5 Key Data Protection Challenges and How to Overcome Them

Organizations understand their sensitive data is everywhere — and adversaries are after it. 

Data protection solutions have become an essential part of modern cybersecurity strategies. Organizations realize that in order to avoid a breach, they must have a plan to monitor and control data flow at the user level so they can better understand where data is going, who is accessing it and when malicious activity occurs. 

But when it comes to deployment and operationalization, things can get complicated. With so much data on the move, how can security teams ensure they don’t lose visibility into unsanctioned data egresses? And when deploying solutions, how can they implement a data protection strategy that minimizes effort and maximizes results?

In this blog, we explore five common data protection challenges organizations face. We also discuss how CrowdStrike Falcon® Data Protection enables CrowdStrike customers to define and automate their data protection policies and workflows — from detections to forensics — using their existing CrowdStrike Falcon® sensor.

Navigating Data Protection Challenges

Organizations have long relied on legacy data protection tools to secure their corporate data. But these deployments are rife with challenges. When we talk to organizations struggling with these traditional data protection tools, these are the most common challenges: 

1. Deployment complexity

In many organizations, the data protection strategy doesn’t extend to all corners of the business because legacy data protection tools are complicated to deploy and operationalize. These solutions also add more agents on the endpoint, many of which are resource hogs. Further, monitoring large volumes of data across numerous endpoints can slow down systems, as traditional data protection solutions aren’t designed to scale efficiently. As organizations grow or go through mergers and divestitures, it becomes difficult to scale data protection to cover all endpoints without introducing multiple agents or gaps in protection.

2. Management struggles

Organizations and analysts are overwhelmed and often struggle to manage complex data loss prevention (DLP) implementations. With traditional data protection tools, organizations often deal with broken scripts, middleware issues, complex rule management and frequent false positives — all requiring significant effort from the data security team. This becomes more complex during mergers, as handling siloed tools and a diverse mix of vendors and platforms demands more effort but gives little value in protecting sensitive data. 

3. Limited visibility

In modern organizations, characterized by SaaS applications, cloud storage and hybrid infrastructures, traditional data protection solutions often fall short. These conventional tools typically focus on content inspection without considering the context of data usage — the who, what, why and where — creating visibility gaps in data movement. This oversight can lead to more false positives, causing alert fatigue among security teams. Moreover, employees may resort to shadow IT practices (using unapproved applications and processes) for data sharing, creating more blind spots and increasing the risk of data breaches.

4. Policy creation and management hurdles

Creating and managing data protection policies is often among the biggest hurdles. Organizations need to create granular policies to cover various data types, user roles and environments. As they grow, they face challenges in tailoring and updating policies to meet evolving business needs, while striking a balance between security and productivity. Overly restrictive policies may block legitimate actions, leading to frustration, potential workarounds by employees and false positives.

5. Too much data, too much noise

Excessive noise in traditional data protection solutions can overwhelm security teams, leading to alert fatigue and missed threats. Other consequences include wasted resources, higher operational costs and lower trust in the data security strategy. Excessive noise due to low-fidelity detections can disrupt business operations by blocking legitimate activities, slowing productivity and complicating policy management.

Alternatively, organizations may resort to using the tool in monitor-only mode to prevent business disruptions, making sensitive data vulnerable to accidental and malicious exposure. Over time, these issues can create security blind spots, increase compliance risks and lead to breaches.

How Falcon Data Protection Can Help

CrowdStrike Falcon® Data Protection was designed to directly address these challenges. It offers an intelligent, adaptive approach that leverages machine learning and behavioral analytics to distinguish between legitimate activities and real threats — significantly reducing the mean time to detect and respond. Other benefits include:

Effortless deployment and operationalization

As a module of the CrowdStrike Falcon® cybersecurity platform, Falcon Data Protection is easy to deploy as it’s baked into the unified sensor architecture. With continuous visibility from a single unified console and accurate detections, it ensures effective protection with little effort. 

Contextual visibility into data flows

Falcon Data Protection provides visibility into all data flows across the enterprise, monitoring data from origin to destination before sensitive data is classified or protection policies are configured. This early insight helps users understand data movement and develop effective protection strategies. 

For more granular control, users can define web sources like Microsoft Office 365, Google Workspace and Box at the account level. This enables them to distinguish between managed and unmanaged applications, offering clearer context for data flows. For example, users can easily identify files with personally identifiable information moving from a managed OneDrive to a personal OneDrive, reducing false positives and ensuring accurate policy enforcement.

Simple policy creation and enforcement

Falcon Data Protection simplifies creating, testing and enforcing rules for custom data classifications, ensuring effective detection and prevention of data egress. Its precedence-based rules offer flexibility, allowing you to either block by default — that is, lock down data with exceptions — or allow by default with specific block rules. 

One of Falcon Data Protection’s standout features is Similarity Detection. This ensures policies follow the data, regardless of how it may transform — such as renaming, modifications or partial copying into other files or destinations like generative AI tools. Falcon Data Protection removes the overhead and reliance on tagging and labeling to protect data and apply policies. 

To avoid business disruptions, Falcon Data Protection’s simulation mode lets users visualize and test policies before enforcement. This helps assess potential impacts, refine rules and reduce false positives. By analyzing “what if” scenarios, it can ensure policies are effective and don't impact user experience. Falcon Data Protection empowers teams to enforce precise, tested policies with confidence, balancing security and usability while safeguarding data.

Automate with accurate detections

With both machine-learning and user-generated detections available in Falcon Data Protection, analysts and data protection administrators can quickly identify true positives and automate response actions. Falcon Data Protection has user-behavioral analytics factored into ML-based anomaly detections, complementing the work of analysts and admins to uncover suspicious behavior that might otherwise fall through the cracks of user-created rules. 

Triage options

Once a detection has surfaced, analysts can respond directly within the Falcon platform. They can use automated responses with CrowdStrike Falcon® Fusion SOAR to quickly move hosts to a group with stricter rules in place to block data leakage. They can also send a Slack or Teams message to their team with the detection and queries attached to quickly triage. Or, with the new data forensics feature, they can investigate a copy of the quarantined file so if it's deleted by the exfiltrating user, there's still an original copy available.

Efficient investigation with evidence retrieval

Falcon Data Protection’s new data forensics feature enables teams to store data that is part of a suspected exfiltration event. The hash of the offending data is stored to confirm the integrity of the evidence is true to the time of egress for legal or HR purposes. Chain-of-custody records are maintained, and the data is available for auditing or further investigation. 

This also applies to data that’s been copied and pasted. For example, If a user copies source code to ChatGPT, analysts can see this action, block it and retrieve evidence of the attempted paste in order to educate users or further strengthen protections. 

Effective Data Protection from the Falcon Platform

From automatically detecting potential data egress risks to providing deep forensic insights, Falcon Data Protection empowers analysts and information security leaders with high-fidelity detections and response automation, without losing sight of data. It provides full visibility, intelligent analysis and rapid incident response at significantly lesser effort when compared to traditional data protection solutions. 

CrowdStrike’s platform approach further enhances its effectiveness. With options to automate responses using Falcon Fusion SOAR workflows, dig deeper into users and their risk scores and privileges with CrowdStrike Falcon® Identity Protection and ingest data into CrowdStrike Falcon® Next-Gen SIEM for faster investigations, deploying Falcon Data Protection as part of the Falcon platform gives organizations a consolidated approach to security.

Additional Resources

• See Falcon Data Protection in action in these short demo videos: Preventing GenAI Data Loss and Surfacing Anomalous Data Egress.
• Dive in and try out Falcon Data Protection in this self-paced interactive demo.