What is data exfiltration?
Data exfiltration is when sensitive data is accessed without authorization or stolen. This can occur due to hackers exploiting misconfigurations, rogue insider threats, or other malicious activities. Just like any data breach, it can lead to financial loss, reputational damage, and business disruptions
Securing your cloud data in today’s threat landscape is critical, making protecting it against data exfiltration a top priority. This blog covers data exfiltration techniques, as well as the methods for preventing such attacks.
What qualifies as sensitive data?
Sensitive data refers to any information that, if accessed by unauthorized individuals, could cause harm to individuals, businesses, or governments. It is categorized into several types based on its use:
Personally identifiable information (PII): Data that can be used to identify an individual, such as names, Social Security numbers, addresses, phone numbers, and financial details.
Protected health information (PHI): Medical records, patient data, and healthcare-related information governed by regulations like HIPAA to protect patient privacy.
Intellectual property (IP): Proprietary business data, including trade secrets, patents, research findings, and source code, which give companies a competitive edge.
Financial records: Banking details, credit card numbers, tax records, and transaction history that could be exploited for fraud or financial theft.
Government and corporate data: Classified government documents, legal records, and confidential business strategies that, if leaked, could lead to national security or regulatory issues.
Sensitive data is a prime target for cybercriminals and malicious insiders because of its high value in financial fraud, identity theft, and corporate espionage. Attackers can sell stolen personal or financial data on the dark web, use PHI for medical fraud, or exploit trade secrets for competitive advantage.
Data breaches vs Data leakage vs Data exfiltration
Data exfiltration, data leakage, and data breach are terms often used in the context of cybersecurity and information security. While they are related, each describes a different scenario in how sensitive data is improperly accessed or disclosed.
Data Breach: A broad term for any incident where sensitive information is accessed by someone who shouldn't have it. This can be intentional (hacking) or unintentional (misconfiguration). Breaches can involve data exfiltration, but also other actions like data encryption (ransomware).
Data Leakage: The accidental exposure of sensitive data. This can happen due to technical vulnerabilities or human error, like sending an email with confidential information to the wrong address.
Data Exfiltration: The intentional theft and removal of data from a system. This often happens after a data breach, where an attacker steals the exposed data. Exfiltration can involve copying data, uploading it to a remote server, or transferring it to a physical device.
Understanding data exfiltration techniques
The cloud offers convenience and flexibility, but it also raises data security risks. Various techniques exist for extracting sensitive information from your cloud environment. We discuss the methods cybercriminals most commonly use below.
| Technique | Description |
|---|---|
| Phishing and social engineering | Attackers use phishing emails or social engineering to trick victims into revealing cloud credentials or authentication tokens. These tactics, such as deceptive messages or fake websites, target cloud admins or users with sensitive access. Once hackers obtain credentials, they can access cloud resources, steal data, and launch further attacks. |
| Insider threats | Employees or authorized users can misuse their access to cloud data for personal gain, spying, or malicious activities. Insider threats are more dangerous than external actors due to their knowledge of the cloud environment and potential to exploit physical access to devices. This makes detecting and preventing data exfiltration more difficult. |
| Data interception | When data flows between cloud services and end users, it is inherently vulnerable to data interception and eavesdropping. Hackers can use man-in-the-middle (MIIM) attacks, packet sniffing, or compromised networks to intercept and manipulate data packets, enabling them to steal sensitive information or inject harmful payloads into the data. |
| Misconfigurations | Misconfigured cloud resources, like storage buckets, databases, and firewalls, can expose sensitive data to the internet. Common issues include weak access controls, excessive permissions, and unencrypted data, increasing the risk of data exfiltration. |
| Data leakage & breaches | Data leakages happen in the cloud when organizations fail to enforce data loss prevention measures. Data breaches are due to unmitigated security vulnerabilities, cloud service misconfigurations, and sophisticated cyberattacks. |
| Unauthorized access | Malicious actors can gain unauthorized access to cloud environments exploiting various vulnerabilities to view, download, manipulate, or exfiltrate sensitive data. |
| DNS tunneling and covert channels | Attackers disguise exfiltrated data as legitimate DNS queries, HTTP requests, or other normal network traffic to evade security monitoring. |
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Key examples of data exfiltration
Here are key real-world examples of how attackers exploit different techniques to steal information.
Email-based exfiltration
Phishing remains one of the most effective methods for stealing sensitive data. In 2020, Magellan Health suffered a ransomware attack after an employee fell for a spear phishing email. Hackers exfiltrated employee data, including Social Security numbers and tax details, before encrypting files. The breach impacted nearly 365,000 individuals, highlighting the dangers of email-based attacks.
FTP or file-sharing services
Compromised file-sharing credentials can provide attackers with direct access to critical systems. Since September 2022, tens of thousands of websites targeting East Asian audiences have been under attack. Hackers have exploited stolen FTP credentials to inject malicious scripts, redirecting users to unwanted sites while secretly harvesting visitor data. This ongoing campaign highlights the persistent threat posed by compromised file-sharing services in enabling large-scale data exfiltration.
Cloud-based exfiltration
Cloud misconfigurations are a major target for cybercriminals looking to exfiltrate sensitive data. In 2019, a former AWS employee exploited a firewall misconfiguration to steal data from 106 million Capital One customers. Exfiltrated data included Social Security numbers, bank account details, and credit scores. This breach underscores the importance of strong cloud security controls to prevent unauthorized access.
Command and control (C2) channels
In December 2021, security researchers identified a critical vulnerability in Apache Log4j (CVE-2021-44228) that allowed remote code execution. Hackers quickly exploited this flaw to gain unauthorized access to unpatched systems, using C2 channels to deploy malware, steal data, and run cryptomining operations. This incident underscores the urgent need for timely patching to prevent large-scale data exfiltration.
Custom malware and advanced persistent threats (APTs)
APT10, a Chinese state-sponsored hacking group, remains an active threat in global cyber espionage. Known for Operation Cloud Hopper, the group targets corporations and government agencies by infiltrating managed service providers (MSPs) to access their clients’ networks. APT10 continues to use stealthy tactics and custom malware to exfiltrate sensitive data, posing an ongoing risk to organizations worldwide.
A few simple best practices for preventing data exfiltration
Preventing and detecting data exfiltration in the cloud involves a multi-layered approach that spans across several aspects of cloud infrastructure and operations. Here are detailed best practices, categorized for ease of implementation:
1. Data Management and Protection
Data Classification: Implement a data classification scheme to identify sensitive or confidential data that requires stricter controls.
Encryption: Use encryption for data at rest and in transit. Employ strong encryption standards and manage encryption keys securely.
Data Loss Prevention (DLP): Deploy DLP solutions to monitor and control data transfer, ensuring sensitive information is not sent outside the organization without authorization.
2. Access Control and Identity Management
Least Privilege Access: Assign permissions based on the principle of least privilege, ensuring users and applications have only the access they need.
Multi-Factor Authentication (MFA): Enforce MFA for accessing cloud resources to add an additional layer of security.
Regular Audits: Conduct regular audits of user activities and permissions. Remove inactive user accounts and unnecessary permissions.
3. Network Security
Secure Network Configuration: Use firewalls, virtual private networks (VPNs), and network access control lists (ACLs) to restrict network traffic.
Segmentation: Segment network resources to limit lateral movement and contain potential breaches. Use private networks for sensitive operations.
Intrusion Detection Systems (IDS)/Intrusion Prevention Systems (IPS): Deploy IDS/IPS to monitor network and system activities for malicious activities or policy violations.
4. Endpoint Security
Endpoint Protection: Use anti-malware, anti-virus software, and endpoint detection and response (EDR) tools to protect against malicious software.
Secure Configuration: Ensure that endpoints are securely configured and regularly updated with the latest patches.
Device Management: Implement device management policies, including the use of secure, approved devices for accessing cloud resources.
5. Monitoring and Anomaly Detection
Log Management: Collect and analyze logs from all cloud resources. Use centralized log management solutions for better visibility.
Anomaly Detection: Use tools that employ machine learning or other methods to detect unusual patterns that may indicate data exfiltration attempts.
Alerting: Set up alerting mechanisms for suspicious activities. Ensure that the alerts are actionable and monitored continuously.
6. Incident Response and Forensics
Incident Response Plan: Develop and regularly update an incident response plan that includes procedures for responding to data exfiltration incidents.
Forensic Analysis: Be prepared to conduct forensic analysis in the event of an incident to determine the cause and scope of the breach.
Training and Awareness: Regularly train staff on security best practices, incident response procedures, and the latest cyber threats.
7. Vendor and Third-party Management
Vendor Risk Assessment: Conduct risk assessments of third-party vendors who have access to your data or infrastructure.
Contractual Controls: Ensure contracts with vendors and third parties include clauses that mandate adherence to your organization’s security policies and standards.
Continuous Monitoring: Monitor third-party activities and security postures regularly to ensure they comply with agreed-upon standards.
Implementing these best practices requires a continuous effort and regular review of security policies and procedures to adapt to new threats and changes in the cloud environment.
Signs of data exfiltration or data theft in an organization
Detecting data exfiltration early is crucial to preventing breaches. Watch out for these warning signs that your sensitive information may be at risk:
Unusual data transfers or large file movements: Unexpected spikes in data transfers, especially outside normal business hours, may indicate an exfiltration attempt.
Unauthorized access to sensitive data: Repeated access attempts or unusual access patterns to critical files by unauthorized users can signal a breach.
Anomalous network activity and outbound connections: Unexpected data flows to unfamiliar IP addresses or encrypted outbound traffic could suggest data is being exfiltrated.
Increased use of external storage devices: A sudden rise in USB usage, external hard drives, or cloud file-sharing services may indicate an insider threat.
Suspicious email activity or account behavior: Employees sending large attachments, forwarding sensitive information, or using personal email accounts to handle company data can be red flags.
Insider threats exhibiting unusual behavior: Employees accessing data outside their role, resigning staff downloading excessive files, or unusual login locations may point to malicious intent.
Security tool alerts or endpoint detections: Warnings from DLP tools, EDR systems, or anomaly detection solutions should be investigated promptly.
What to do if your organization's data is exfiltrated
A data exfiltration incident can have serious consequences, so a quick response is necessary to minimize damage and prevent future attacks. Follow these steps to contain the breach and investigate its cause:
1. Identify and contain the breach
Use forensic tools and security logs to determine the scope of the breach, identifying which systems, files, and user accounts were affected. Immediate containment is crucial, so disable compromised accounts, revoke unauthorized access, and isolate impacted systems to prevent further data loss.
If the breach involves cloud environments, reconfigure security settings and review recent access logs to detect ongoing threats.
2. Analyze attack vectors
Investigate how the attackers gained access—whether through phishing, misconfigurations, insider threats, or vulnerable endpoints. Review audit logs, threat intelligence reports, and network traffic to identify the exfiltration method.
Once the exfiltration method is identified, apply patches, update security policies, and strengthen access controls to close exploited gaps and prevent similar attacks.
3. Notify relevant stakeholders
Depending on the nature of the exfiltrated data, legal and regulatory obligations may require disclosure. Compliance frameworks like HIPAA, GDPR, and CCPA, mandate timely reporting of breaches to regulators and affected individuals.
Organizations should work with legal teams to ensure all necessary notifications are made while maintaining transparency with customers, partners, and internal teams.
4. Implement stronger security measures
Use insights from the incident to reinforce security policies, tighten access controls, and improve DLP measures. Conduct red team exercises and security simulations to identify and address vulnerabilities before attackers can exploit them again.
If you haven't already had a session on security awareness, make sure to conduct a training session for your employees and increase real-time monitoring to detect and respond to anomalies before they escalate.
5. Monitor for further threats
Even after containment, attackers may attempt follow-up intrusions using compromised credentials or leftover backdoors. A thorough post-incident analysis is vital to ensure no residual risks remain.
Implement continuous security monitoring, penetration testing, and endpoint detection tools to identify any lingering threats and bolster long-term resilience.
Data exfiltration protection with Wiz
Looking at the evolving threat landscape, organizations need a comprehensive suite of security solutions to safeguard their sensitive data and proactively mitigate data exfiltration risks.Wiz provides a comprehensive approach to detect data exfiltration through its Data Security Posture Management (DSPM) capabilities and real-time threat detection features.
The system employs the Wiz Runtime Sensor and other runtime signals, such as cloud events, to detect and respond to suspicious and malicious activities that could indicate data theft or leakage. This enables organizations to prevent data exfiltration and perform efficient investigations to understand the scope of any potential breach.
For instance, Wiz's Data analyzer samples and analyzes data in resources to detect sensitive information and secrets. These findings are correlated with other risk factors like exposure and vulnerabilities to provide a full risk assessment of your data assets. Additionally, the analyzer in Wiz can identify risky lateral movement paths and highlight high privileged roles, which are often used in data exfiltration scenarios.
By integrating with third-party platforms, Wiz can also enrich its data findings and increase visibility into sensitive data and related security risks, further enhancing its ability to detect potential data exfiltration attempts.
Wiz’s DSPM capabilities can also be extended to AI, ensuring that sensitive data is not included while training AI models to prevent possible attack paths.
With Wiz’s arsenal of tools, you can proactively take care of your organization’s data security in the cloud and implement the right measures to prevent data exfiltration.
Get a personalized demo today to learn more!
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