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.
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 | Here, attackers leverage phishing emails or social engineering tricks to deceive victims into giving up their cloud credentials, passwords, or other authentication tokens. Tactics include deceptive emails, messages, or fake websites targeting cloud administrators or users with access to sensitive information. Once hackers acquire the needed credentials, they can gain unauthorized access to cloud resources and exfiltrate data, compromise systems, or perpetrate further attacks. |
| Insider threats | Employees or authorized users with access to cloud data can misuse their privileges to access sensitive information for personal gain, spy on organizations, or engage in malicious activities. These internal parties can be more dangerous than external actors, as they have detailed knowledge of the cloud environments, processes, and data at stake. They can also easily bypass traditional security controls, making it more difficult for a company to know an attack is underway and take action against it. |
| 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, such as cloud storage buckets, databases, and network firewalls, can create major security holes, exposing sensitive data to the public internet. Common misconfigurations include weak access controls, broad security permissions, and unencrypted data—all of which could lead to data exfiltration risks. |
| 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. |
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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.
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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