Guide to Performing a Data Risk Assessment

Most companies know how to engage in a security risk assessment. However, the first step in the security assessment process should be engaging in a data risk assessment. While the two sound similar, they provide different insights. This guide to performing a data risk assessment explains what it is, why it’s important, and how to engage in one.

What is a data risk assessment?

A data risk assessment (DRA) is the process of reviewing the locations that store and manage sensitive data, including intellectual property and personally identifiable information (PII). By taking a systemized approach, a DRA reviews where sensitive data is located, who accesses it, and any changes made to data access controls.

Often, companies know that they maintain sensitive information, but they may not be able to identify all the types of data and locations where they store it. The data risk assessment includes reviewing databases, files, shared drives, and collaboration tools to determine whether they contain critical employee, customer, project, client, or business-sensitive information.

Why is a data risk assessment important?

There’s a saying in security that you can’t secure what you don’t know you have. A data risk assessment helps you gain visibility into all the potential threat vectors that can lead to security or privacy violations.

A data risk assessment enables you to evaluate:

• Risk of managing PII
• Legal, regulatory, and industry-standard compliance posture
• Organizational baselines for risk tolerance
• Potential vulnerabilities that increase the likelihood of a data leakage or breach
• Security key-performance indicators
• Additional data security investment needs

How to perform a data risk assessment

A strong data risk assessment usually follows a three-step process.

Map Data to Applications

The first step is gaining full visibility into all the data that you store, collect, and transmit, referred to as a data footprint. When engaging in this process, you need to define:

• Data owners/data stewards: who in a department or domain is responsible for the collection, protection, and quality of data.
• Data types and attributes: the process of identifying and tagging sensitive files with classifications to enhance controls
• Data classification: the risk level and potential impact to the organization if the data is compromised

As part of this process, you want to consider whether a data type or attribute is high, medium, or low risk. However, to complete this process, you want to make sure that you also decide how to manage access to the data. You might want to consider assigning a classification level like:

• Restricted: data whose unauthorized disclosure, alteration, or destruction poses a high level of impact to the organization
• Private: data whose unauthorized disclosure, alteration, or destruction poses a moderate level of impact to the organization
• Public: data whose unauthorized disclosure, alteration, or destruction poses a low level of impact to the organization

Once you define the responsible parties and risk levels, you need to make sure that you map the data to the applications that use it, including:

• Applications: list of applications that query or use data
• Data environment: geographic locations or regions where data resides
• Data flows: the way data travels between applications, databases, and processes
• Controls: security controls used to protect in-scope data

Assess risk

This process involves reviewing, analyzing, and assessing threats and vulnerabilities that can place data at risk.

Some risks to review include:

• Excess access: users with more access than necessary to complete job functions
• Outdated user permissions: users who keep access from one job within the organization to another may no longer need historic access
• File sharing: “anyone with a link” permissions
• Collaboration tools: sharing data in chat tools like Slack or Microsoft Teams
• Stale data: data kept beyond retention policy periods
• Privileged Access: users with administrative or superuser privileges
• Service accounts: non-human privileged accounts that run automated services and execute applications

Using automated solutions can help streamline this process by scanning data repositories. Then, they scan data repositories and analyze data storage, handling, and security processes, practices, and controls.

Remediate vulnerabilities

Once you assess potential risks, you need to mitigate risk by remediating weaknesses. Some potential remediation activities include:

• Principle of least privilege: Ensure users have only the least amount of access needed to complete job functions by using role-based access controls (RBAC) and attribute-based access controls (ABAC)
• Multi-factor authentication (MFA): Place additional authentication controls around sensitive data, including step-up authentication when users move between applications and modules
• Global group access: Remove global access group permissions that allow everyone in the organization to access folders and create an active users group
• Data-centric security policy: Focus on securing sensitive data types with policies and controls that take business context as well as transmission across applications and storage locations into account
• Data sharing policies: Establish and enforce policies that define when and how to share data with external users including offline access
• Data access monitoring: Define “normal” user behaviors and monitor for “abnormal” access, including downloading and after-business-hours access
• Data retention policies: Review and enforce data retention policies, including how to dispose of data once the retention period is over

Moving from a traditional security approach to a data-centric security approach can be challenging. For example, a traditional approach to securing networks focuses on firewalls that allow traffic in and out of a network. However, distributed workforces connect to your data from the public internet. This means that you need to secure the transmission itself, like with a virtual public network (VPN) or Secure Access Service Edge (SASE) to protect data while in transit.

How SecurityScorecard Helps Protect Data

SecurityScorecard’s security ratings platform helps organizations take a proactive approach to monitoring security and protecting sensitive information. Our security ratings use an easy-to-read A-F rating scale that provides visibility into your data security controls’ effectiveness. SecurityScorecard’s platform sends actionable alerts to your security team across ten categories of risk factors so that you can continuously monitor for new risks to sensitive data.

Creating a data-centric security program requires visibility across all third-party vendors, Software-as-a-Service (SaaS) applications, and storage locations. With SecurityScorecard, you can create a resilient approach to cybersecurity that mitigates data risks wherever your information resides.