76% of IT security leaders experienced data breaches involving the loss or theft of sensitive information contained in documents or files. – Code42 2021 Data Exposure Report
The increasing prevalence of data breaches was discussed often in 2021 as enterprises such as LinkedIn, Colonial Pipeline, and Volkswagen were breached, exposing massive volumes of personal information and causing damage worth millions of dollars.
Most organizations focus on thwarting cyberattacks on critical resources. They fail to invest as much time on fully locking down data stores as they do on a whack-a-mole approach towards security threats. As the scale and complexity of data breaches are predicted to rise again in 2022, this seems as good a time as any to highlight the importance of reducing the attack surface before it is stormed. To achieve this, cracking down on activities that lead to data exposure and identifying exposed data are crucial steps.
What is sensitive data exposure?
While organizations remain largely focused on endpoint security and perimeter protection, the problem of unsecured data in storage repositories has compounded. On top of this, rapid data growth year after year, proliferating ROT data, and sparse file analytics have rendered most data security strategies inefficient.
Sensitive data exposure occurs when data that is sensitive, business-critical, or both is inadequately protected and inadvertently left vulnerable to attackers. Since this vulnerability has not yet been exploited to access the exposed data maliciously or steal it, it differs from a data breach. Essentially, it is an open door that, if located by threat actors, will be taken full advantage of.
Security pitfalls that lead to sensitive data exposure
Whatever the vector of data breach, sensitive data exposure is enabled primarily by permission vulnerabilities. Some of the security pitfalls that lead to sensitive data exposure are:
Broken inheritances allow users to access a file even if they don’t have permission to access the folder it is stored in. This permission inconsistency poses a critical access control issue as employees could have unnecessary access to sensitive data.
Excessive permissions assigned to users
User roles are constantly in flux in organizations, and a user’s assigned permissions and job role are liable to fall out of sync, leading to privilege creep. Further, overexposed files such as those that are accessible by the Everyone security group or allow Full Control access to some users are another security risk. In particular, user accounts with Full Control access to sensitive files are a goldmine for hackers carrying out credential-theft attacks. Analyzing effective permissions and reviewing access rights periodically will help run a tight ship and also streamline audits for the PCI DSS, GDPR, and other regulations.
Absence of data remediation measures
Not all data is valuable, and hoarding outdated, trivial, or duplicated data only slows down data protection activities. Further, the older a file, the more likely that its data is past its limitation period and that its permissions are inconsistent with present needs. Periodic data remediation is key to preventing non-compliance penalties and streamlining file analytics and e-discovery.
Unsecure storage locations
Sensitive files in loosely secured locations are a security vulnerability by themselves, but when stored in open shares, they are especially problematic. In open shares, even users with the lowest access levels can lead to massive security incidents with one misstep. By continuously monitoring file activity and scanning file content, you can verify that sensitive data remains in its intended location.
No enforcement of classification
When file classification is not automated, it is one less criteria by which the content and context of files can be analyzed. This can lead to incidents such as users accidentally emailing confidential files to external receivers and undetected attempts to exfiltrate sensitive data. By implementing a sturdy classification policy based on the sensitivity of file content, organizations can gain enhanced visibility into data usage by employees and even control it. They can quickly identify suspicious file transfers, and execute responses based on the classification label.
To avoid these pitfalls, organizations must implement holistic policies to locate sensitive data and prevent its exposure.
How to protect sensitive data from exposure
Sensitive data exposure prevention policies must consist of three primary steps:
1. Identifying sensitive data
Organizations must employ data discovery and classification tools to locate files containing critical data, analyze their level of sensitivity, and label them based on established classification policies.
2. Reducing the potential attack surface
Then, with a file analysis tool, they must examine the file’s attributes, metadata, and security permissions to locate and remediate risks such as incorrect permission propagation, excessively loose permissions, duplication, and storage of stale data.
3. Implementing endpoint DLP
Monitor how the files are accessed, modified, and transferred by employees and lock down endpoints to prevent data exfiltration.
Streamlining sensitive data exposure prevention
Enterprise data and roles evolve continuously. This means that all strategies to prevent the exposure of business-critical data should be continuous processes as well. This is where ManageEngine DataSecurity Plus can help. A unified data visibility and security solution, it can discover sensitive data, analyze and deduplicate file storage, spot security vulnerabilities, detect anomalous file activity, prevent data leaks, and much more. To learn more about how DataSecurity Plus works, schedule a demo with a solution expert.