by consolidating tools.
• Benchmarking against peers – cite examples of other organizations migrating to XDR.
• Outlining an implementation roadmap showing phased rollout.
• Describing risks and mitigation plans – especially around maintaining detection coverage during the transition.

The goal is framing XDR as a strategic investment that pays back over time by strengthening security and reducing overhead. Secure buy-in from leadership as an enterprise priority.

Assessing Readiness

With executive sponsorship, the next step is assessing organizational readiness. This lays the groundwork for a smooth transition by understanding the starting state:

• Take inventory of existing EDR implementation – agents, management consoles, data sources integrated, policies and configurations.
• Document current use cases applied to EDR – suspicious process execution, lateral movement, etc.
• Analyze detection rules, threat intel feeds, and other analytics applied to EDR data.
• Review ongoing tuning and maintenance of the EDR deployment.
• Catalog existing alert triage, investigation and response workflows.
• Identify any gaps or pain points in current EDR capabilities.
• Determine business requirements and priority use cases for XDR.
• Assess staff skills and identify training needed to operate XDR solutions.

This readiness assessment achieves two goals: 1) Creating a baseline to transition from 2) Identifying operational requirements to guide XDR planning.

Defining the XDR Architecture

With requirements established, next is architecting the future state XDR deployment:

• Based on priority use cases, determine which additional telemetry sources beyond endpoints will feed into XDR analytics. Network, cloud, identity, email and other data each expand visibility.
• For each data source, identify the collection and ingestion mechanisms needed. API connections to cloud platforms? Is traffic mirroring to analyze network data? Log aggregation from email systems?
• Design an expansion roadmap over time. Aim to minimize disruption by moving telemetry sources over to XDR in phases. Maintain legacy EDR integration during the transition.
• Construct analytic detection policies oriented around priority threats and asset protection. Reuse existing behavioral indicators where applicable, but take advantage of XDR’s expanded analytics.
• Plan integration with downstream processes like SOAR playbooks and ticket systems. XDR should augment and enhance, not disrupt, existing workflows.

A well-scoped architecture tailored to the organization’s needs smoothes the adoption of XDR capabilities. Balance a future-looking vision with pragmatic near-term implementation.

Choosing the Right XDR Vendor

With requirements established, the next key decision is selecting an XDR vendor. I advise clients to conduct an in-depth evaluation of solutions :

• Assess the detection efficacy of analytics and machine learning capabilities using real-world attack data sets. Avoid overreliance on vendor marketing claims.
• Review native integrations with data sources and IT infrastructure for coverage and implementation burden.
• Validate that the solution scales to the organization’s size without performance issues.
• Test investigation workflows to evaluate usability, visualization, and hunting features.
• Determine options for cloud, on-prem, or hybrid deployment of the XDR platform.
• Evaluate whether vendor professional services will be needed for deployment and configuration.
• Consider offerings for managed XDR if lacking internal expertise.
• Compare license costs and total cost of ownership between solutions.

Selecting the XDR platform that best aligns with organizational needs is critical. I advise narrowing the options and then performing proof-of-concept deployments of two or more final contenders to make the decision.

Incrementally Deploying XDR Capabilities

With the XDR platform selected, next is the implementation process itself. I strongly recommend taking an incremental approach:

• Begin by forward deploying the XDR agent alongside existing EDR agents on endpoints. Run XDR and EDR in parallel during the transition to maintain coverage.
• Gradually shift detection policies and use cases over from EDR to XDR analytics. Disable corresponding EDR analytics to reduce duplication.
• Over time, expand XDR agents and integrations to ingest new data sources like network and cloud. Adjust detection policies to leverage this expanded telemetry.
• Once efficacy is validated, start rolling back EDR capabilities for detection use cases now covered by XDR. Finally, remove EDR agents once satisfied.

This gradual phase-out prevents coverage gaps while building familiarity with XDR. Maintain legacy EDR integration just in case rollback is needed. Only retire after verifying XDR efficacy over time. A deliberate transition is lower risk.

Using a SOC Platform to support the transition

A SOC platform can accelerate and smooth the transition from EDR to XDR in several key ways:

Automation - SOC platforms allow security teams to automate manual tasks and enforce consistent workflows. This can free up staff to focus on higher-value activities around tuning and optimizing the new XDR deployment. Playbooks can automatically handle alert triage, initial investigation steps, and mitigation for common threats.

Orchestration - SOAR orchestration stitches together XDR tools, data sources, and processes into unified workflows. This streamlines collaboration across security, IT, and other groups. Complex multi-step response actions can be codified into playbooks and standardized.

Analytics - SOC platforms generate metrics on analyst activity, dwell times, false positives, and more. This visibility helps teams continuously fine-tune XDR analytics and workflows to maximize value. Analytics identify inefficiencies to address.

Knowledge management - Playbooks and automation capture tribal knowledge and best practices around XDR management, reducing dependence on individuals. This makes the team more resilient to staff turnover.

Scalability - By handling repetitive low-level tasks, SOC platforms boost analyst productivity and allow the XDR implementation to scale across the organization. Capacity doesn't have to solely rely on hiring more staff.

Visibility - Dashboards provide visibility into XDR operations' health, detection efficacy, and other metrics to optimize performance. Teams can visually track progress against KPIs.

In summary, SOC platforms reduce manual toil, enforce consistency, capture knowledge, and maximize productivity - all crucial when adopting new XDR capabilities and workflows. The integration pays off, especially during periods of transition.

Refine through continuous improvement

Here are some tips on refining and continuously improving an XDR implementation over time:

• Measure and track performance against KPIs. Key metrics may include time-to-detect threats, false positive rates, efficiency of investigation and response, and overall mean time to remediate (MTTR).
• Establish a feedback loop for analysts to identify pain points with workflows, detection gaps, etc. Foster an environment for sharing this input without blame.
• Use threat-hunting exercises to validate detection policies proactively. Hunting uncovers blindspots that may require analytics tuning.
• Review incidents post-response to identify lessons learned. Continuously improve playbooks.
• Expand sources of telemetry into the XDR platform incrementally over time to gain more signal. But phase this in gradually.
• As new data sources are added, evolve detection rules to leverage them. But avoid rules sprawl - focus on high-fidelity detections.
• Run XDR platform updates promptly to gain new capabilities in algorithms, visualizations, etc. But test rigorously first.
• Provide ongoing education and cross-training for analysts on XDR capabilities and workflows. Knowledge drives value.
• Regularly fine-tune configurations, custom detections, false positive suppression, and other optimizations. Expect this as ongoing work.
• Track tool usage trends to identify underutilized features to remove gaps to address through new use cases.
• Treat XDR not as a one-time project, but as an evolving platform. Continually refine it as threats and the business evolve.

The key is driving continuous improvement through data-driven feedback, analyst input, executive engagement, and an agile mindset. XDR requires ongoing supervision but pays dividends over time.

How to measure XDR efficiency?

• Mean time to detect (MTTD) - The average elapsed time between an intrusion and when it is detected by XDR.
• False positive rate - The percentage of alerts generated by XDR that turn out to be benign.
• True positive rate - The percentage of actual threats and incidents that XDR can detect.
• Mean time to respond (MTTR) - The average elapsed time between threat detection and successful containment/eradication.
• Incident volume - The number of security incidents handled over a period of time. Useful for measuring patterns over time.
• Containment rate - The percentage of detected incidents that were successfully contained before spreading. MTTI could be used.
• Case closure rate - The percentage of cases/incidents that were closed out through successful remediation in a period of time.
• Analyst productivity - Key metrics for individual analysts such as cases investigated per day/week. Useful to track training progress.
• Detection coverage - The percentage of the infrastructure/environment covered by XDR analytics and visibility.
• Platform uptime - The percentage of time the XDR platform is online and performing as expected..
• Threat hunting yield - The number of true threats uncovered through proactive threat hunts using XDR.

The right KPIs provide objective measures of XDR performance, effectiveness, and analyst productivity over time. This allows for making data-driven decisions on where to prioritize improvements.

The Journey Continues

Transitioning from EDR to XDR represents a significant strategic undertaking. But with proper planning, strong execution, and ongoing refinement, organizations can evolve their security programs to meet today's threats.

While the migration requires investment, the enhanced visibility, detection and efficiency of XDR ultimately helps security teams be more proactive against attacks. This pays long-term dividends in risk reduction and resilience.

Of course, each organization's needs and environment are unique. If you're considering an EDR to XDR transition, I encourage you to reach out. I'm always happy to offer guidance to CISOs and security leaders weighing their options. Feel free to connect with me here on LinkedIn to continue the discussion. You can also read this ebook.

Through collaboration and knowledge sharing across the industry, we can ensure security evolves in step with the ever-changing threat landscape. But we must be proactive - as cyber advisors, our clients depend on our leadership to navigate these transitions. The journey to XDR represents the next leg of that ongoing endeavor.