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How to Protect Personally Identifiable Information: PII Security Best Practices

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From Social Security numbers to credit card details, companies handle a plethora of sensitive information crucial for identifying customers and managing employee records. While this data facilitates essential functions like order processing and payroll management, the stakes of its security are undeniably high. Only recently, a breach at an IT service provider, Infosys McCamish Systems, led to a data breach impacting Bank of America customers, leaving the personal information of at least 57,000 customers exposed. 

Given the immense costs associated with breaches, including damage to customer trust and potential legal battles, protecting personal information goes beyond simply complying with legal regulations; it's a cornerstone of ethical business practice. This article will explore the risks associated with handling PII, the best practices for PII security, and the necessary knowledge and tools for security professionals to maintain robust data protection measures.

Understanding the Risks: Protecting Personally Identifiable Information (PII)

PII encompasses any data that can be used to identify a specific individual, ranging from basic identifiers like names and addresses to more sensitive details such as Social Security numbers and biometric data.

Unfortunately, despite increased awareness and regulatory measures, PII remains under constant threat from various risks. Let's explore some of the most prominent dangers facing PII:

  • Cyberattacks and Data Breaches: Cybercriminals continually target organizations to gain unauthorized access to PII. Data breaches, whether through sophisticated hacking techniques or human error, can expose vast amounts of sensitive information, leading to identity theft, financial fraud, and reputational damage. 
  • Phishing and Social Engineering: Phishing attacks, often disguised as legitimate communications, aim to deceive individuals into divulging their PII. Over 2023, the US FTC (Federal Trade Commission) reported receiving over 2.6 million reports of consumer fraud, with the leading cause of fraud attributed to imposter scams. Social engineering tactics exploit human psychology, tricking victims into revealing confidential information through manipulation or coercion.
  • Insider Threats: Employees, contractors, or other trusted insiders pose a significant risk to PII security. Intentionally or unintentionally, insiders may access, misuse, or disclose sensitive data, resulting in breaches and compliance violations.
  • Third-Party Vulnerabilities: Many organizations rely on third-party vendors and service providers to handle PII. However, inadequate security practices or breaches within these external entities can compromise the confidentiality and integrity of shared information.
  • Emerging Technologies: The proliferation of new technologies such as the Internet of Things (IoT), artificial intelligence (AI), and cloud computing introduces additional risks to PII. While offering numerous benefits, these technologies also present new avenues for cyber threats and data exposure.

To mitigate these risks, organizations must implement robust security measures and adhere to regulatory standards such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA).

PII Security Best Practices

Safeguarding PII requires a systematic and comprehensive approach. Here are some PII protection best practices you can implement to ensure your organization’s PII is stored as securely as possible:

1. Locate All Types of PII in Your Data Repositories

Organizations must initiate PII protection by deploying advanced scanning tools and algorithms to systematically pinpoint all forms of PII within their data repositories, both in managed and unmanaged data stores or even SaaS vendors holding data. This proactive strategy not only boosts visibility and control over potential security vulnerabilities but also extends to managing the digital footprint effectively. By comprehensively locating and categorizing PII, organizations can gain valuable insights into their data landscape, enabling them to implement targeted security measures and minimize the risk of unauthorized access or data breaches.

2. Classify Discovered PII

Once identified, organizations should classify PII found in databases and warehouses based on sensitivity levels. This classification process involves differentiating between various levels of sensitivity attributed to different types of PII. For example, distinguishing between types such as Social Security numbers and biometric identifiers versus less sensitive information like business contact details. By implementing a comprehensive classification system, organizations can effectively prioritize their security measures, allocating resources and attention where it is most needed.

3. Manage PII That’s Not Needed

To mitigate risk exposure, organizations should adopt a strategy of minimizing the collection and retention of unnecessary PII. Regular reviews and evaluations of the necessity of retaining certain types of PII are essential. Implementing data minimization strategies, such as de-identification, pseudonymization, or anonymization, becomes crucial in limiting the scope of PII stored within organizational systems. Additionally, organizations should consider implementing retention policies to govern the lifespan of PII, including actions such as deleting outdated PII or applying retention policies based on criteria such as the time since the user's last login. By adopting these measures, organizations can effectively mitigate the risk of data breaches and uphold the privacy and security of sensitive information.

4. Implement Data Security

Organizations should implement comprehensive data security measures to protect PII and personal data from unauthorized access and data breaches. This can include the use of strategies and techniques such as:

Data Encryption

Encrypt PII both at rest and in transit to protect it from unauthorized access. Utilize strong encryption algorithms and secure key management practices to ensure the confidentiality and integrity of sensitive data. Implement encryption mechanisms at the application level, database level, and during data transmission to enhance overall data security.

Secure Storage

Adopt secure storage practices to safeguard PII from unauthorized access or data breaches. Prefer using application level encryption for your customer data, which means any unauthorized user accessing the data in the database won’t be able to decipher it. Utilize encrypted storage solutions and access controls to restrict permissions and ensure that only authorized users can access sensitive information. Employ robust authentication mechanisms, such as multi-factor authentication (MFA), to strengthen data access controls further.

Implement the Principle of Least Privilege (PoLP)

Follow the principle of least privilege to restrict access to PII based on users' roles and responsibilities within the organization. It emphasizes the practice of only granting users access to sensitive information on a need-to-know basis and to the minimal extent necessary. By adhering to this approach, organizations reduce potential avenues for data leaks, as access is restricted to those who genuinely require it to fulfill their duties. Regularly review and update access permissions to mitigate the risk of unauthorized data exposure. Normally, databases are configured to give full read-write access to many users; once compromised, all data can be stolen. Hence, it’s considered a bad practice.

Practice Identity & Access Management (IAM) & MFA

Implement comprehensive identity and access management policies to control user authentication and authorization. Utilize IAM solutions to manage user identities, enforce strong password policies, and monitor user activities for suspicious behavior. Enhance security measures with multi-factor authentication to add an extra layer of protection against unauthorized access. And normalize the requirement to rotate API keys and passwords at least once a year.

5. Implement Data Privacy

Organizations aiming to maintain data privacy standards must prioritize data minimization and protection techniques, such as:

Data Minimization: De-identification, Pseudonymization, and Anonymization

Reduce the risk associated with PII by applying data minimization techniques such as the following:

  • De-identification: De-identification involves (fully) removing or altering identifiable data to sever its association with individual identities. 
  • Pseudonymization: This technique substitutes personal identifiers with non-sensitive tokens (pseudonyms) within datasets. Therefore, the identifiers are still kept in the system but are harder to get access to.
  • Anonymization: Anonymization takes data minimization a step further by ensuring that data can never be traced back to specific individuals, thereby safeguarding privacy and bolstering overall data protection measures. For example, it can be achieved by de-identifying data.

Enforce a Data Usage Policy

Establish clear guidelines and policies governing the use of PII within your organization. Educate employees on proper data handling practices and enforce compliance with regulatory requirements. Implement access controls and auditing mechanisms to monitor and track data usage, ensuring adherence to established policies. For example, developers should not use debug logs in production that spill customer PII, which will eventually give access to more unauthorized personnel.

Cookie and Consent Management

Ensure compliance with privacy regulations, such as the GDPR, by implementing robust cookie and consent management solutions. Obtain explicit consent from users before collecting or processing their personal information through cookies. Provide transparent disclosures regarding data usage and offer users control over their privacy preferences. For example, if you want to use a customer’s phone number as a means for 2FA, it must have been collected for that purpose. Otherwise, you’re violating the use of her data.

Data Subject Access Requests (DSAR)

Facilitate data subject access requests by establishing streamlined processes for handling requests from individuals to access their personal data. Respond promptly to DSARs and provide individuals with transparent insights into how their PII is processed and stored. Maintain detailed records of DSARs and actions taken to demonstrate compliance with regulatory requirements.

Right To Be Forgotten (RTBF)

Respect individuals' rights to erasure by implementing procedures for honoring requests for the deletion of personal data. Ensure that PII is securely erased from all data repositories and backup systems in accordance with regulatory obligations. Maintain comprehensive records of data deletion activities to demonstrate compliance with RTBF requirements. Remember that in some cases, you’re still obliged to keep some data for tax and legal purposes. Consult your legal counsel to see what takes precedence before deleting data.

Maintain a Data Inventory

Maintain an up-to-date inventory of all PII collected, processed, and stored by your organization. Document the types of data collected, the purposes for which it is used, and the storage locations. Conduct regular audits and assessments to ensure the accuracy and completeness of the data inventory, enabling effective data governance and compliance management. This is needed either way in order to satisfy any data subject access rights.

Proactively Scan & Identify In-Code Data Leaks

Implement automated scanning tools to detect and mitigate in-code data leaks and vulnerabilities. Regular code reviews and penetration testing should be conducted to identify potential security gaps and vulnerabilities that could expose PII. Integrate security testing into the software development lifecycle to ensure that security measures are implemented from the outset.

6. Periodical Assessments

Implementing automated scanning tools and regular code assessments to detect and mitigate in-code data leaks and vulnerabilities is essential. While there are various forms of assessment required by regulatory boards, such as:

Privacy Impact Assessments (PIA)

Conduct privacy impact assessments to evaluate the potential privacy risks associated with new projects or initiatives. Assess the collection, use, and disclosure of PII to identify and mitigate privacy risks proactively. Document assessment findings and implement recommendations to ensure compliance with privacy regulations and protect individuals' privacy rights. This is not about security per se but more about the appropriate use of data rather than misusing or sharing it.

Data Protection Impact Assessment (DPIA)

Perform data protection impact assessments to assess the potential risks to individuals' rights and freedoms arising from data processing activities. These assessments are essential in order to understand risks and threats that can result from collecting data and processing and then how to reduce them proactively. Evaluate the necessity and proportionality of data processing operations and implement measures to mitigate identified risks. Incorporate DPIAs into the decision-making process to ensure that data processing activities comply with applicable data protection laws.

How to Protect PII and Other Sensitive Data with Piiano

Piiano offers comprehensive solutions designed to strengthen PII and personal data security and minimize data footprints. Through its solutions, Piiano Vault and Piiano Flows, Piiano provides users with the tools to track and secure their sensitive data. The Piiano Data Privacy Vault serves as a centralized hub for PII, granting organizations precise control and comprehensive oversight over sensitive data. Through advanced tokenization and encryption features, Piiano's PII Vault significantly reduces the copies of stored PII in databases, fostering a proactive approach to privacy from the early stages of development, enhancing data security, and promoting a privacy-centric company culture. 

In addition, PII Vault protects data from breaches, enforces strict access controls, and streamlines compliance with regulations such as the GDPR, CCPA, HIPAA, SOC2, and PCI-DSS, mitigating the risk of non-compliance penalties and legal ramifications. With its developer-centric approach, Piiano Vault offers a user-friendly interface and comprehensive documentation, facilitating seamless integration and implementation for developers. Additionally, organizations have the flexibility to choose between self-hosted deployment or Piiano's SaaS offering, tailoring Piiano Vault deployment to their infrastructure requirements and ensuring optimal performance and scalability as their business grows.

Able to operate in conjunction with Piiano Vault or independently, Piiano Flows is an advanced privacy code scanner that analyzes your source code to track sensitive data usage and detect data leaks or other data-related events before they reach production. By integrating Piiano Flows into the development process through CI/CD, organizations can shift data security left and protect PII directly from the code. This approach not only reduces the risk of data leaks but also saves time and resources by identifying and addressing privacy violations early in the development lifecycle. With Piiano Flows, organizations can ensure that their applications are scanned daily for privacy violations and receive daily or weekly notifications about relevant code changes that touch sensitive data and act immediately upon them.


Effectively safeguarding PII requires a proactive approach encompassing comprehensive security measures and adherence to data privacy regulations. By embracing PII security best practices, developers and security engineers can effectively mitigate privacy risks and shield sensitive data assets from unauthorized access, breaches, and misuse. Through the adoption of robust measures such as data encryption, secure storage protocols, and proactive assessments, organizations can significantly reduce the likelihood of data breaches and fortify their defenses against unauthorized access to sensitive information.

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It all begins with the cloud, where applications are accessible to everyone. Therefore, a user or an attacker makes no difference per se. Technically, encrypting all data at rest and in transit might seem like a comprehensive approach, but these methods are not enough anymore. For cloud hosted applications, data-at-rest encryption does not provide the coverage one might expect.

John Marcus

Senior Product Owner

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