In the world of DevOps, sensitive data is any information that, if revealed, might hurt a company or its clients. To that end, all the components of a DevOps environment, including source code, configuration files, databases, user passwords, API keys, or logs, classify as sensitive information. In fact, IBM’s 2022 Cost of Data Breach report stated that the average data breach cost increased to USD 9.44 million in 2022.
Secrets management, which involves safely storing and maintaining sensitive data, including passwords, API keys, certificates, and other private information, is essential to DevOps security. Having robust secrets management is crucial as it helps safeguard sensitive data from unauthorized access, reduce the risk of data breaches, and guarantee adherence to security standards and legislation. However, according to a report from IBM, 55% of organizations lack the visibility to access applications and assets across security and IT teams.
This article discusses the challenges, areas of focus, and best practices for managing sensitive data in DevOps environment
Challenges while managing sensitive data
With the increasing adoption of DevOps, developers are working with copies of the production database that contain customer data. Consequently, they are bound to have risk areas that can lead to a data breach. On paper, the need for data security is imminent. However, organizations face several challenges while handling data within a DevOps environment.
- Protecting data throughout the pipeline – The DevOps environment is complex and dynamic, involving multiple teams, tools, and processes. Ensuring that sensitive data is protected throughout the DevOps pipeline can be challenging.
- Lack of automation – Manual management of sensitive data in a DevOps environment can be significant, making it challenging to manage increases the risk of human error and security breaches.
- Absence of restricted access management – Risk of unauthorized access and data breaches while sharing sensitive data between different teams and tools
- Regulatory demands – Compliance with various security standards and regulations, such as HIPAA, PCI-DSS, and GDPR, increases the complexity of managing secrets and sensitive data in a DevOps environment.
Steps to follow while protecting sensitive data
Being a collaborative process, protecting data inside a DevOps environment requires focus on four different aspects – where people can access data, data sensitivity, purpose and user access, and performance monitoring.
While discussing managing data, it is important to understand where it resides. The primary reason data becomes vulnerable is not having a clear idea of where sensitive data is stored inside the cloud environments. Failure to have a record of data exposes the organization to various data privacy risks and cyberattacks.
After understanding where the data resides, the next focus should be classification. This is an important step in managing sensitive data as it is a prerequisite in access management, data masking, and securing sensitive and secretive data.
The third step is data protection. This starts from granting data access based on the user to masking data based on sensitivity. Businesses must identify each team’s role and the data access needed to perform their tasks.
Finally, managing data is an ongoing task. Organizations must perform database monitoring continuously and make necessary changes to their security plan to improve their security position. In case of a breach, businesses should have proper backup plans and make amends to the existing ones to save the system from further damage.
8 best practices for managing sensitive data in a DevOps environment
Although DevOps offers developers the freedom to work, it also is susceptible to security concerns. To that end, organizations must take a DevSecOps approach by offering best practices training to ensure teams can secure their environment and the data within. Here are a few best practices for managing data and secrets.
- Classify data – Before any sensitive data is processed or stored, define a policy that classifies data based on its level of sensitivity. This will help ensure appropriate security measures are applied to protect sensitive data.
- Encrypt data – Use encryption to protect sensitive data in transit and at rest. This will help to prevent unauthorized access to sensitive data, even if the data is intercepted.
- Deploy secrets management tools – Secrets management tools allow users to securely store and manage sensitive data, such as passwords and API keys, reduce the chance of accidental exposure of sensitive data, and ensure access is limited to authorized users.
- Install access controls – Implement access controls to restrict access to sensitive data on a need-to-know basis to prevent unauthorized access and ensure that only authorized users can access sensitive data.
- Create data logs – Implement logging and monitoring to track access to sensitive data and detect unauthorized access. This will help to identify any security incidents and take appropriate action to prevent data breaches.
- Automate testing – Use automated testing and deployment to reduce the risk of human error and ensure that sensitive data is protected throughout the DevOps process.
- Security assessments – Conduct regular security assessments to identify any vulnerabilities or gaps in security controls. This will help to ensure that sensitive data is protected against new and evolving threats.
- Secret injections – Use secret injection to inject sensitive data into applications and containers at runtime securely. This will help to prevent sensitive data from being exposed in logs or other unsecured areas.
Data privacy and protection are now essential requirements for organizations working in a DevOps environment. Organizations can control the breaches by identifying and classifying data, masking sensitive data appropriately, and monitoring all the databases. With the advent of technology, automating configuration management and access control also helps the DevOps environment to a large extent.