What Is Data Exfiltration?

Data exfiltration is the unauthorized copying, transfer, or retrieval of data from a server or an individual’s computer. It’s a type of security breach that occurs when personal or company data is illicitly copied, transferred, or retrieved from a device or server without proper authorization, often with malicious intent.

As a critical security concern with potentially catastrophic consequences, organizations with high-value data are particularly at risk of data exfiltration attacks, whether from outside threat actors or trusted insiders. They can occur through various attack methods, ranging from phishing and malware attacks to physical theft and file-sharing sites.

Today, data exfiltration is a top organizational concern. According to a recent study from McAfee, 61% of security professionals have experienced a data breach at their current company. Stricter compliance regulations around data privacy, like GDPR and the California Consumer Privacy Act, have raised the stakes for reporting data exfiltration events.

Outsider attacks and insider threats are the two primary ways data is exfiltrated.

Insider threat incidents are one of the top causes of data exfiltration, whether accidental or malicious. Malicious insider threats are trusted individuals who intentionally exfiltrate data to harm an organization for their own (or someone else’s) gain. However, two out of three insider threat incidents are accidental, which could prove equally costly to an organization if these mistakes take too long to investigate.

As for outsider attacks, data exfiltration can happen through:

• Social engineering via email or various internet channels like spoofed sites for phishing, file-sharing sites, and social media.
• Malware injection onto an endpoint, such as a computer or mobile device connected to the corporate network.
• Hackers who breach systems that rely on vendor-set or easy-to-crack passwords.

Data exfiltration can be conducted manually by an individual with physical access to a computer but can also be automated through malicious programming over a network.

According to McAfee’s research cited above, the most common data exfiltration methods at organizations include:

• Database leaks
• Network traffic
• File shares
• Corporate email
• Malware attacks

Cloud Apps and Databases

A recent “CA Technologies Insider Threat” report called databases “The number-one most vulnerable IT asset,” ahead of file servers, cloud apps, and mobile devices. Because the data contained within them is so valuable, databases are commonly targeted by both insiders and external attackers alike.

Exfiltration of Data Through Removable Storage Media

Removable media are another common insider threat vector. Even in the age of ubiquitous cloud storage, old-school data exfiltration methods like flash drives are still pervasive. While altogether banning USB use for every organization is unrealistic, employees must understand the risks and adhere to policies around data access and storage.

While file shares top the list of data exfiltration methods in North America, USB drives are the number-one exfiltration vector in APAC and Europe.

Accidental Insider Threats

Besides users with malicious intentions, accidental insider threats are a primary cause of data exfiltration. Phishing emails and social engineering attacks remain a tried-and-true way for hackers to access company data. In addition, weak or reused passwords or a lack of multifactor authentication, are common weaknesses hackers seek to infiltrate a user’s account. In these scenarios, the best defense is often cybersecurity awareness. McAfee’s study also showed that insider threats frequently used email data exfiltration.

Data Misuse

According to a recent Verizon Insider Threat Report, misuse is another top cause of data exfiltration. Unlike its careless cousin, the accidental insider threat, misuse is when users intentionally or unintentionally circumvent security controls or policies. For example, an employee may use unsanctioned software to work with a third-party contractor because it’s faster or easier to use, resulting in unintentional data exfiltration.

Employees can also exfiltrate company data in various ways, including personal email accounts, cloud storage, printers, file-sharing sites, keyboard shortcuts, and more. Organizations can find it challenging to distinguish legitimate user activity from malicious activity. However, using a system that delivers context into user actions can help.

Malware Attacks

Data exfiltration is often the target of malware attacks, where the malware is injected into a computer or mobile device connected to an organization’s network. Once injected, the malware exfiltrates the data to an external server controlled by the attacker, where it’s sold or distributed. These malware attacks can spread across an organization’s network and infiltrate other devices, searching for sensitive corporate data to exfiltrate information.

While these terms are often used interchangeably, they represent distinct types of data security incidents. Understanding their differences is crucial for proper incident classification and response.

Data Exfiltration is a deliberate, targeted extraction of data from a secure system. It involves the unauthorized transfer of data to an external destination and typically requires malicious intent. This occurs through sophisticated attack methods like malware deployment, social engineering, or exploitation of system vulnerabilities.

Data Leakage occurs when sensitive information is unintentionally exposed due to human error or system misconfiguration. Common examples include misconfigured cloud storage, accidental email attachments, or improper data handling. Unlike exfiltration, leakage doesn’t require malicious intent and often results from negligence or lack of security awareness.

Data Breach encompasses a broader category of security incidents where unauthorized access to protected information occurs. It can result from either exfiltration or leakage and includes any incident involving unauthorized disclosure, loss of control, or data compromise.

Detecting data exfiltration requires a multi-layered approach to identify suspicious patterns and anomalous behaviors. Network monitoring tools can spot unusual spikes in outbound traffic or data transfers at odd hours.

Organizations should watch for telltale signs like large, compressed file transfers, unexpected admin account usage, and unusual access to sensitive databases. Advanced detection systems can identify when data is encoded or encrypted differently than normal traffic patterns. Some of the most common detection methods include:

• Monitoring DNS queries: Investigating suspicious DNS queries that lead to known malicious domains. This is crucial as attackers often use DNS tunneling to surreptitiously exfiltrate data. Regular analysis of DNS query patterns and volume can help identify command-and-control communications.
• Analyzing outbound email traffic: Utilizing automated tools to scrutinize outgoing emails for anomalies in content, large attachments, and unauthorized recipients. This includes monitoring for sensitive data patterns, unusual encryption methods, and suspicious email forwarding rules that could indicate compromise.
• Tracking file access patterns: Implementing access logs and analytics to detect patterns that deviate from the norm, such as an employee accessing large amounts of sensitive data they wouldn’t typically need. This includes monitoring for mass file downloads, unusual file types, or access from unexpected locations.
• Implementing data loss prevention (DLP) solutions: DLP systems can actively monitor and restrict the movement of sensitive data, alerting security teams when potential exfiltration attempts are detected. Modern DLP solutions can also identify and block attempts to transfer data to unauthorized cloud storage services or removable media.
• User and entity behavior analytics (UEBA): Employing UEBA tools to establish a baseline of normal user activity, alerting teams to deviations that could signify malicious intent. This includes monitoring login patterns, resource access timing, and unusual lateral movement across network segments.

Real-time alerts and automated response systems are also crucial detection features, as data exfiltration can happen within minutes. Security teams should regularly audit access logs and maintain updated threat intelligence feeds to spot emerging exfiltration techniques.

Preventing data exfiltration is a critical cybersecurity initiative that requires a comprehensive security strategy combining advanced monitoring tools, zero-trust architecture, and intelligent threat detection to address unauthorized activity in real-time. These measures, combined with the following tools and protocols, can effectively prevent data exfiltration from infiltrating an organization’s network:

• Monitor user activity: Implement UEBA to establish baseline behaviors and automatically detect anomalies. Administrators should track who accesses what files, when, and how often, using AI-powered analytics to identify potential insider threats and compromised accounts.
• Deploy adaptive authentication: Implement risk-based authentication that adapts security requirements based on user behavior, location, device health, and other contextual factors. This includes biometric verification and hardware security keys for high-risk actions.
• Implement modern identity management: Utilize password-less authentication methods where possible and enforce strong password policies when necessary. Implement Single Sign-On (SSO) solutions integrated with identity governance frameworks.
• Maintain robust patch management: Deploy automated patch management systems prioritizing critical security updates based on risk assessment. Implement vulnerability scanning and automated remediation workflows.
• Use advanced DLP solutions: Deploy next-generation DLP solutions with machine learning capabilities that can understand context and content. These tools should integrate with cloud services and provide real-time policy enforcement across all data channels.
• Implement end-to-end encryption and data classification: Apply intelligent data classification to automatically identify and protect sensitive information. Utilize homomorphic encryption for sensitive data processing and quantum-resistant encryption methods for data at rest.
• Balance security with productivity: Implement security measures that are contextually aware and risk-appropriate. Use progressive security controls that adjust based on risk levels while maintaining workflow efficiency.
• Deploy zero trust architecture: Implement a “never trust, always verify” approach with micro-segmentation and continuous validation of every access request.
• Enable cloud access security broker (CASB): Deploy CASB solutions to maintain visibility and control over cloud services while preventing unauthorized data movement.
• Implement network detection and response (NDR): Use NDR solutions to monitor network traffic patterns and detect potential exfiltration attempts in real-time.

Organizations should regularly assess and update these prevention measures as threat landscapes evolve. Success in preventing data exfiltration requires a holistic approach that combines technological solutions with strong security policies and ongoing employee education.

Proofpoint offers a comprehensive, people-centric approach to preventing data exfiltration through our integrated Enterprise DLP and Insider Threat Management solutions. Our unified platform provides unprecedented visibility and control across email, cloud, and endpoints.

Our Enterprise DLP solution delivers intelligent detection and response capabilities by combining content analysis with behavioral telemetry. This approach not only identifies sensitive data but also provides crucial context about how users interact with that information. The platform’s cloud-native architecture ensures quick deployment and seamless scaling to protect organizations of any size.

For enhanced protection, Proofpoint’s Insider Threat Management solution provides deep visibility into user behavior and data interactions. The platform can identify risky activities from careless, compromised, or malicious users through advanced behavioral analytics and AI-powered detection. With features like detailed activity timelines and automated alert systems, security teams can rapidly investigate and respond to potential insider threats.

The combination of these solutions creates a robust security framework that:

• Detects and prevents data loss across all channels
• Provides contextual insights into user behavior and intent
• Streamlines incident investigation and response
• Maintains user privacy while ensuring security
• Offers flexible deployment options with modern cloud architecture

Organizations looking to strengthen their data protection strategy can experience these capabilities firsthand through Proofpoint’s demonstration environment. Our security experts can help assess your specific needs and demonstrate how our integrated approach can protect your sensitive data while maintaining operational efficiency.

To learn more, contact Proofpoint.