The Ultimate Guide to DLP Remediation for Data Threats

Businesses today are in constant fear of cyber threats. And with rising threats, governments are also strengthening compliance requirements. Founders and compliance offers are constantly striving to comply with regulatory requirements. The struggle to protect confidential data is real and pressing, from small startups to large enterprises.

The consequences of neglecting data security challenges are far-reaching. In 2023, the average cost of a data breach soared to USD 4.45 million worldwide. This report reflects a staggering 15% increase over the past three years.

This article provides actionable insights on DLP remediation to strengthen your organization’s data protection measures.

Understanding DLP incidents

A Data Loss Prevention (DLP) incident occurs when sensitive, confidential, or critical information is exposed to an unauthorized entity. This can include sending a confidential document to the wrong recipient or unauthorized access to sensitive data. 

Common causes of DLP incidents

DLP incidents are not limited to external threats, they often involve internal actions which lead to potential data breaches. Such incidents can arise from different sources including:

• Human error: Mistakes such as sending emails to incorrect recipients or misconfiguration databases are frequent culprits.
• Insider threats: Employees or contractors with access to sensitive information may misuse their privileges.
• External attacks: Hackers and cybercriminals employ sophisticated techniques like phishing, malware, or social engineering to breach defenses.
• Lack of awareness: A significant number of incidents occur because employees are not aware of the proper protocols for handling sensitive data.
• Inadequate security measures: Weak passwords, outdated software, and lack of encryption can make it easier for data breaches to occur.

The impact of DLP incidents on organizations

The consequences of DLP incidents can be far-reaching and devastating for organizations as below:

• Financial loss: From regulatory fines to litigation costs and DLP remediation expenses, the financial impact can be substantial.
• Reputation damage: A single incident can tarnish an organization's reputation which leads to lost trust among customers and partners.
• Operational disruption: Responding to a DLP incident often requires significant resources and time to divert attention from regular business activities. The average time to detect and contain a breach in 2023 was 277 days.
• Legal and regulatory consequences: Many regions and industries have strict data protection regulations, and non-compliance can result in severe penalties.
• Intellectual property loss: Leaks of proprietary information can erode competitive advantages and result in significant strategic setbacks.

The Role of Remediation Scripts in DLP

Remediation scripts are automated tools designed to respond to Data Loss Prevention (DLP) incidents as they occur. These scripts are an integral part of a DLP strategy, providing a proactive approach to managing and mitigating potential data breaches. 

By automating the response process, remediation scripts ensure that incidents are addressed quickly and efficiently. It reduces the window of exposure and minimizes the impact on the organization. They can be tailored to the specific needs and policies of an organization.

Types of Remediation Scripts

Remediation scripts can be categorized into several types, each serving a different function within the DLP framework:

• Endpoint scripts: These scripts are deployed on individual devices or endpoints within the network. They can perform actions such as isolating a compromised device and DLP delete sensitive data from unauthorized locations. They even block the execution of unauthorized applications and control the spread of potential threats from individual devices.
• Incident management scripts: These scripts cover the broader aspects of incident response, including logging incident details, notifying relevant personnel, and establishing follow-up processes. They ensure that every incident is recorded and assessed for a coordinated response and to improve prevention strategies.
• Policy scripts: Policy scripts enforce the organization's data protection policies automatically. They can modify access permissions, redirect data flows, or block data transfers based on predefined rules. By enforcing policies consistently, these scripts help prevent incidents before they occur and ensure compliance with regulatory requirements.

How Remediation Scripts Work in Response to DLP Incidents

Remediation scripts are triggered by DLP systems when they detect an incident that violates predefined data protection policies. Once activated, the scripts follow a set of programmed instructions tailored to the nature of the incident. Here's how they operate:

• Detection: The DLP system identifies a potential threat or policy violation, such as an unauthorized attempt to copy or send sensitive data.
• Analysis: The system assesses the severity and nature of the incident to determine the appropriate response based on predefined criteria.
• Execution: The relevant remediation script is triggered to execute actions designed to mitigate the incident. This could involve quarantining affected data, revoking access permissions, or alerting the security team.
• Notification: The script informs the relevant stakeholders about the incident and the actions taken. It ensures transparency and enables further investigation if necessary.
• Logging: All actions and outcomes are recorded for audit purposes and future analysis. It helps organizations improve their DLP strategies and prevent similar incidents.

What are the DLP Remediation Techniques?

DLP remediation techniques define the actions taken to mitigate potential data breaches and ensure sensitive information remains secure. Listed below are the techniques:

1. DLP masking

DLP mask involves hiding specific data elements within a dataset to protect sensitive information from unauthorized access. This is achieved by replacing the original data with pseudonyms or other non-sensitive equivalents. It ensures that the data remains usable for legitimate purposes without exposing the actual information.

It is effective in environments where data needs to be shared for development, testing, or analytics but contains sensitive information. Additionally, it can be used in user training scenarios or third-party collaborations where data exposure needs to be minimized.

2. DLP encryption

DLP encrypt transforms sensitive data into a coded format, making it unreadable to unauthorized users. Access to the data requires decryption keys so that only authorized personnel can view the original information.

Encryption is crucial for protecting data in transit, such as emails or data moving across networks, and data at rest. It includes files stored on servers, laptops, or external drives.

3. DLP blocking

DLP block prevents the transfer or sharing of sensitive information based on predefined policies. When a potential data breach is detected, the DLP system automatically blocks the transmission of the sensitive data. It prevents the data from leaving the secure environment.

Blocking assists in preventing unauthorized data exfiltration through email, cloud storage, or USB drive copying. It is also useful in real-time scenarios like stopping unauthorized print jobs or blocking access to restricted websites.

4. End user remediation

End user remediation involves assigning the remediation process to the end users, typically the data owners or those closest to the incident. This approach allows for quicker resolution times and reduces the burden on IT departments.

Involving end users can lead to faster incident resolution, increased awareness of data protection policies, and improved data handling practices. It also empowers employees to take responsibility for the data they handle.

Configuring Remediation Actions in DLP Solutions

Modern DLP solutions offer a range of remediation actions, from alerts and quarantines to encryption and deletion. Configuring these settings involves defining the conditions under which each action is triggered and who is notified.

Aligning remediation actions with organizational policies ensures that incident responses are consistent, appropriate, and compliant with regulatory requirements. It also helps maintain the balance between security and operational efficiency, particularly when DLP redact strategies are in place.

Best Practices for Implementing DLP Remediation Techniques

Here are some best practices to guide you in selecting and applying the right remediation strategies for your organization.

• Assess your data: Classify data based on sensitivity and compliance requirements to determine the appropriate level of protection needed.
• Understand regulatory requirements: Know the legal and regulatory frameworks applicable to your industry and region. This understanding will guide the selection of remediation techniques that ensure compliance.
• Evaluate your risk profile: Conduct regular risk assessments to identify potential data security threats and vulnerabilities. This will help you prioritize the techniques based on the likelihood and impact of different types of data breaches.
• Tailor remediation to data context: Set policies to protect for each type of data. For instance, encryption may be essential for protecting data at rest, while blocking may be more appropriate for preventing unauthorized data transfers.
• Awareness campaigns: Run ongoing awareness campaigns using posters, emails, and intranet articles to keep data protection top of employees' minds.
• Feedback and reporting mechanisms: Encourage employees to report suspicious activities or potential data breaches and provide feedback on DLP policies and training.

What Makes Strac Stand Out in the DLP Space?

Strac has established itself in the DLP space through its innovative features and user-centric functionalities for cloud, SaaS, and endpoints. Its features are listed below:

Automated detection and redaction

Strac’s DLP redact capabilities to identify and mask sensitive information across various data formats and platforms. Strac is more accurate and faster than traditional DLP, which requires manual tagging and classification, leading to scalability issues and requiring the lion’s share of your security teams’ time to work with.

No-code integrations

Strac’s seamless, integration with most SaaS applications enable organizations to implement DLP measures without technical expertise and disrupting existing workflows.

Real-time monitoring and alerts

Strac provides immediate notifications about potential data breaches or policy violations. It enables swift preventative actions and ensures that organizations respond instantaneously to threats.

Compliance management

In terms of regulatory compliance, the platform helps organizations adhere to various data protection standards and regulations. It automates the compliance process and provides clear insights into data handling practices.

Advanced scanning capabilities

Strac’s advanced scanning capabilities allow for deep data analysis and inspection beyond simple text matches. This includes the ability to understand context, recognize patterns, and identify sensitive information hidden within structured and unstructured data.

Deep integrations with SaaS, endpoints, and cloud apps

The integration with SaaS, endpoints, and cloud apps ensures that DLP policies are consistently applied across all data environments. This comprehensive protection is crucial for securing data regardless of its location.

Zero data architecture

Strac's innovative data architecture, which does not store or process data, sets a new standard for data security. It minimizes the risk of data breaches within the DLP system itself and provides an additional layer of security.

Schedule a free meet to learn how Strac meets your specific data security needs.