Discovery tools for cardholder data (CHD) are crucial for pinpointing unprotected sensitive data within your systems. Without knowing what sensitive data you possess, where it’s located, its importance to your business, and who has access, you can’t effectively protect it. Data breaches often stem from unintentional processing of confidential information. Accidental exposure, modification, or loss of sensitive data can lead to significant financial, legal, and reputational damage for any organization.
Sensitive data encompasses credit card numbers, Personally Identifiable Information (PII), Social Security Numbers (SSNs), state ID numbers, biometric data, medical records (PHI), passwords, digital signatures, and trade secrets.
See Also: How can you make unreadable stored PAN information?
In today’s digital landscape, safeguarding confidential information from theft and vulnerabilities is more complex than simple physical security. Protecting sensitive data has become increasingly challenging, especially with the widespread adoption of cloud storage.
However, by prioritizing data protection standards and understanding your data landscape, you can prevent sensitive information from falling into the wrong hands and becoming vulnerable to theft or leakage.
Managing and controlling sensitive data within a single, centralized database is relatively straightforward. However, the reality is that data constantly circulates throughout organizations – in HR databases, business analytics, testing environments, and decision support systems. This data proliferation complicates data protection efforts. Furthermore, cybercriminals often target easily accessible points like production servers or POS terminals.
See Also: How DLP Helps with PCI DSS Compliance
Many businesses assume they have a clear picture of their data environment, but often lack visibility into databases and other network locations. Software developers and IT administrators might believe that credit card details aren’t stored in their systems. Companies often accept these assurances and proceed with PCI compliance efforts based on incomplete information.
Imagine a scenario where your company develops an application designed to avoid capturing sensitive data. However, if the application is accidentally run in debug mode, it could inadvertently capture sensitive information. Simpler scenarios, like an employee innocently emailing sensitive data to a colleague, also pose risks. The rise of remote work further amplifies these vulnerabilities.
See Also: How Can I Protect Stored Payment Cardholder Data?
Voice recordings, especially in BPOs, banks, and insurance companies, often contain sensitive data when scanning voice interactions. Similarly, image files (.jpg, .gif, .png, .bmp, etc.) can unknowingly harbor sensitive data within your environment.
By continuously monitoring activities and implementing robust data discovery systems, businesses can effectively prevent these data breaches.
What is PCI DSS Card Data Discovery and What Data Does it Search For?
Card data discovery is a systematic process of scanning, identifying, and analyzing sensitive cardholder data, confidential information, proprietary data, and Personally Identifiable Information (PII). Card data typically includes the Primary Account Number (PAN), Service Code, Magnetic Stripe Data, Sensitive Authentication Data (SAD), Card Verification Value (CVV), and Personal Identification Number (PIN).
See Also: PCI DSS Data Classification Requirements
The purpose of card data discovery within the Cardholder Data Environment (CDE) is to assess the effectiveness of security controls protecting the confidentiality, integrity, and availability of this sensitive data. Data found on file systems, standard drives, databases, and removable media within the CDE is then either adequately secured or securely deleted based on its necessity and retention policies.
PCI DSS Requirements for Credit Card Scanning Tools
PCI DSS compliance has strict regulations against storing unnecessary or unauthorized cardholder data within systems. Identifying and eliminating this inappropriate data can be challenging, as it often resides in obscure systems or deep within folder structures.
See Also: Parts of a Debit or Credit Card and How They Work
Organizations utilize Credit Card Scanning Tools to analyze workstations and servers, including memory storage in retail POS systems, to ensure credit card information is not being stored insecurely.
Employing a robust credit card scanning tool that thoroughly examines file systems and databases for card data is the most effective way to guarantee that no unauthorized data is circulating within your environment.
Studies consistently highlight the critical role of proactively identifying and securing unencrypted credit card data in protecting customer payment information.
Common risk scenarios to be aware of include:
- Payment gateways that improperly configured might inadvertently dump card data into text or XML files when sending/receiving encrypted information.
- Payment data stored insecurely on desktops, cloud storage services like iCloud or Google Drive.
- Smartphones and tablets, due to cloud synchronization, can host and synchronize payment information outside the controlled corporate environment.
- Email remains a surprisingly frequent source of discovered card data across various endpoints.
Prioritizing credit card scanning tools is a proactive step towards strengthening customer data protection and preventing your business from becoming the next data breach headline.
See Also: What do credit card numbers mean?
Card data on personal devices like smartphones, tablets, and laptops (BYOD) should not be overlooked. Credit card data discovery is a comprehensive undertaking, as undiscovered cardholder data poses a significant risk to PCI compliance and exposes your organization to vulnerabilities. Is this a risk worth taking?
Credit card scanning tools are vital not only at the initial stages of a PCI DSS program to ensure security and compliance, but also for ongoing maintenance of compliance.
PCI DSS mandates regular assessment of the scope to ensure its accuracy. Specifically, PCI DSS Requirement 3.1 requires the discovery of unencrypted card data. Therefore, understanding the best approach for conducting card data discovery is paramount for businesses.
Card data discovery should be performed at least annually. Even with documented policies stating that no cardholder data is stored, accidental storage can still occur. Credit card information might be inadvertently left in documents predating PCI DSS compliance efforts or due to violations of established card handling procedures.
See Also: What are the PCI DSS Data Retention and Disposal Requirements?
One of the most significant operational threats today is data stored in unrecognized locations. Accidental processing of card data is often a precursor to a data breach. To mitigate this risk, organizations must securely manage and remove cardholder data that exceeds retention periods, ideally every three months.
When undertaking PCI DSS card data discovery and scanning, consider these five key factors:
- Enterprise-wide Scope: Card data discovery should encompass the entire organization, not just the defined PCI DSS scope or Card Data Environment (CDE). You’re likely to find card data in unexpected places.
- Diverse Data Platforms: Thoroughly scan all systems, databases, networks, and file systems. Relying solely on Data Loss Prevention (DLP) software can be insufficient, as DLPs may not support all databases, operating systems, cloud environments, voice platforms, and mail servers. This can leave sensitive data locations undiscovered.
- Agentless vs. Agent-based Tools: Agent-based tools might be suitable for smaller networks (under 100 systems). However, agentless tools can be more efficient for larger networks, avoiding the time-consuming process of accessing and scanning each file individually. Agent-based tools may be best run during periods of low network usage.
- Varied Data Formats: Data can be stored in any file type, including temporary files and RAM dumps. Card data discovery efforts must account for all potential data storage formats.
- Managing False Positives: Accuracy is critical in data discovery. Data validation is essential for correct classification, which informs protection and compliance efforts. However, results need continuous monitoring, verification, and refinement to minimize false positives and ensure accuracy over time.
The initial card data discovery process should include a comprehensive review of the network infrastructure, data flow diagrams, and known Cardholder Data (CHD) locations. Furthermore, in-depth interviews with stakeholders involved in handling cardholder data storage, processing, and transmission are essential. This thorough preparation will ensure an accurate understanding of the current data landscape and scope.
Numerous licensed and open-source tools are available to scan servers, networks, and databases for cardholder data. Let’s explore some of these options.
Licensed Credit Card Scanning Tools for Enterprise Environments
Advanced, licensed credit card scanning tools are designed to effectively search for PANs across complex, heterogeneous environments. The best tool for your organization will depend on your specific environment and the findings of your scoping exercise.
Licensed tools often provide comprehensive features and dedicated support, making them suitable for larger organizations with complex IT infrastructures. Examples of licensed card discovery tools that can aid in PCI DSS compliance include Nessus, Ground Labs Enterprise Recon, Security Metrics PANScan, and Controlcase CDD.
Nessus, a widely recognized network vulnerability scanner, offers a Windows File Content Compatibility Check plugin (plugin ID #24760) specifically designed for Windows systems to identify specific data types. This alt text describes the Nessus interface and its function as a vulnerability scanner, incorporating relevant keywords for SEO.
Nessus also provides pre-built audit files for common types of sensitive data, including credit card numbers, social security numbers, and driver’s license numbers. These audit files often align with state-level breach reporting requirements.
By providing file system access credentials, Nessus can identify systems that fail to meet PCI compliance standards. Nessus can be configured to pinpoint data locations and mask discovered information, preventing unintended data exposure. Scanning an entire Windows system can be time-consuming, so consider segmenting searches by network areas.
Enterprise Recon from Ground Labs is a data discovery and compliance software solution enabling organizations to locate and remediate sensitive data across diverse platforms. The alt text focuses on the Enterprise Recon dashboard and its function in data discovery and compliance, utilizing keywords relevant to SEO.
Enterprise Recon natively supports sensitive data discovery on a wide range of operating systems, including Windows, macOS, Linux, FreeBSD, Solaris, HP-UX, and IBM AIX.
Enterprise Recon offers both agent-based and agentless deployment options, providing flexibility for different network environments. Its remote scanning capabilities extend to virtually all stored network data, including hosts using EBCDIC IBM systems.
Card Recon, also from Ground Labs, is specifically designed to scan files, memory, and even deleted areas on workstations and file servers. It analyzes hundreds of file types to accurately identify credit card numbers from major payment card brands. This alt text describes the Card Recon scanning process and its focus on credit card number identification, incorporating keywords for search engine optimization.
Card Recon is capable of detecting credit card information stored in various formats, including office documents, email clients, and nested zip files.
Security Metrics PANScan is designed to locate unencrypted payment card data on your computer systems. This allows for the secure deletion or encryption of any sensitive data discovered. PANScan identifies Primary Account Numbers (PANs) and magnetic stripe track data within computer systems, hard drives, and connected storage devices. The alt text highlights the Security Metrics PANScan interface and its purpose in finding unencrypted payment card data for security, utilizing relevant keywords for SEO purposes.
ControlCase Card Data Discovery (CDD) software is a tool for scanning file systems, including those within Office 365, for unencrypted sensitive data. It can also scan for card data in most proprietary and open-source databases, computers, and drives. The alt text describes the ControlCase Data Discovery dashboard and its function in scanning for unencrypted sensitive data, incorporating relevant SEO keywords.
CDD is known for its fast scanning capabilities and minimal resource utilization. It typically operates without requiring plugins or tools on scanned machines. CDD helps identify PAN, track data, PIN, CVV, and other unencrypted sensitive data that may be unintentionally stored within your network.
Open Source Credit Card Scanning Tools for Basic Assessments
Open-source tools like Ccsrch, Panhunt, Pantastic, and PANBuster offer cost-effective options for PAN searching, particularly in simpler, smaller environments. Some open-source tools can even run locally on the device being scanned.
However, open-source credit card scanning tools often produce a higher rate of false positives compared to licensed tools. They typically work with flat files and may not be able to query databases directly. Despite these limitations, they can be a valuable starting point for initial PAN screening and discovery. Keep in mind that analyzing scan results, filtering out false positives, and remediating confirmed data storage issues can be more demanding with open-source options.
PANhunt is a fast, Python-based tool distributed as a standalone executable, making it portable and runnable via USB. It uses regular expressions to search for card data within documents and email files. Panhunt can scan Word documents, TXT files, Excel spreadsheets, PST files, and XML files for Visa, MasterCard, and American Express card numbers.
PANhunt also supports recursive searching within ZIP files. It generates a report listing identified, masked PANs. While system files may generate false positives, you can exclude Windows system directories by default to reduce noise. Panhunt effectively searches text files using regular expressions to match various credit card patterns.
CCSRCH is a cross-platform credit card (PAN) file system search tool designed for security assessments. It operates on Windows and UNIX-based operating systems, searching for and identifying unencrypted credit card numbers (PANs). CCSRCH also pinpoints the location of PAN data within files and records MAC timestamps for analysis.
Pantastic is a script designed to scan your computer for credit card PANs. It includes configuration options to ignore specific Issuer Identification Numbers (IINs), master identifiers, card numbers, file types, and deprecated issuers, allowing for customization and false positive reduction.
The script evaluates and classifies card numbers in various formats, from 12 to 19 digits, using Luhn algorithm checks and IIN determination. Pantastic employs different methods to help detect and minimize false positives, improving the accuracy of its results.
PANBuster is a command-line tool for identifying PANs and track data. It supports Windows, Linux, and iOS systems. PANBuster can identify card brands like VISA, MasterCard, American Express, JCB, Discover, and China UnionPay within cache or files. It can parse compressed files in memory and detect PAN data within MySQL, MSSQL backup, PostgreSQL, and Oracle dump files, offering broad format support.
CardScan4Linux is a lightweight script specifically for Linux systems, designed to locally scan for credit/debit card data within stored files. It is written to be lightweight and does not require any external Python libraries, making it easily deployable and usable.
Choosing the Best Credit Card Scanning Tool for PCI Compliance
When selecting a credit card scanning tool for PCI DSS compliance and card data discovery, consider these essential criteria:
Versatile Format and Source Support: The ideal tool should be adaptable enough to identify data in diverse formats, including audio, Excel files, ZIP archives, text documents, PDF files, and images. It should also be capable of scanning various systems, such as Windows servers, IBM AIX servers, Oracle and SQL Server databases, MySQL databases, Solaris servers, and Linux distributions (Ubuntu, CentOS).
Remediation Capabilities: The tool should not only locate card data but also facilitate remediation. It should be able to identify non-compliant data and offer options to mask, truncate, or securely delete unencrypted payment card data found in network systems, hard drives, databases, and emails. Furthermore, the tool should generate reports suitable for PCI DSS compliance documentation.
To maximize the effectiveness of your credit card scanning efforts, remember these best practices:
1. Understand Your Data Scope and Files:
Knowing your data landscape is crucial.
- Maintain an inventory of the types of confidential information your organization stores.
- Identify the servers and storage devices that typically house these types of files.
2. Consider Data Retention Requirements:
Before storing any file containing sensitive data, evaluate its necessity.
- Does saving the file serve a legitimate business purpose?
- Are there any contractual or legal obligations to retain the information?
3. Eliminate Unnecessary Sensitive Data:
Proactively remove files containing confidential information that are no longer required. When it comes to sensitive data, less is indeed more. Prioritize eliminating all unencrypted data within your organization.
4. Protect Necessary Sensitive Data:
If sensitive data must be stored, ensure robust protection measures are in place.
- Encrypt all necessary stored data.
- Implement strict need-to-know access controls.
- Avoid using removable media for storing confidential data.
- Conduct sensitive data scans regularly (quarterly or monthly).
Common Hiding Places for Payment Card Data:
Payment card data can inadvertently leak into networks due to flawed processes or misconfigured applications, even those not intended to store sensitive data. Common locations where credit card information might be found include:
- Error logs
- Accounting departments’ files
- Sales departments’ records
- Marketing departments’ data stores
- Customer service representatives’ systems
- Administrative assistants’ files
7 Key Tips for Effective Credit Card Scanning and Secure Data Storage
Data discovery is not a one-time task; it’s an ongoing process. Regularly scheduled scans are essential to maintain continuous PCI compliance.
A thorough investigation is necessary for accurate cardholder data identification. Initial efforts should include a review of the existing network, data flow diagrams, CHD locations, and discussions with relevant stakeholders about cardholder data handling.
This comprehensive approach will either validate the current scope or reveal that the actual scope is broader than initially defined. Adjustments can then be made in collaboration with program managers and data managers.
Establishing known card data locations is just the first step. Verifying that these locations encompass all cardholder data, both within and outside the PCI scope, is crucial. Data leakage often occurs in unexpected locations, and identifying these hidden spots is vital.
Insufficient scope coverage can lead to inadequate or unenforced controls for protecting cardholder data in storage. This is where credit card scanning and discovery software becomes indispensable, providing the necessary visibility for robust data protection.
- Interview Employees: Understand how different departments handle card data.
- Map Card Data Flow: Visualize how card information moves through your systems.
- Utilize Credit Card Scanning Software: Regularly scan for card data with a dedicated tool.
- Secure Discovered Data: Securely delete or encrypt any discovered card data.
- Restrict System Access: Limit system access to authorized personnel only.
- Minimize Data Storage: Avoid storing card data unless absolutely necessary.
- Implement Network Segmentation: Isolate card data to reduce the number of systems involved in storage, processing, or transmission.
