Database Security Overview: Challenges, Tools & Best Practices

Overview

Historically, securing a database was a relatively straightforward affair. The prevailing practice was to handcraft the database and place it within a Virtual Private Cloud (VPC), with only a select few DBAs requiring legitimate access. This strategic isolation minimized the risk of insider threats and account compromises. These databases typically only interacted with home-grown, monolith production applications, which were themselves shielded by various application security tools, with absolutely minimal external interactions.

Database deployment and access has undergone a profound transformation. They are stamped out as part of a CI/CD pipeline, often in tandem with corresponding microservices. Large portions of the engineering and SRE team want to be able to access the database. Additionally, databases are often indirectly connected to a myriad of third party services which run in the public cloud. These practices not only introduce new challenges but also underscores the critical importance of implementing robust database security measures that go beyond just “locking down the network”. 

This white paper aims to provide a buzz-word free framework for database security, shedding light on common threats and the methodologies to fortify against them, and shares best practices on how to manage the available controls.

Defining the Scope of Database Security

What is Database Security? Historically, database security was about securing the host server that databases are deployed on using traditional IT and network security tools. This security model was built on the operating assumption of there being a handful of databases being accessed by a few specialized users. However, as organizations became data driven, that assumption changed:

• Exponential Increase in Data Usage: As organizations embraced data-driven decision-making, the sheer volume and diversity of data usage soared. Database security assumptions had to adapt to support not only increased access but also varied types of users, ranging from data analysts to business executives, each with distinct needs and privileges.
• Rise of Cloud-Based Applications and Microservices: The proliferation of cloud-based applications and microservices transformed the traditional database security paradigm. Security considerations now extend beyond the confines of on-premises infrastructure, demanding a shift towards cloud-native security measures to protect databases accessed by distributed and interconnected services.
• Transition to SaaS Model: The movement of databases, especially data warehouses, to a SaaS model introduced a new layer of complexity. Database security assumptions evolved to accommodate shared responsibility models, where both the SaaS provider and the organization play critical roles in securing data, demanding a more nuanced approach to access controls and data protection.
• Dynamic Scalability Challenges: The dynamic nature of data-driven environments requires scalable solutions. Database security assumptions must now account for the elastic nature of cloud resources and adapt to fluctuating workloads, necessitating robust mechanisms for authentication, authorization, and encryption that can seamlessly scale with the organization’s needs.
• Focus on Data Privacy and Compliance: With the intensification of data regulations, database security assumptions now place a heightened emphasis on data privacy and compliance. As more databases are accessed and manipulated to support business operations, organizations must ensure adherence to regulatory frameworks, influencing the design and implementation of security measures.

These changes have led to an increased emphasis on database security and protecting databases from breach.

Data Security vs Database Security

Data security is an all-encompassing concept that stretches across the realms of IT, infrastructure, products, networks, and devices. It is a holistic approach dedicated to safeguarding data integrity, confidentiality, and accessibility throughout its lifecycle, irrespective of the systems or services involved.

Database security, while primarily residing within the domains of infrastructure and product security, ensures the protection of data stored within databases. This includes measures such as access controls, encryption, and auditing to fortify against unauthorized access or malicious manipulation.

Even within the domains of infrastructure and product security, data security spans the following:

• Databases:
  • Structured storage of organized data.
  • Designed for efficient querying and transaction processing.
  • Well-suited for operational applications and transactional workloads.
• Data Warehouses:
  • Centralized repository for large-scale structured data consolidation.
  • Optimized for complex queries and analytics.
  • Supports reporting and business intelligence activities.
• Data Lakes:
  • Storage for diverse and raw data types, both structured and unstructured.
  • Provides a flexible and scalable storage infrastructure.
  • Emphasizes on storing data in its raw form for future flexibility.
• Data Products:
  • Outputs of data analysis, machine learning, or analytics processes.
  • Can take the form of reports, visualizations, predictions, or recommendations.
  • Often involves packaging analytical results for consumption by end-users or other systems.

This white paper focuses on database security, but the concepts can be extended to data warehouses as well.

Drivers for Investing in Database Security

• Data Protection: Safeguarding customer data and proprietary information fundamental to maintaining a competitive edge in the market.
• Regulatory Compliance: There is an increase in mandates for data security and privacy measures, and non-compliance can lead to substantial fines and legal penalties.
• Customer Trust and Reputation: A security breach erodes customer trust, impacting brand reputation and customer loyalty.
• Operational Continuity: Database security investments ensure uninterrupted business operations by mitigating the risk of data breaches that could disrupt essential functions.

Goals and Holes of Database Security

Database Security Best Practice

Implementing a robust database security strategy encompasses a range of controls that address various aspects of database protection.

• Auditing & Monitoring: Continuous auditing and monitoring are crucial for detecting and responding to potential security breaches. Implement tools and procedures to track database access, activity logs, and system events. Regularly review these logs to identify anomalies or suspicious patterns that may indicate unauthorized access or attempted attacks.
• Access Control: Access control serves as the gatekeeper of database security, ensuring that only authorized users with legitimate needs can access sensitive data. This involves implementing strong authentication mechanisms, such as multi-factor authentication, to prevent unauthorized access.
• Data Masking: Data masking techniques protect sensitive information by obscuring or replacing original data with non-sensitive placeholders. This safeguards sensitive data while enabling its use for testing, training, or development purposes without compromising confidentiality.
• Data Redaction: Data redaction removes sensitive information from databases or from query results, preventing its exposure in the event of a breach. This technique is particularly useful for protecting Personally Identifiable Information (PII) and other highly sensitive data.
• Vulnerability Management and Patching: Databases, like any software system, are susceptible to vulnerabilities. Regularly scan databases for vulnerabilities and promptly apply security patches to address these weaknesses. This proactive approach helps mitigate potential attack vectors and keep databases secure.
• Least Privilege: The principle of least privilege ensures that users and applications are granted only the minimum level of access necessary to perform their designated tasks. This minimizes the potential damage that could result from malicious insiders or compromised accounts.

By implementing these comprehensive controls, organizations can significantly enhance database security, protect sensitive information, maintain data integrity, and ensure the continued availability of critical systems.

While encryption is a cornerstone of database security, data breaches invariably happen because of unauthorized access but using valid credentials, which encryption doesn’t protect from. Field-level encryption is useful but its implementation is often riddled with challenges. It often requires changes to applications and complex user workflows, and any mistakes can result in data loss.

Challenges with Database Security

Modern infrastructure is dynamic and elastic, with resources scaling up or down based on demand. This dynamism poses challenges in maintaining a consistent security posture. Traditional security controls often struggle to adapt to these fluctuations, however when it comes to databases, the challenges are often deeper than merely operational:

• Lack of integration with IAM tools: Lack of seamless integration with Identity and Access Management (IAM) tools results in fragmented and insecure access controls. This not only makes access management arduous but also leaves databases vulnerable to unauthorized access.
• Service account proliferation: While service accounts are indispensable for database applications, managing and securing these accounts becomes increasingly complex, opening avenues for potential misconfigurations, misuse, abuse and exploitation.
• Complexity of granular access control: In complex databases, where tables may store diverse types of sensitive information, ensuring that users or applications only access the data they legitimately need becomes intricate, leading to over-permissioned users and increased exposure.
• Insufficient Auditing and Monitoring: Challenges arise when attempting to implement comprehensive monitoring across diverse database environments. Inadequate logging, coupled with the sheer volume of events generated, can obscure critical security incidents. 

Database Security Tools

There are several types of tools and products available on the market, with several emerging categories that are quickly becoming popular. This section aims to provide a quick overview of those categories and how they can be used:

Database Activity Monitoring

Database Activity Monitoring (DAM) is a security solution dedicated to the continuous surveillance and analysis of database activities in real-time. It monitors all user actions, queries, and transactions within the database infrastructure, flagging potential threats, unauthorized access, and anomalous behaviors. DAM solutions play a critical role in maintaining data integrity, ensuring compliance with industry regulations, and fortifying defenses against evolving cyber threats.

At its core, a DAM provides the following key features

1. Monitor and log all database activity, at the field level
2. Allow logs to be stored externally for assurance 
3. Provide consistent monitoring and logging
4. Help respond to threats and unauthorized access

Privileged Access Management

Operating as a specialized subset of identity and access management, Privileged Access Management (PAM) is dedicated to overseeing and controlling privileged accounts, such as those belonging to administrators, executives, and other high-impact roles. It emphasizes the need for strict access controls, robust authentication mechanisms, and comprehensive auditing to mitigate the risks associated with unauthorized access and potential misuse of privileged credentials. PAM solutions have historically been designed for ssh-based server access but increasingly PAM solutions purpose-built for databases have become popular. 

PAM products have the following key features

1. Granular privilege assignment
2. Just-In-Time access control
3. Robust authentication measures
4. Access reporting and monitoring

Data Security Posture Management

Data Security Posture Management (DSPM) products are software solutions that help organizations protect their data by providing visibility into where sensitive data is stored, who has access to it, and how it is being used. DSPM products also help organizations identify and remediate security risks, comply with data privacy regulations, and ensure that their data is protected from unauthorized access, modification, or deletion. While DSPM can apply to any service, databases and data warehouses are generally a key focus area for them.

Some of the key DSPM features are

1. Database discovery
2. Data discovery and classification
3. Access and privilege reporting
4. Request monitoring and logging

Data Access Governance

Data Access Governance (DAG) products are software solutions that help organizations manage and control access to their data. They provide a centralized platform for managing user access permissions, tracking data usage, and enforcing data security policies. The concept is very broadly applicable, but often focused on data products that connect to data warehouses and data lakes for reporting.

Common DAG features include

1. Data discovery and classification
2. Policies for granular authorization
3. Data masking and redaction
4. Request monitoring and logging