Shadow Data: The Hidden Security Threat
What is shadow data?
Shadow data refers to the data that is created, stored, and managed outside of an organization’s approved IT systems and infrastructure. This data can be created by employees using their personal devices, using third-party applications and services, or even by simply saving files to local hard drives or cloud storage accounts without authorization.
The existence of shadow data can pose a significant security risk for organizations, as it can be difficult to track, control, and protect. Shadow data can also lead to data leaks and breaches if it contains sensitive or confidential information.
How does shadow data occur?
Shadow data happens when employees create, store, and manage data outside of an organization’s approved IT systems and infrastructure. This can occur for various reasons, such as convenience, productivity, or the use of personal devices and applications. For example:
- Employees may use their personal smartphones, tablets, or laptops to access and store company data, either to work remotely or for convenience.
- Employees may use unauthorized third-party applications or cloud services to collaborate, share, or store data, either because they find them more convenient or because they are not aware of the potential security risks.
- Employees may save files to local hard drives or cloud storage accounts without proper authorization, either because they want to keep a backup copy or because they do not want to use the organization’s approved systems.
This creates several challenges for organizations as the information stored in shadow IT systems is not under the control of the IT department, leading to issues of control, management, and security. Shadow data can pose significant risks to the organization, including data breaches, compliance violations, and reputational damage. Therefore, organizations need to take steps to manage and secure shadow data to minimize these risks.
Mitigating shadow data risks
Steps to mitigate the risk of shadow data include:
- Establishing clear policies and procedures for the use of personal devices and third-party applications to manage data.
- Providing regular employee training to raise awareness about the risks of shadow data and the importance of following security protocols.
- Implementing data classification and access controls to ensure that sensitive information is properly secured and accessed only by authorized personnel.
- Regularly auditing and monitoring shadow data usage to detect potential security risks and ensure compliance with organizational policies.
- Using security technologies such as encryption, firewalls, and anti-malware software to protect data against unauthorized access, theft, or loss.
- Collaborating with employees to identify and manage shadow data sources and develop solutions to address any risks or compliance issues.
Shadow IT vs Shadow Data
Shadow IT refers to the use of unauthorized hardware, software, or cloud services by employees, without the knowledge or approval of the organization’s IT department. Shadow IT can pose significant risks to the organization, including security vulnerabilities, compliance violations, and loss of control over data.
Shadow data, on the other hand, refers to the data created, stored, and managed outside of an organization’s approved IT systems and infrastructure, which can include data created by employees using Shadow IT. Shadow data can pose similar risks to the organization, including data breaches, compliance violations, and reputational damage.
While Shadow IT and Shadow data are closely related, they are not the same thing. Shadow IT can be a contributing factor to the creation of Shadow data, but Shadow data can also be created and managed by employees without the use of unauthorized hardware, software, or cloud services. Therefore, organizations need to address both Shadow IT and Shadow data to ensure that they are adequately managing and securing their data and IT systems.
Shadow data examples
- An employee who uses their personal email account to send and receive work-related emails, instead of using the organization’s approved email system. This creates shadow data because the emails and attachments are being stored outside of the organization’s control and may not be subject to the same security measures and policies.
- A team that uses a cloud-based collaboration tool, such as Dropbox or Google Drive, to share and store files that contain sensitive or confidential information. This creates shadow data because the organization may not be aware of the data being stored outside of their approved IT systems, and may not have visibility or control over who has access to the files.
- An employee who saves a copy of a sensitive document to their personal computer or USB drive, instead of saving it to the organization’s network drive. This creates shadow data because the organization may not be aware of the document’s existence and may not be able to ensure that it is properly secured or deleted when no longer needed.
Fines & Violations
The fines and violations associated with having shadow data depend on various factors, such as the type of data involved, the scope of the violation, and the laws and regulations applicable to the organization’s industry and location. Here are some examples of the fines and violations that can result from having shadow data:
- Data breaches: If shadow data contains personal information or other sensitive data, and is accessed or disclosed without authorization, the organization may face fines, legal actions, or reputational damage. For example, the European Union’s General Data Protection Regulation (GDPR) imposes fines of up to 4% of an organization’s global annual revenue or €20 million, whichever is higher, for data breaches.
- Non-compliance: If shadow data violates laws or regulations related to data protection, security, or privacy, the organization may face fines, legal actions, or reputational damage. For example, the Health Insurance Portability and Accountability Act (HIPAA) in the United States imposes fines of up to $1.5 million per violation for non-compliance with its regulations.
- Loss of intellectual property: If shadow data contains confidential or proprietary information, and is accessed or disclosed without authorization, the organization may lose its competitive advantage or intellectual property rights, which can result in financial losses, legal actions, or reputational damage.
In addition to these fines and violations, having shadow data can also lead to additional costs and risks, such as data recovery, data loss, increased IT support, and decreased productivity. Therefore, it is important for organizations to take proactive measures to identify, manage, and secure their shadow data to avoid these fines and violations.
BigID’s Approach to Reducing Shadow Data Risk
BigID is a data discovery platform for privacy, security, and governance that provides solutions to identify, manage, and secure an organization’s data, including shadow data. Here’s how BigID can help reduce or avoid shadow data risk:
- Data discovery: Using advanced AI and ML classification, BigID automatically and accurately discovers and classifies sensitive data, including shadow data, across on prem stores, cloud applications, and endpoints. Giving organizations greater visibility into their data landscape, understanding where their sensitive data resides, and prioritizing their data protection efforts.
- Access Intelligence: BigID’s Access Intelligence App detects excessive access and exposed data, while implementing a zero-trust model. Secure any overexposed data and swiftly address potential security breaches or unauthorized access— decreasing the chances of internal security threats, data leaks, and data breaches.
- Data remediation: BigID’s Data Remediation App effectively addresses and resolves issues related to high-risk, sensitive, and regulated data. Utilize custom workflows, complete audit trails, and notifications to confidently manage data remediation. Remain informed with alerts and notifications throughout the remediation process.
- Risk analysis: BigID’s Risk Scoring App assesses the risk associated with your shadow data, based on factors such as data sensitivity, access permissions, and usage patterns. Allowing you to prioritize data protection efforts, allocate resources effectively, and demonstrate compliance with regulatory requirements.
To start minimizing your organization’s risk and uncovering your shadow data— get a 1:1 demo with BigID today.