08/23/2024 | News release | Distributed by Public on 08/23/2024 10:31
In today's digitized world, the heart of any organization's IT infrastructure is arguably its database systems. Databases host a wide range of information, from sensitive customer data to proprietary business intelligence - which makes them a top target for cyberattacks. As a database administrator (DBA), you need a solid grasp of database security to protect your organization's databases from downtime and data breaches. This article explains the key concepts, best practices, and tools you need to understand to get started on the right foot.
Database security involves measures, tools, and policies to protect databases from inappropriate user access, misuse, theft, or loss. This includes controlling who can access the database, securing the data within the database, and securing the data as it's moved or accessed. Effective database security standards protect an organization's valuable information assets, which in turn helps maintain customer trust and avoid the financial and reputational damages caused by data breaches.
However, organizations need to remember that measures designed to maximize data security often frustrate users and impede their productivity. Paradoxically, this can lead users to circumvent security measures - ultimately hurting security. For example, requiring passwords to be complex and frequently changed helps protect against account compromise but may also frustrate users, leading to unsafe practices like reusing passwords or writing them down. Organizations need to balance database security measures against the impact on the user experience to avoid these issues.
The core goals of database protection measures are to ensure the confidentiality, integrity and availability of sensitive information. Let's elaborate on each of the goals.
Confidentiality involves ensuring that only those authorized to access particular information can do so. Guarding against unauthorized disclosure, data breaches, and misuse of information is especially important for sensitive data such as personal information, financial details, and intellectual property. Maintaining data confidentiality is also vital for meeting legal and regulatory requirements, including laws like GDRP that explicitly protect the privacy rights of individuals. Violations of data confidentiality can lead to significant issues, including legal penalties, financial loss, and damage to an organization's reputation.
This refers to the accuracy, consistency, and reliability of data throughout its lifecycle. The goal is to ensure that the data is never inappropriately unaltered during storage, transfer, and retrieval, protecting against corruption, unauthorized access, and errors. Maintaining data integrity is crucial for the trustworthiness of data in decision-making as well as for compliance with regulations. Techniques to uphold data integrity include access controls, data validation, encryption, and regular audits.
Data needs to be readily accessible to authorized users when needed. Availability is critical to business continuity, decision-making, compliance with service level agreements (SLAs), and operational efficiency. Ensuring high data availability involves implementing systems and practices that mitigate data loss and downtime. This can include redundancy through backup systems and failover mechanisms, maintaining and monitoring network infrastructure, and adhering to best practices in disaster recovery planning.
Many separate threats can compromise the confidentiality, integrity and availability of data stored in database systems. Some of the most common are detailed below.
Let's look at each of them.
Any account that has been granted access rights to a database is a threat. These threats come in two types:
Deliberate threats typically include malicious insiders who intentionally misuse their access to steal, leak or damage data. Malicious insiders include not just the legitimate account owners but any adversary who compromises the account. They may be motivated by personal gain, such as selling sensitive information to competitors or revenge against the organization. Insider threats are particularly insidious because inappropriate actions by legitimate accounts can be hard to detect.
Software vulnerabilities are weaknesses in the design, implementation or configuration of database management software, which attackers can exploit to gain unauthorized access, extract sensitive data or disrupt database services. These vulnerabilities can arise from a variety of sources, as follows:
One common strategy to exploit software vulnerabilities is injection attacks. These attacks exploit vulnerabilities in a web application's software to send malicious code through unvalidated input, aiming to manipulate a database in unauthorized ways. While SQL injection targets traditional relational databases, NoSQL injection focuses on newer, schema-less databases like MongoDB, Couchbase, and Cassandra.
Another attack involves buffer overflow exploitation. When a program writes more data to a buffer (a temporary data storage area) than it can hold, the excess data can overwrite adjacent memory spaces, erasing important data or executable instructions. Adversaries can exploit buffer overflows to gain unauthorized access, corrupt data or even cause a system crash.
In a denial of service (DoS) attack, attackers flood the target system with an overwhelming amount of traffic or queries in order to disrupt the business. Specifically, these attacks can lead to slowed response times, transaction processing failures or complete system shutdowns. If the traffic originates from multiple sources, the attack is known as a distributed denial of service (DDoS) attack.
Adversaries can use malicious software to attack databases in multiple ways. There is malware that will encrypt database files and demand a ransom for the decryption key. Other malware will secretly monitor the database and transmit the information it collects back to the attacker. Self-replicating malicious code can corrupt database files or exploit vulnerabilities to distribute the malware further. And Trojans, or malware disguised as legitimate software, can open backdoors in security systems.
Attackers understand that backups often contain the same sensitive information as live databases but may be protected by weaker security measures. Consequently, they can target backups with the same attacks they use on live databases, including stealing data from backups and encrypting backups to deny access until a ransom is paid. Hackers may also try to destroy backup data to increase the impact of an attack on live systems by making recovery more difficult or impossible.
Several factors make database security management increasingly challenging for organizations today. They include:
The more data an organization stores, the larger its attack surface becomes. Existing security measures may not scale effectively to protect all the data adequately.
Organizations today often have a complex mixture of on-premises databases and cloud-based services. Each comes with its own set of security protocols and challenges, making implementing uniform access management and other security practices difficult.
New laws protecting data confidentiality, integrity, and availability continue to be introduced, and existing laws are often modified to require more robust protection measures. Organizations can struggle to achieve, maintain, and prove compliance.
Organizations can find it challenging to engage and retain professionals experienced in database security. As a result, current staff may become overburdened, which can lead to burnout and increase the likelihood of errors. In addition, organizations may be unable to stay up to date with the latest security technologies since skilled personnel are needed to implement and manage them.
Attacks on databases can result in a wide range of repercussions, including the following:
If an attacker or malicious insider steals sensitive information from an organization's databases, the damage can be severe. For example, theft of intellectual property (IP) can lead to loss of revenue and market share, and improper disclosure of upcoming products or services can jeopardize launch strategies and partnerships.
A database security breach can cause profound and lasting damage to the company's reputation. News of a breach can spread rapidly across social media, news outlets and online forums, leading consumers to question the reliability and integrity of the brand. Existing customers may choose to take their business elsewhere, wary of further risks to their personal information, and potential new customers might be dissuaded from engaging with the brand based on its poor security track record.
The loss or corruption of critical data in a breach can disrupt essential business processes, from customer relationship management to supply chain logistics. Moreover, in the aftermath of a data breach, affected systems may need to be taken offline for forensic analysis and remediation, causing downtime that impedes productivity and service delivery. These operational disruptions can lead to reduced sales, contract cancellations, and lost business opportunities, severely impacting revenue streams.
Repairing the damage from a data breach involves a complex web of direct and indirect costs beyond compliance fines. They can include legal fees for settling lawsuits, expenses for engaging consultants on how to secure databases better to prevent future incidents, and investments in new security solutions and processes.
Organizations need to implement robust database security controls to overcome modern data security challenges and avoid costly breaches and downtime. These controls can be grouped into three categories:
Administrative controls are procedures and policies designed to mitigate risks associated with human error. Examples including role-based access control (RBAC) to enforce least privilege, regular review of accounts and their access privileges, and change management procedures.
Preventive controls are measures designed to stop unauthorized actions before they occur. Common examples include firewalls, intrusion detection and intrusion prevention systems (IDS/IPS), VPNs, and strong authentication mechanisms.
Detective controls are designed to spot threats in progress and alert administrators so they can respond in time to limit the damage. Database monitoring tools can analyze login attempts, data access activity and administrative actions in real time to spot anomalies and other suspicious activity. Some solutions leverage machine learning (ML) and artificial intelligence (AI) to identify patterns of behavior that deviate from the norm and integrate with security information and event management (SIEM) systems to provide a more comprehensive view of activity across the IT infrastructure.
The following best practices are essential for ensuring database security:
The first step in securing databases is understanding the threats they face. Cyber threats are constantly evolving, making it crucial for organizations to stay informed about the latest security risks. Common threats to databases include SQL injection attacks, unauthorized access, malware, and data leaks. By understanding these threats, organizations can better prepare their defenses.
Security policies are formal documents that outline an organization's approach to security, defining what is protected, why it is protected and who is responsible for protecting it. As you build your data protection policies, keep the following best practices in mind:
Database security should be viewed not as merely a technical challenge or compliance requirement, but as an integral component for helping the business to achieve its goals, such as expanding into new markets, launching new products, or enhancing the customer experience. For instance, having a clear understanding of business objectives helps determine which data assets are most critical and thus require higher levels of protection. It can also help the organization highlight its commitment to security in marketing and sales efforts to attract new customers and retain existing ones.
Database security policies need to be aligned with applicable regulatory standards that dictate how data should be managed and protected. Since regulations change and new requirements are introduced, organizations need to regularly review and update their data security policy to ensure ongoing compliance.
Clearly define the roles and responsibilities of different parties involved in ensuring the security of database systems. Stakeholders can include:
Organizations need to ensure that only the right users can access databases and that they can perform actions only in line with their roles and necessities. The following best practices are essential for implementing strong access control:
Let's have a look at each.
At minimum, require strong, unique passwords. For stronger security, implement multifactor authentication (MFA), which requires two or more authentication methods, such as a password plus a biometric identifier or code sent to a user's device.
Each user should be granted the minimum permissions needed to perform their duties, and accounts of former employees and inactive accounts should be promptly deactivated or deleted. This approach limits the damage that a user can do accidentally or deliberately, as well as the reach of a threat actor who compromises an account. For even more robust protection, consider replacing highly privileged accounts with just-in-time access rights for specific tasks using a modern privileged access management (PAM) solution.
Encryption tools used to convert plaintext into a scrambled format, known as ciphertext, using an algorithm and an encryption key. Tokenization replaces sensitive data elements with non-sensitive substitutes, known as tokens, which have no exploitable value. The original data is stored in a secure token vault, and the relationship between the data and its token is maintained for processing or transaction purposes.
Encrypted data is unreadable even if it is exfiltrated by adversaries. Options include column-level encryption, which offers granular encryption of specific data within a database column, and application-level encryption, where encryption and decryption operations occur within the application rather than the database.
Transparent Data Encryption (TDE) is often used to encrypt data at rest, while encryption of data in transit is typically achieved using protocols like SSL (Secure Sockets Layer) or TLS (Transport Layer Security).
Regularly check for outdated software, misconfigurations and weak access controls. Furthermore, conduct penetration testing to simulate cyberattacks and assess the effectiveness of existing security measures.
Use database activity monitoring solutions to detect and alert on suspicious activity in real time, enabling swift response to potential threats. In particular, closely audit successful logins, failed login attempts, attempts to access privileged functions, and attempts to modify, delete or exfiltrate data.
Provide training to all users on topics such as recognizing phishing attempts, securing personal devices used for work, and following proper procedures for accessing and handling data. Tailor the training to the needs of different groups of users, repeat it on a regular basis, and consider performing tests such as simulated phishing campaigns to measure effectiveness.
Software vulnerabilities are a common attack vector for cybercriminals, so applying security patches promptly is crucial for protecting databases against known attacks. The patch management process should be automated as much as possible and include regular checks for updates from all software vendors.
A comprehensive incident response plan should outline the steps to be taken in the event of a security breach, including containment, eradication, recovery and communication strategies. Regularly testing and updating the incident response plan is essential to ensure its effectiveness.
Ensure that valuable and sensitive data backups are securely stored and can be recovered in event of data loss, corruption or other disaster. The 3-2-1 backup rule recommends keeping at least three total copies of your data, two of which are local but on different devices and one of which is off site.
Containerization of databases using technologies like Docker and Kubernetes offers opportunities for more granular security controls and isolation.
Ensure that security considerations are addressed early in the development lifecycle of database applications and environments.
Organizations have a wide variety of database security solutions to choose from. Below are some of the top options for each critical function.
Database security today requires a comprehensive approach. Key database security measures include identifying critical data, using encryption for data both at rest and in transit, implementing strong access control measures like RBAC and MFA, and monitoring for suspicious database activity. It's also vital to conduct regular vulnerability assessments, penetration tests and user account audits, as well as to have a robust backup and disaster recovery plan in place. These measures are essential for both database security and compliance with regulations like GDPR, HIPAA and PCI-DSS, which have specific requirements for data protection and privacy.
Database security is not just about deploying the right tools and technologies. It's also about establishing strong policies, procedures and awareness among employees to protect against human errors, which are often the weakest links in database security.
Data security refers to the protective measures and protocols put in place to secure data from unauthorized access, data breaches, or any form of malicious activities aimed at compromising data integrity, confidentiality, and availability. This includes a wide range of processes and strategies designed to protect digital information, prevent data loss, and ensure that data remains accessible only to those with proper authorization.
Secure data is information safeguarded against unauthorized access, modification, and destruction. It ensures confidentiality by being accessible only to authorized users, maintains integrity by being accurate and consistent, and guarantees availability so that it is accessible when needed. Secure data also verifies the authenticity of users and systems interacting with it and ensures that actions and transactions are traceable, preventing denial of actions.
Data security is important for protecting sensitive information, maintaining privacy, complying with laws and regulations, fostering trust, preventing financial losses, ensuring business continuity, and safeguarding national security.
To secure a database, implement strong access controls, use encryption, keep software updated, regularly back up data, monitor access and changes, secure the underlying system, apply the principle of least privilege, secure physical access, and conduct regular security assessments.
To store sensitive data securely in a database, use encryption methods like AES-256 for data at rest and SSL/TLS for data in transit. Implement access controls, such as Role-Based Access Control (RBAC), and ensure users have the minimum necessary permissions. Data masking and tokenization can be used to obfuscate and replace sensitive data. Additionally, regular monitoring and logging of database activities, periodic security audits, and compliance checks are essential.