What is Data Exfiltration and How to Prevent It?

Data exfiltration is a nightmare for many organizations. Every 39 seconds, a cyberattack occurs, underscoring the relentless pressure businesses face to secure their data. According to the IBM Cost of a Data Breach Report 2024, the average cost of a data breach has surged to $4.88 million, reflecting a 10% increase from the previous year.

The impact of data exfiltration goes beyond financial losses. It erodes trust, disrupts operations, and exposes organizations to compliance penalties and legal repercussions.

In this blog, we’ll dive into the mechanics of data exfiltration, the data most targeted by attackers, lessons learned from recent breaches, and practical steps you can take to protect your organization.

What Is Data Exfiltration?

Data exfiltration refers to the unauthorized transfer of data from an organization to an external destination. This transfer can result from external cyberattacks, such as phishing or malware, or from insider threats, whether malicious or accidental. Regardless of the method, the consequences are often severe, making it essential for organizations to understand and address this threat effectively.

Watch the Keepnet Security Awareness Podcast episode below to learn more about data exfiltration and how to protect your organization.

How Does Data Exfiltration Work?

Attackers use a variety of tactics to exfiltrate data. The most common methods include:

• Phishing and Social Engineering: Cybercriminals trick employees into sharing sensitive information, such as credentials, or downloading malicious software.
• Malware Infections: Malware infiltrates networks, scans for valuable data, and transfers it to external servers.
• Compromised Email and Messaging Systems: Attackers exploit breached accounts to send sensitive data externally or trick employees into divulging more information.
• External Devices: Employees who store data on unsecured devices, such as USB drives or personal laptops, unintentionally create vulnerabilities.
• Cloud Misconfigurations: Poor cloud security practices can expose sensitive data to malicious actors, enabling data theft through compromised virtual machines or weak access controls.

Types of Data Targeted During Data Exfiltration

Hackers focus on data that is most valuable to organizations, such as:

• Financial Records – Data that can be used for fraud or to gain competitive insights.
• Intellectual Property (IP) – Trade secrets, proprietary algorithms, and other unique assets.
• Customer Databases – Personal and financial information of clients, which can be monetized.
• User Credentials – Logins that grant unauthorized access to broader systems.
• Personally Identifiable Information (PII) – Details like Social Security numbers and birth dates.
• Cryptographic Keys – Used to decrypt otherwise secure data.

Real-world Examples of Data Exfiltration: Case Studies

Real-world examples data exfiltration cases highlight the devastating consequences of data exfiltration:

• Anthem Health Insurance: An insider incident where an employee forwarded 18,500 members' records, including PII like social security numbers, to a third party. Source: SC Magazine.
• Unnamed Financial Company: Another insider case where a former employee exfiltrated nearly 100 GB of data, planning to sell it for $4,000 to a competitor. Source: Bleeping Computer.
• eBay: An outsider attack in 2014, where hackers used compromised employee credentials to affect 145 million users. Source: The Washington Post.
• Wawa: An outsider incident in 2019, with malware harvesting credit card data of over 30 million customers. Source: Krebs on Security.
• British Airways: An outsider breach starting in June 2018, exfiltrating data of over 400,000 customers, leading to a £20 million fine. Source: Information Commissioner's Office (ICO).

These incidents were chosen to reflect the diversity of methods (e.g., insider sharing, malware, phishing) and sectors (healthcare, finance, e-commerce, retail, travel), ensuring a broad perspective.

How to Detect Data Exfiltration

Timely detection of data exfiltration is crucial in preventing significant harm and financial loss to an organization. Implementing sophisticated monitoring and detection mechanisms ensures early warning signs are acted upon swiftly.

Here's an in-depth look at advanced detection methods:

Network Traffic Analysis (NTA)

Network traffic analysis involves continuous monitoring of network data flow for signs of potential data breaches. Key techniques include:

• Anomaly Detection: Utilizing machine learning algorithms to detect deviations from normal network traffic patterns, such as sudden spikes in data transfer volumes or unusual destination IP addresses.
• Deep Packet Inspection (DPI): Inspecting data packets thoroughly to uncover hidden or disguised exfiltration activities.
• Flow Analysis: Analyzing metadata (e.g., NetFlow, IPFIX) to identify unusual or large-scale data transfers, particularly to external and high-risk IP addresses.

Behavioral Analytics

Behavioral analytics leverages machine learning to establish normal user behavior patterns and identifies deviations that may indicate data exfiltration attempts:

• User and Entity Behavior Analytics (UEBA): Monitoring user activities such as atypical file accesses, unusual login times, or abnormal data downloads.
• Geolocation Anomalies: Flagging access from unfamiliar locations or simultaneous access from geographically distant locations indicating potential compromised accounts.
• Contextual Analysis: Evaluating activities based on user roles, permissions, and historical behavior to detect suspicious deviations.

Endpoint Detection and Response (EDR)

Endpoint Detection and Response tools offer real-time monitoring and protection on user endpoints:

• Real-Time Threat Detection: Immediate identification of suspicious file transfers, unexpected network communications, and attempts to bypass security controls.
• Automated Response: Quick isolation of compromised endpoints, thereby containing potential data exfiltration events.
• Process and File Activity Monitoring: Continuous monitoring and logging of endpoint activities, highlighting abnormal behaviors indicative of malicious intent.

Data Loss Prevention (DLP) Systems

DLP solutions prevent unauthorized data transfers by monitoring sensitive data movements across organizational boundaries:

• Content Inspection: Scanning data transfers to identify and block confidential or sensitive information leaving the organization without proper authorization.
• Policy Enforcement: Establishing and enforcing granular data protection policies to restrict access and transmission of sensitive data based on context and role.
• Real-time Alerts: Prompt notifications upon detecting attempts to exfiltrate data, enabling immediate action.

Audit Logs and Monitoring

Audit logs serve as a critical source of information for detecting and investigating potential data exfiltration incidents:

• Comprehensive Log Collection: Regularly aggregating logs from networks, endpoints, applications, and cloud services.
• Correlation Analysis: Integrating logs from multiple sources to identify correlated patterns or activities signaling potential threats.
• Incident Response Support: Providing detailed records to assist forensic investigations, helping pinpoint the root cause of data breaches and strengthening future defenses.

By leveraging advanced data exfiltration detection techniques such as network traffic analysis, behavioral analytics, endpoint detection and response, robust DLP systems, and comprehensive log monitoring, organizations can significantly enhance their cybersecurity posture and rapidly respond to threats.

Best Practices for Preventing Data Exfiltration

Preventing data exfiltration requires a layered security approach:

• Conduct Data Risk Assessments: Regularly evaluate the sensitivity of your data and the potential threats to it.
• Implement Data Encryption: Encrypt data both at rest and in transit to minimize its value if stolen.
• Monitor User Behavior: Deploy tools to track and flag abnormal user activities.
• Enforce BYOD Policies: Restrict access to sensitive data on personal devices and ensure proper security measures are in place.
• Regular Backups: Frequently back up data to minimize the impact of breaches or accidental data loss.
• Restrict Privileged Access: Adopt a just-in-time access model to limit data exposure to only what is necessary for specific tasks.
• Employee Training: Educate your workforce on identifying phishing attempts and securely handling sensitive data.

Secure Your Organization with Keepnet Human Risk Management

Protect your organization from data exfiltration with Keepnet Human Risk Management Platform:

• Phishing Simulator: Train employees to spot phishing attempts with realistic simulations and track their progress to reduce risks.
• Security Awareness Training: Equip your team with practical knowledge to handle threats like phishing and ransomware through engaging, tailored programs.
• Incident Responder: Quickly detect, contain, and remediate security incidents with automated response tools, minimizing damage.

With Keepnet, strengthen your defenses by combining prevention, training, and rapid response into a single, effective platform.

Editor's note: This blog post was updated on June 19, 2025