Nation-State Threats Put SMBs in Their Sights

Cyberthreat groups increasingly see small and medium businesses, especially those…

Kimsuky Exploits BlueKeep RDP Vulnerability to Breach Systems in South Korea and Japan

Cybersecurity researchers have flagged a new malicious campaign related to…

Akira Ransomware Launches New Cyberattacks Using Stolen Credentials and Public Tools

The Akira ransomware group has intensified its operations, targeting over…

Detecting And Blocking DNS Tunneling Techniques Using Network Analytics

DNS tunneling is a covert technique that cybercriminals use to…

New Phishing Technique Hides Weaponized HTML Files Within SVG Images

Cybersecurity experts have observed an alarming increase in the use…

CISA Warns: Old DNS Trick ‘Fast Flux’ Is Still Thriving

An old DNS switcheroo technique is still helping attackers keep…

CISA Adds Five Actively Exploited Vulnerabilities in Advantive VeraCore and Ivanti EPM to KEV List

The U.S. Cybersecurity and Infrastructure Security Agency (CISA) on Monday…

Minnesota Tribe Struggles After Ransomware Attack

Hotel and casino operations for the Lower Sioux Indians have…

Google Brings End-to-End Encryption to Gmail

The new Google Workspace features will make it easier for…

Lexmark Expands Print Security Services Worldwide

Post Content ​The original article found on darkreading Read More

Uncategorized

DeepSeek R1: The Revolutionary AI Model Disrupting Global Analytics and Transforming Industries

In the fast-evolving landscape of artificial intelligence (AI), few innovations have caused as much disruption as the DeepSeek R1. Released by the Chinese startup DeepSeek, this groundbreaking AI model has sent shockwaves through the tech industry, challenging the dominance of established players like OpenAI and Google. With its unique approach to AI development and its potential to democratize access to advanced analytics, the DeepSeek R1 is not just a technological marvel but a market disruptor reshaping the global AI landscape.

In this blog post, we’ll explore what the DeepSeek R1 is, why it’s considered a game-changer, and how it’s impacting industries worldwide. We’ll also examine the broader implications of this Chinese innovation and why it has sparked intense debate in the tech and financial sectors.

What is DeepSeek R1?

The DeepSeek R1 is an advanced AI model developed by the Chinese startup DeepSeek, which is owned by the stock trading firm High-Flyer 

Released on January 20, 2025, the R1 model has quickly gained attention for its innovative design and disruptive potential. Unlike traditional AI models that rely heavily on supervised fine-tuning, DeepSeek R1 employs pure reinforcement learning, allowing it to learn through trial and error and self-improve through algorithmic rewards 

This approach has proven particularly effective in enhancing the model’s reasoning capabilities, setting it apart from competitors like OpenAI’s GPT models or Google’s Gemini.

One of the most striking features of the DeepSeek R1 is its cost efficiency. According to DeepSeek’s official WeChat account, the R1 model is 20 to 50 times cheaper to use than OpenAI’s comparable models, depending on the task 

This affordability has made it an attractive option for businesses and researchers, particularly in regions with limited access to high-cost AI solutions.

Key Features of DeepSeek R1
  1. High-Speed Processing: The DeepSeek R1 boasts a powerful processing unit that can handle multiple data streams simultaneously, ensuring rapid analysis without sacrificing accuracy.
  2. AI-Driven Insights: Utilizing state-of-the-art AI algorithms, the DeepSeek R1 can identify patterns and trends in data that would be nearly impossible for humans to detect.
  3. User-Friendly Interface: Designed with usability in mind, the device features an intuitive interface that allows users to navigate complex data sets and extract valuable information easily.
  4. Scalability: The DeepSeek R1 can be scaled to meet the needs of different organizations, from small businesses to large corporations, making it a versatile solution for various industries.
  5. Real-Time Analytics: By processing data in real time, users can make informed decisions quickly, which is crucial in fast-paced environments.

Why is DeepSeek R1 a Market Disruptor?

The release of the DeepSeek R1 has disrupted the AI market in several significant ways:

  1. Challenging Big Tech’s Dominance
    For years, U.S.-based companies like OpenAI, Google, and Microsoft have dominated the global AI landscape. DeepSeek’s R1 model has challenged this status quo, raising questions about whether American companies can maintain their edge in the face of rising competition from China 4. The model’s release has even triggered a selloff in global AI stocks, with companies like Nvidia losing billions in market value.
  2. Low-Cost Innovation
    One of the most disruptive aspects of the DeepSeek R1 is its ability to deliver high-quality AI performance at a fraction of the cost of its competitors. By using less technologically advanced chips and optimizing its algorithms, DeepSeek has made advanced AI more accessible to a broader audience. This democratization of AI technology could level the playing field for smaller businesses and startups, enabling them to compete with larger, more established players.
  3. Open-Source Accessibility
    DeepSeek’s decision to release the R1 model as open-source has further amplified its impact. This move has generated significant interest in the AI research community, as it allows developers and researchers to experiment with and build upon the model’s capabilities 5. By fostering collaboration and innovation, DeepSeek is accelerating the pace of AI development globally.
  4. Reinforcement Learning Approach
    The R1 model’s reliance on reinforcement learning differs from traditional AI development methods. This approach enhances the model’s reasoning abilities and reduces the need for extensive labeled datasets, which are often expensive and time-consuming to create. As a result, the R1 model is both more efficient and more adaptable than many of its competitors.

Implications for Various Industries

The impact of DeepSeek R1 extends across multiple sectors, each experiencing unique benefits:

  • The DeepSeek R1’s disruptive potential extends across multiple sectors, each experiencing unique benefits and challenges:
  • Finance: The R1 model’s ability to analyze market trends and predict stock movements in real time has made it a valuable tool for investment firms in the financial sector. However, its release has also caused volatility in global markets as investors reassess the competitive landscape.
  • Healthcare: The R1 model’s advanced reasoning capabilities could revolutionize healthcare by enabling more accurate diagnoses and personalized treatment plans. Its cost efficiency makes it particularly appealing for healthcare providers in developing regions.
  • Retail and E-Commerce: Retailers can leverage the R1 model to analyze customer behavior and optimize inventory management. Its affordability allows even small businesses to access advanced analytics, leveling the playing field in a competitive market.
  • Technology and AI Development: By making its model open-source, DeepSeek has created opportunities for collaboration and innovation in the tech sector. Developers worldwide can experiment with the R1 model, leading to new applications and advancements in AI technology.

Case Studies: Real-World Applications

To illustrate the profound impact of the DeepSeek R1, let’s examine a few real-world applications:

  1. Financial Services: A leading investment firm integrated the DeepSeek R1 into its trading operations. By analyzing stock market data in real time, they could predict market shifts with remarkable accuracy, resulting in a 20% increase in their investment returns over six months.
  2. Healthcare Provider: A healthcare provider employed the DeepSeek R1 to analyze patient data from electronic health records (EHRs). The system could identify patterns that led to the early detection of chronic diseases, ultimately improving patient care and reducing hospitalization rates.
  3. E-commerce Business: An e-commerce company utilized the DeepSeek R1 to analyze customer purchase behavior. By understanding trends and preferences, they could optimize their marketing strategies, leading to a 30% increase in sales during a key shopping season.

Security and Privacy Concerns

There are still a lot of concerns with the security and privacy not only of AI chatbots but specifically ones from China. You need to use common sense when dealing with any online program. It is fine to ask common public knowledge questions, but I would not input anything personal or business-related.

Michael Wooldridge, a professor of the foundations of AI at the University of Oxford, told the Guardian it was not unreasonable to assume data inputted into the chatbot could be shared with the Chinese state.

“I think it’s fine to download it and ask it about the performance of Liverpool football club or chat about the history of the Roman empire, but would I recommend putting anything sensitive or personal or private on them? “Absolutely not … Because you don’t know where the data goes.” Michael Wooldridge

DeepSeek is based in Hangzhou and makes clear in its privacy policy that the personal information it collects from users is held “on secure servers located in the People’s Republic of China”.

It says it uses data to “comply with our legal obligations, or as necessary to perform tasks in the public interest, or to protect the vital interests of our users and other people”.

China’s national intelligence law states that all enterprises, organizations, and citizens “shall support, assist, and cooperate with national intelligence efforts.”

The Global Impact of DeepSeek R1

The release of the DeepSeek R1 has disrupted the AI market and sparked broader geopolitical and economic debates. As a Chinese innovation, the R1 model has intensified competition between the U.S. and China in the race for AI supremacy. Its success has raised questions about the global balance of power in technology and whether U.S. companies can maintain their leadership in the face of rising competition.

Moreover, the R1 model’s affordability and accessibility have the potential to bridge the digital divide, enabling more countries and organizations to benefit from advanced AI technology. However, this democratization also comes with risks, as the widespread availability of powerful AI models could lead to misuse or unintended consequences.

Future Prospects for DeepSeek R1

As the DeepSeek R1 continues gaining traction, its prospects look promising. Here are some potential developments to watch:

  1. Enhanced Capabilities: Future iterations of the R1 model may incorporate even more advanced algorithms, further improving its performance and adaptability.
  2. Broader Adoption: As more organizations recognize the value of the R1 model, its adoption is likely to increase across various industries and regions.
  3. Integration with Emerging Technologies: The R1 model could be integrated with other technologies, such as the Internet of Things (IoT) and blockchain, creating new opportunities for innovation.
  4. Regulatory Challenges: As the R1 model disrupts markets and industries, it may face increased scrutiny from regulators, particularly in the U.S. and Europe.

DeepSeek Self Host

DeepSeek models can be self-hosted on your local machine, offering a private and secure alternative to cloud-based services. Here are some resources and steps to guide you through the process:

  • Ollama: Ollama is a user-friendly tool for running DeepSeek R1 locally. It requires minimal configuration and is suitable for individuals or small-scale projects. You can start by checking your GPU configuration with nvidia-smi and then running the DeepSeek R1 model with commands like ollama run deepseek-r1:8b for an 8B version or ollama run deepseek-r1:32b for a 32B version.
  • Docker Compose: For a more comprehensive setup, you can use Docker Compose to manage multiple services, including MongoDB, Ollama, and Chat-UI. This approach is detailed in a guide by ThinhDA, which provides a docker-compose.yaml file to configure these services. The setup ensures that all services are correctly configured and connected, making it easier to manage your local environment.
  • Open-WebUI: Another option is to use Open-WebUI for a graphical interface. This requires Python 3.11 for compatibility and involves running the server with open-webui serve. You can access the GUI at http://localhost:8080 or use Docker for a containerized solution.

These methods provide different levels of complexity and flexibility, allowing you to choose the best approach based on your needs and available resources.

Conclusion

The DeepSeek R1 is more than just an AI model—it symbolizes the shifting dynamics in the global tech industry. By delivering high-quality performance at a fraction of the cost of its competitors, the R1 model has democratized access to advanced AI technology and challenged the dominance of established players. Its release has sparked intense debate about the future of AI and the global balance of power in technology.

As we look to the future, DeepSeek R1 reminds us of innovation’s transformative potential. Whether it empowers businesses, revolutionizes industries, or reshapes global markets, the R1 model is a testament to AI’s power to drive change. The question now is not whether DeepSeek will continue to disrupt the market but how far its impact will reach.

If you want to try out DeepSeek R1 yourself, I suggest you use the self-hosted version instead of the online one. The latter still raises many privacy concerns.

The post DeepSeek R1: The Revolutionary AI Model Disrupting Global Analytics and Transforming Industries appeared first on .

Uncategorized

Important Updates to SAQ-A Merchant Compliance Requirements

The PCI Security Standards Council (PCI SSC) has introduced significant updates to the Self-Assessment Questionnaire A (SAQ-A), which take effect as of March 31, 2025. These changes impact merchant eligibility requirements and compliance obligations, sparking discussions within the PCI community about what this means for merchants, Service Providers (SPs), and Qualified Security Assessors (QSAs).


Overview of the Changes

The latest update to SAQ-A involves adjustments to the compliance requirements for e-commerce businesses that outsource cardholder data processing. Specifically:

  1. Removal of Explicit Requirements:
    • PCI DSS requirements 6.4.3 and 11.6.1—which mandate the inventory, justification, and control of scripts on payment pages, as well as the weekly monitoring of HTTP headers—are no longer explicitly required for SAQ-A merchants.
    • Requirement 12.3.1 for conducting a Targeted Risk Analysis to support Requirement 11.6.1 has also been removed.
  2. New Eligibility Criteria:
    • Merchants must now confirm that their entire e-commerce site (not just the payment page) is secure and not vulnerable to attacks from malicious scripts, including first-party, third-party, and external scripts that could compromise e-commerce systems.
    • This requirement introduces a broad, high-standard obligation for ensuring protection against eSkimming and similar threats, even without the specific compliance steps outlined in 6.4.3 and 11.6.1.
  3. Two SAQ-A Versions:
    • The PCI SSC has released two versions of SAQ-A:
      • The version published in October 2024, which will remain valid until March 31, 2025.
      • A new version, published in January 2025, which reflects these updates and becomes mandatory on March 31, 2025.

“If a merchant is planning to continue using SAQ A in the future, they will now need to ensure that the way they protect against script-originated attacks covers the whole site and not just the payment page. If they can’t do this, they won’t meet the new eligibility criteria, and so they’ll likely need to complete SAQ A-EP instead. This would be a huge uplift, going from 27 applicable requirements in future SAQ A, up to 151 requirements and sub-requirements in SAQ A-EP.” – Gareth Bowker (Jscramber)


What Has Changed and Why It Matters

While removing explicit requirements 6.4.3 and 11.6.1 may seem like a relaxation, the underlying security expectations remain stringent. Merchants eligible for SAQ-A must still implement robust eSkimming protections and script controls to meet the new eligibility criteria.

Key points include:

  • Eligibility Is Limited: Only a small subset of merchants—those who fully outsource all cardholder data processing (e.g., e-commerce merchants relying entirely on third-party service providers)—qualify for SAQ-A. Most merchants across Levels 1, 2, 3, and most of Level 4 must still fully comply with 6.4.3 and 11.6.1.
  • Circular Compliance Challenge: Although 6.4.3 and 11.6.1 are no longer explicitly required for SAQ-A, merchants need script inventory, monitoring, and controls to meet the new eligibility requirement of securing their site from vulnerabilities. This effectively necessitates adherence to the principles of these requirements, even in their absence.

What Hasn’t Changed

  1. Compliance Deadlines Remain Unchanged:
    • The deadline for compliance with PCI DSS v4.0.1, including requirements 6.4.3 and 11.6.1, remains March 31, 2025. This applies to all merchants not eligible for SAQ-A.
  2. No Changes for Service Providers:
    • SPs must continue to comply with 6.4.3 and 11.6.1, ensuring script inventory, monitoring, and the security of payment flows.
  3. SAQ-A Merchants Still Need Robust Protections:
    • While the compliance process may appear simplified, the expectation of preventing vulnerabilities (e.g., skimming attacks) remains.

Implications for Stakeholders

For SAQ-A Merchants

  • Eligibility Challenges:
    • To qualify for SAQ-A, merchants must confirm their site is not vulnerable to script-based attacks. Merchants cannot meet this eligibility requirement without proper script controls and monitoring.
    • Merchants unable to meet these criteria must switch to other Self-Assessment Questionnaires (SAQs) that require full compliance with 6.4.3 and 11.6.1, most likely SAQ A-EP.
  • Security Remains Key:
    • The removal of explicit requirements does not eliminate the obligation to secure e-commerce systems. Robust eSkimming protections are essential to safeguard customer data and maintain compliance.

For Service Providers

  • Support Your Merchants:
    • Educate small merchants about the importance of script controls and guide them toward solutions that meet compliance requirements.
    • Small merchant clients may misinterpret these updates as a relaxation of obligations, leaving them vulnerable to attacks. Use this opportunity to position yourself as a trusted partner by offering low-burden, cost-effective solutions.
  • Expand Your Offerings:
    • Generate additional revenue by introducing value-added services that simplify compliance for merchants while enhancing their security posture.

For QSAs

  • Educate and Clarify:
    • Merchants may mistakenly believe that the removal of 6.4.3 and 11.6.1 means fewer security obligations. QSAs must emphasize that the expectation to secure e-commerce environments remains even though explicit requirements have been removed.
  • Provide Actionable Solutions:
  • Address FAQ-1331 Concerns:
    • Clarify that Level 1 merchants cannot misuse the updated SAQ-A to bypass compliance with 6.4.3 and 11.6.1. The circular compliance logic ensures that eSkimming protections are required even for SAQ-A eligibility.

Summary of Key Takeaways

Opportunities for Collaboration: Service Providers and QSAs can be vital in guiding merchants through these changes and implementing effective solutions.

Changes to SAQ-A: The removal of explicit requirements 6.4.3 and 11.6.1 applies only to a small subset of merchants who meet strict SAQ-A eligibility criteria.

Security Expectations Remain: SAQ-A merchants must implement robust protections against script-based vulnerabilities.

Deadline Remains Firm: All merchants must comply with PCI DSS v4.0.1 by March 31, 2025.

You can find the full article on the PCI Council website here.

The post Important Updates to SAQ-A Merchant Compliance Requirements appeared first on .

Uncategorized

Digital Skimming: The Growing Threat to Businesses in the Digital Era

The movement of money from physical to digital has revolutionized how we bank and shop. However, this shift has also attracted criminals, replacing traditional heists with sophisticated digital thefts. Data is as valuable as money in today’s economy, making nearly every business a potential target for digital skimming attacks.

From customer lists and payroll information to sensitive card details (card numbers, expiry dates, and CVV codes), businesses store immense amounts of highly desirable data for cyber criminals. It’s no surprise then that card fraud is a $48 billion problem annually, with projections to double to $100 billion by 2027.

With cybercrime showing no signs of slowing down and new PCI DSS requirements for payment pages coming into effect on April 1, 2025, businesses must act now to protect themselves. In this post, we’ll explore digital skimming, its impacts, how it works, and, most importantly, how businesses can defend against this growing threat.


What Is Digital Skimming?

Digital skimming, also known as e-skimming, formjacking, or data skimming, is a type of cyberattack where criminals steal sensitive information entered into web forms. This often includes payment data from online checkout pages or personally identifiable information (PII) entered into other online forms.

These attacks typically exploit vulnerabilities in a website’s infrastructure, allowing malicious actors to inject JavaScript-based skimmers into payment pages, also called Magecart attacks. What makes these attacks so dangerous is their stealth: the payment process appears unaffected, leaving both the customer and the merchant unaware of the compromise.


The Scale of the Problem

Digital skimming is a major and growing problem with devastating consequences for both businesses and consumers. Recent high-profile breaches underscore just how widespread and damaging these attacks can be:

  • In July 2024, AT&T admitted that criminals had accessed nearly all call and text data of its 110 million customers over a six-month period.
  • A cyberattack on UK pathology lab Synnovis in June 2024 resulted in data theft from 300 million patient interactions, disrupting healthcare services for weeks.
  • A breach at Ticketmaster exposed the personal data of 560 million customers, which attackers threatened to publish on the dark web.

These examples highlight the severity of digital skimming and its far-reaching consequences.


The Business Impact of Digital Skimming

The cost of a digital skimming attack goes far beyond the immediate data theft. Businesses face direct financial losses, incident response costs, regulatory fines, and breach notification expenses. For example:

  • Kaiser Permanente, a U.S. health insurance provider, revealed that tracking technologies on its website had exposed the private health data of 13.4 million patients.
  • Similarly, the U.S. Postal Service faced backlash after tracking pixels on its site potentially compromised the data of 62 million users.

Beyond financial losses, the indirect costs to a business are even more significant. A data breach can damage a brand’s reputation, erode customer trust, and result in long-term loss of business. For instance, Australian prescriptions provider MediSecure declared insolvency just weeks after disclosing a ransomware attack that exposed the data of 13 million people.


How Digital Skimming Works

Digital skimming attacks typically follow a four-step process:

  1. Initial Breach: Attackers access a website’s source code or infrastructure directly or through a third-party provider. This is often achieved through software vulnerabilities, malware, or stolen credentials.
  2. Code Injection: Malicious JavaScript code is injected into payment pages. Attackers tailor their methods depending on whether payment forms are embedded directly on the page or through an iFrame.
  3. Data Exfiltration: When customers input payment or personal data, the malicious code covertly collects and encrypts the information before sending it to the attacker’s server.
  4. Monetization: Stolen data is used for fraudulent purchases or sold on the dark web, which can be used for creating fake identities, issuing fake cards, or other criminal activities.

Who Is at Risk?

The short answer: every business.

Cybercriminals don’t discriminate based on the size or nature of a business. Whether you’re a global retailer, a small nonprofit, or a government agency, you’re a target. Criminals seek out cardholder data and PII because of its high resale value and utility in fraud.

The most common type of data stolen in 2024 was customer PII (48%), but employee PII, such as tax IDs and home addresses, is even more lucrative for criminals. If your business collects or processes data, it’s essential to assume it has value to attackers and take appropriate precautions.


The Rise of Magecart Attacks

A specific type of digital skimming attack, Magecart, has become synonymous with skimming payment pages. Named after the Magento e-commerce platform and shopping carts, Magecart attacks involve injecting malicious JavaScript to steal card data inputted during transactions.

Magecart attacks can take two forms:

  1. First-Party Attacks: Criminals directly compromise the victim’s website by injecting a skimming code into the payment page. For example, the 2023 breach of DNA testing company 23andMe exposed nearly 7 million user records.
  2. Third-Party Attacks: Malicious code is injected through a third-party provider, also known as a supply chain attack. This is particularly concerning as modern websites rely on multiple third-party scripts to function, each of which can serve as an entry point for attackers.

How to Protect Against Digital Skimming

To safeguard your business from digital skimming, start by implementing these key measures:

  1. Prevent Unauthorized Access: Use strong passwords, enforce unique logins, and ensure firewalls, encryption, and anti-virus tools are in place.
  2. Regular Security Assessments: Conduct routine monitoring, third-party due diligence, and security audits to identify vulnerabilities.
  3. Secure Code Practices: Follow secure coding standards and maintain compliance with security frameworks like PCI DSS.

New PCI DSS v4.0 Requirements

Recognizing the growing threat of digital skimming, the PCI Security Standards Council introduced two new requirements in PCI DSS v4.0, effective April 2025:

  1. Requirement 6.4.3: Manage all JavaScript present on payment pages to minimize attack surfaces.
  2. Requirement 11.6.1: Detect and alert on any tampering or unauthorized changes to payment pages.

Conclusion

Digital skimming is a rapidly growing threat, but businesses can protect themselves and their customers with the right tools and precautions. By staying informed, implementing strong security practices, and leveraging technologies, you can build a robust defense against this modern-day scourge.

The post Digital Skimming: The Growing Threat to Businesses in the Digital Era appeared first on .

Uncategorized

Key Considerations for PCI DSS v4.0.1 Requirements 4.2.1.1 and 12.3.3

With several new PCI DSS v4.0.1 requirements set to take effect on April 1, 2025, two requirements—4.2.1.1 and 12.3.3—have generated significant attention and questions. Let’s begin by reviewing the text of these requirements:

  • 4.2.1.1:
    “An inventory of the entity’s trusted keys and certificates used to protect PAN during transmission is maintained.”
  • 12.3.3:
    “Cryptographic cipher suites and protocols in use are documented and reviewed at least once every 12 months, including at least the following:
    • An up-to-date inventory of all cryptographic cipher suites and protocols in use, including the purpose and where used.
    • Active monitoring of industry trends regarding the continued viability of all cryptographic cipher suites and protocols in use.
    • Documentation of a plan to respond to anticipated changes in cryptographic vulnerabilities.”

The Relationship Between 4.2.1.1 and 12.3.3

Requirement 12.3.3 is a broad, comprehensive requirement encompassing all cryptographic use cases, including those covered under 4.2.1.1. While 4.2.1.1 focuses specifically on the inventory of trusted keys and certificates protecting PAN during transmission, 12.3.3 requires organizations to document and assess all cryptographic cipher suites and protocols used across their environments. This includes cryptographic implementations protecting cardholder data (CHD) and sensitive authentication data (SAD) in databases, files, or other locations.

The overarching goal of both requirements is to ensure organizations are cryptographically agile—capable of assessing and responding to cryptographic vulnerabilities or changes in standards without disruption. By proactively developing inventories and response plans, organizations can avoid being caught off guard when an algorithm or mode is deemed insecure or deprecated.

Recommendations for Implementing Requirements 4.2.1.1 and 12.3.3

  1. Address Both Requirements Simultaneously
    Since 4.2.1.1 is a subset of 12.3.3, organizations should aim to fulfill both requirements concurrently. This approach streamlines documentation efforts and ensures all cryptographic assets are accounted for in a single process.
  2. Inventory All Cryptographic Assets, Not Just PCI Scope
    Organizations often limit compliance efforts to systems within PCI scope. However, cryptographic agility is a security principle that extends beyond PCI compliance. Weak or outdated cryptography in non-PCI environments can still pose a risk to the organization, including its PCI environment. To maintain a strong security posture, a comprehensive inventory should include all cryptographic implementations, regardless of scope.
  3. Focus on Cryptographic Inventories
    Developing a thorough inventory is critical for both requirements. For 4.2.1.1, this means cataloging all TLS certificates, including those used internally and externally. Many organizations overlook internally used secure communication protocols, such as:
    • TLS: Often associated with external communications, TLS is also widely used internally, such as with self-signed certificates for browser-based management tools or consoles. These certificates must be included in the inventory.
    • Secure Shell (SSH): Another commonly overlooked protocol, SSH usage must also be inventoried.

Cryptographic inventories should document:

  • The algorithm and bit strength in use.
  • The mode(s) of implementation.
  • The specific locations and purposes for each cryptographic application.

A common pitfall is inadequate documentation for virtual private networks (VPNs). While organizations may know the VPN’s purpose and connections, they often lack details about the cryptographic algorithms and bit strengths used. This lack of information is typically due to outdated implementations or third-party-managed configurations. Regardless, all VPN cryptography must be documented, even for third-party-managed systems.

  1. Understand Cryptography and Its Variations
    Not all cryptographic methods are equally secure. While detailed mathematical understanding isn’t necessary, security professionals should recognize that cryptographic strength varies widely. For instance:
    • The Advanced Encryption Standard (AES) is currently the strongest encryption standard endorsed by NIST. 128-bit, 192-bit, and 256-bit encryption are considered secure. Organizations should prioritize AES for encryption implementations.
    • Cryptography extends beyond encryption, including hashing functions, digital signatures, key derivation, and message authentication codes (MAC). While not all of these are covered under PCI DSS, they remain critical to a robust security strategy.

Organizations should reference NIST’s Special Publication 800-134Ar3 for guidance on transitioning to secure cryptographic algorithms and key lengths. This document outlines cryptographic best practices and deprecates insecure algorithms.

  1. Prepare for Quantum Computing
    The advent of quantum computing underscores the urgency of cryptographic agility. Quantum computing has the potential to render many current cryptographic algorithms insecure. This is particularly concerning for organizations still relying on outdated algorithms like the Triple Data Encryption Algorithm (TDEA) or Secure Hash Algorithm 1 (SHA-1), which are already considered insecure.

    Organizations must proactively transition to quantum-resistant cryptography in line with NIST recommendations. Transition plans should account for end-of-life (EOL) deadlines and the complexities of replacing cryptographic implementations, such as third-party dependencies or rekeying large datasets.

Cryptographic Architecture and Active Monitoring

  • Cryptographic Architecture
    A cryptographic architecture defines the organization’s approach to cryptography, including:
    • When and where cryptography is implemented.
    • The acceptable algorithms, modes, and methods (e.g., TLS, VPN, whole disk encryption, field/column encryption, etc.).
    • Guidelines for consistent implementation.

While a diagram may be helpful, a detailed written discussion of these elements is often more effective in defining cryptographic architecture.

  • Active Monitoring of Cryptographic Trends
    To comply with the monitoring requirements of 12.3.3, organizations should maintain meeting minutes documenting discussions and decisions related to cryptographic trends and vulnerabilities. This includes:
    • Reviewing industry updates.
    • Assessing the impact of new vulnerabilities.
    • Planning transitions to secure algorithms.

Organizations must document clear transition plans for algorithms nearing EOL to prevent security gaps. Many commonly used algorithms are set to expire by 2030, so organizations should begin preparations immediately to ensure timely transitions.

In summary, PCI DSS v4.0.1 requirements 4.2.1.1 and 12.3.3 emphasize the need for organizations to maintain comprehensive cryptographic inventories, actively monitor industry trends, and ensure cryptographic agility. Organizations can mitigate risk and maintain compliance in an evolving threat landscape by adopting a proactive and comprehensive approach to cryptographic management.

If you want to learn more about PCI DSS 4.0.1, check out my book, Fortifying The Digital Castle.

a book cover with a castle

The post Key Considerations for PCI DSS v4.0.1 Requirements 4.2.1.1 and 12.3.3 appeared first on .

Uncategorized

Understanding the PCI Approved Scanning Vendor (ASV) Program: A Comprehensive Guide

The Payment Card Industry Data Security Standard (PCI DSS) has established rigorous requirements to safeguard sensitive cardholder data and ensure the security of payment systems globally. Among these standards is the PCI Approved Scanning Vendor (ASV) Program, which is vital in identifying and addressing vulnerabilities in external-facing systems. This blog explores the PCI ASV Program, detailing its purpose, scope, importance, and scan reporting requirements. It serves as a roadmap for businesses looking to ensure compliance with PCI DSS and fortify their cybersecurity posture.


What Is the PCI ASV Program?

The PCI ASV Program, a structured framework managed by the PCI Security Standards Council (PCI SSC), is crucial to the security of payment systems. It enables qualified companies, known as Approved Scanning Vendors (ASVs), to perform external vulnerability scans on merchants’ and service providers’ systems. These scans, a key component of PCI DSS (PCI Data Security Standard) Requirement 11.3.2, are mandated to be conducted at least once every three months by an ASV.

ASVs, certified by the PCI SSC, use specialized scanning tools, methodologies, and processes to identify vulnerabilities in internet-facing components that could potentially expose sensitive cardholder data. By ensuring entities comply with PCI DSS requirements, ASVs significantly reduce the risk of data breaches.

You can find an updated list of certified ASVs on the PCI SSC website.


Why Is the PCI ASV Program Important?

Given the ever-increasing complexity of cyberattacks, the PCI ASV Program is essential for maintaining the security of cardholder data environments (CDEs). Here’s why the program is vital:

  1. Compliance with PCI DSS is not just a recommendation; it’s a necessity. Requirement 11.3.2 mandates that an ASV conduct quarterly external vulnerability scans. Non-compliance can result in severe penalties, loss of customer trust, and significant financial liabilities. The ASV Program is a crucial tool in avoiding these risks.
  2. Proactive Risk Management: The PCI ASV Program is about meeting compliance requirements and staying ahead of potential threats. By identifying weaknesses in internet-facing systems, businesses can address them before malicious actors can exploit them, giving them a sense of preparedness and control.
  3. Standardization and Assurance: The program ensures that scans are performed consistently across entities, providing acquirers, payment brands, and customers with assurance that vulnerabilities are being managed effectively.
  4. Enhanced Security Posture: Regular scans help organizations build a robust cybersecurity framework by identifying and mitigating threats, reducing the likelihood of a data breach.
  5. Consumer Trust: By demonstrating compliance with PCI DSS, businesses reinforce their commitment to protecting sensitive customer data, fostering trust and loyalty.

Can a Merchant or Service Provider Perform its own External Vulnerability Scanning?

The short answer is No. Merchants and service providers must use only ASVs to perform the quarterly external vulnerability scans required by PCI DSS Requirement 11.3.2, and the ASV must manage the ASV scan solution. Some ASV scan solutions may, while still under the control and management of the ASV, be started remotely by a scan customer (for example, via an ASV’s web portal and/or ASV’s scan solution) to allow a scan customer to select the best times to scan their cardholder data environment and define which of the customer’s components are to be scanned. However, only authorized ASV Employees are permitted to configure any settings (for example, modify or disable any vulnerability checks, assign severity levels, alter scan parameters, etc.) or modify the scan output. Additionally, the ASV scan solution must not allow anyone other than an authorized ASV Employee to alter or edit any reports or revise any results.

The approved ASV Companys and the scan solutions are listed here.

Roles and Responsibilities

Approved Scanning Vendors

An ASV is an organization with an ASV scan solution (i.e., a set of security services and tools) used to validate adherence to the external scanning requirements of PCI DSS Requirement 11.3.2. The ASV’s ASV scan solution must be tested by an ASV Validation Lab and approved by PCI SSC before that ASV is added to the list of Approved Scanning Vendors.

ASVs are responsible for the following:

  • Performing external vulnerability scans in accordance with PCI DSS Requirement 11.3.2, this document and other supplemental guidance published by PCI SSC.
  • Maintaining the security and integrity of systems and tools used to perform such scans is a key responsibility of ASVs. This commitment to security should reassure businesses and instill confidence in the PCI ASV Program.
  • Ensuring that such scans:
    • Do not impact the normal operation of the scan customer environment.
    • Do not penetrate or intentionally alter the scan customer environment.
  • Scanning all IP address ranges, domains, components, etc., provided by the scan customer to identify active components and services.
  • Consulting with the scan customer to determine whether components found but not provided by the scan customer should be included in the scope of the scan.
  • Providing a determination as to whether the scan customer’s components have met the scanning requirements.
  • Provide adequate documentation within the scan report to demonstrate compliance or non-compliance of the scan customer’s components with the scanning requirements.
  • Submitting (to the scan customer) the ASV Scan Report Attestation of Scan Compliance cover sheet (an “Attestation of Scan Compliance”) and the scan report in accordance with the instructions of the scan customer’s acquirer(s) and/or Participating Payment Brand(s).
  • This includes the required scan customer and ASV Company attestations in the scan report in accordance with this document and applicable ASV Program requirements.
  • Retaining scan reports and related work papers and work products for three (3) years, as required by the ASV Qualification Requirements.
  • Providing the scan customer with a means for disputing findings of scan reports.
  • Maintaining an internal quality assurance process for its ASV Program-related efforts in accordance with this document and applicable ASV Program requirements.

Scan Customers

Scan customers are responsible for the following:

  • Maintaining compliance with PCI DSS at all times, including properly maintaining the security of their Internet-facing systems, is a crucial responsibility of scan customers. This sense of responsibility and accountability is integral to the success of the PCI ASV Program.
  • Selecting an ASV from the list of Approved Scanning Vendors from the Website to conduct quarterly external vulnerability scanning in accordance with PCI DSS Requirement 11.3.2 and this document using an ASV scan solution.
  • Per the scan customer’s due diligence processes, perform due diligence in the ASV selection process to obtain assurance as to the ASV’s qualification, capability, experience, and level of trust in performing the scanning services required by PCI DSS.
  • Monitoring Internet-facing systems, active protection systems, and network traffic during the scan to the degree deemed appropriate by the scan customer assures an acceptable level of trust is maintained.
  • Defining the scope of external vulnerability scanning, which includes:
    • Providing the IP addresses and/or domain names of all Internet-facing systems to the ASV so the ASV can properly conduct a full scan.
    • Implementing proper network segmentation for any external-facing components excluded from the scope.

See “What Is in Scope for PCI ASV Scans” for more information.

  • Ensuring that devices do not interfere with the ASV scan, including:
    • Configuring active protection systems so they do not interfere with the ASV’s scan, as required by this document. See Section 5.6, “ASV Scan Interference.”
    • Coordinating with the ASV if the scan customer has load balancers in use.
  • Coordinating with the scan customer’s Internet service provider (ISP) and/or hosting providers to allow ASV scans.
  • Attesting to proper scoping and network segmentation (if IP addresses or other components are excluded from scan scope) within the ASV scan solution.
  • Providing sufficient documentation to the ASV to fully enable the ASV’s investigation and resolution of disputed findings, such as suspected false positives, and providing related attestation.
  • Providing sufficient documentation to the ASV to fully enable the ASV’s evaluation of any compensating controls implemented or maintained by the scan customer. See Section 7.8 of the program guide, “Addressing Vulnerabilities with Compensating Controls.”
  • Reviewing the scan report and correcting any noted vulnerabilities that result in a non-compliant scan.
  • Arrange with the ASV to re-scan any non-compliant systems to verify that all “High” and “Medium” severity vulnerabilities have been resolved to obtain a passing quarterly scan. “Vulnerability Severity Levels Based on the NVD and CVSS.”
  • Submitting the completed ASV scan report to the scan customer’s acquirer(s) and/or Participating Payment Brand(s), as directed by the Participating Payment Brands.

What Is in Scope for PCI ASV Scans?

This is one of the biggest sources of confusion regarding ASV scanning. Just as with scoping a PCI DSS assessment, all system components that are not adequately segmented away from the Cardholder Data Environment (CDE) are in scope. This means that if a system can communicate with anything in your CDE or can affect the security of anything in your CDE, it is in scope for ASV scanning.

ALL public IP (Internet Protocol) addresses routed to the in-scope environment and ALL URLs (Uniform Resource Locator) that point to any of the public IP addresses MUST be included in the scans. Failure to do so may result in an inadequate ASV Scan and a non-compliant report.

The scope of an ASV scan is a critical aspect of the PCI ASV Program. It determines which components of a merchant’s or service provider’s infrastructure must be scanned. Here’s a breakdown of what is typically in scope:

  • Internet-Facing Components
    • All external components that are connected to or provide access to the CDE must be scanned. This includes:
      • Web servers
      • Mail servers
      • Firewalls and routers
      • Web server URLs to “hidden” directories that cannot be reached by crawling the website from the home page
  • Cardholder Data Environment (CDE)
    • The CDE comprises systems, people, and processes that store, process, or transmit cardholder data. This includes any system component that could impact its security.
  • Vulnerable Services and Protocols
    • Services such as DNS, mail, and remote access software are assessed for vulnerabilities. Deprecated protocols like SSL or early versions of TLS must also be identified and addressed.
  • Embedded Links and Scripts
    • Scripts loaded and executed on payment pages, especially those originating from external domains, must be scanned for vulnerabilities.
  • Load Balancers and Network Segmentation
    • Scans must account for load balancers to ensure comprehensive testing. If implemented, network segmentation must be validated to exclude non-CDE components from the scan scope.
  • Virtualized and Cloud Environments
    • The scan scope also includes virtual machines, hypervisors, and cloud-based systems that interact with the CDE.

The scan customer (merchant or service provider) must define and attest to the scope of the scan before the ASV finalizes the report. The customer is held accountable if an external-facing system is excluded from the scan and later becomes the source of a data breach.

ASV “Discovery” and Scope Validation

ASVs must, at a minimum, perform the below actions to identify whether any scoping discrepancies exist in the information provided by the scan customer. Information about any scoping discrepancies must be indicated on the Attestation of Scan Compliance under A.3, “Scan Status” (Number of components found by ASV but not scanned because scan customer confirmed components were out of scope). Although this information must be reported as noted above, the ASV should disregard this information in making its PCI DSS compliance determination:

  • Include any IP address or domain previously provided to the ASV and still owned or used by the scan customer that has been removed at the request of the scan customer.
  • For each domain provided, look up its IP address to determine whether the scan customer already provided it.
  • For each domain provided, perform DNS forward and reverse lookups of common host names—such as “www,” “mail,” etc.—that were not provided by the scan customer.
  • Identify any IP addresses found during MX record DNS lookup.
  • Identify any IP addresses outside the scope reached via web redirects from in-scope web servers (this includes all forms of redirect, including JavaScript, Meta redirect, and HTTP 30x codes).
  • Match domains found during crawling to user-supplied domains to find undocumented domains belonging to the scan customer.

FQDNs vs IP

Using an Approved Scanning Vendor (ASV) does not always guarantee that vulnerability scans will be performed correctly. Some ASV solutions fail to handle Fully Qualified Domain Names (FQDNs) properly. Instead of scanning the FQDN, they may only perform a DNS lookup and scan the associated IP address. This approach can lead to significant issues.

When web traffic is directed to an IP address, it often lands on a generic page or a default server response. However, using the correct FQDN ensures that traffic is routed to the intended website via the host header. Host headers are critical for web services that host multiple websites on the same server or for systems like Web Application Firewalls (WAFs), proxy servers, or load balancers. These systems rely on the host header to direct incoming requests to the appropriate internal resources. If an ASV solution cannot handle FQDNs correctly, the scan may only target a landing page, failing to assess the actual website and its vulnerabilities.

The ASV Program Guide, specifically Section 5.5, titled “ASV Scan Scope Definition,” emphasizes the importance of ensuring that scans cover all unique entry points into system components across the entire in-scope infrastructure. This includes properly handling FQDNs to ensure comprehensive and accurate scanning.

In summary, ensuring that your ASV solution can correctly process FQDNs is essential for accurate vulnerability scanning and compliance with PCI DSS requirements.

ASV Scan Interference

Besides defining the scope, this is one of the most significant items of confusion regarding ASV scanning. 

If an ASV detects that an active protection system has actively blocked or filtered a scan, then the ASV must handle it per Section 7.6, “Resolving Inconclusive Scans,” in the program guide.  In order to ensure that reliable scans can be conducted, the ASV scan solution must be allowed to perform scanning without interference from active protection systems, where “active” denotes security systems that dynamically modify their behavior based on information gathered from non-attack network traffic patterns. Non-attack traffic refers to potentially legitimate network traffic patterns that do not indicate malformed or malicious traffic. In contrast, attack traffic includes, for example, malicious network traffic patterns or patterns that match known attack signatures, malware, or packets exceeding the maximum permitted IP packet size.

Examples of active protection systems that dynamically modify their behavior include, but are not limited to:

  • Intrusion prevention systems (IPS) that drop non-malicious packets based on previous behavior from the originating IP address (for example, blocking all traffic from the originating IP address for a period of time because it detected one or more systems being scanned from the same IP address)
  • Web application firewalls (WAF) block all traffic from an IP address based on the number of events exceeding a defined threshold (for example, more than three requests to a login page per second)
  • Network security controls that shun/block an IP address upon detection of a port scan from that IP address
  • Network security controls that block IP address ranges because an attack was perceived based on previous network traffic patterns.
  • Quality of Service (QoS) devices that limit certain traffic based on traffic volume anomalies (for example, blocking DNS traffic because DNS traffic exceeded a defined threshold)
  • Spam filters that blacklist a sending IP address based on certain previous SMTP commands originating from that address

Such systems may react differently to an automated scanning solution than they would react to a targeted hacker attack, which could cause inaccuracies in the scan report.

Systems that consistently block attack traffic while consistently allowing non-attack traffic to pass (even if the non-attack traffic follows directly after attack traffic) typically do not cause ASV scan interference. Examples of these security systems (that do not dynamically modify their behavior; rather, they maintain consistent, static behavior based on rules or signatures) include, but are not limited to:

  • Intrusion detection systems (IDS) log events, track context, or have a multifaceted approach to detecting attacks, but action is limited to alerting (there is no intervention).
  • Web application firewalls (WAF) detect and block SQL injections but let non-attack traffic from the same source pass.
  • Intrusion prevention systems (IPS) that drop all occurrences of a certain attack but let non-attack traffic from the same source pass.
  • Network security controls that are configured to always block certain ports but always keep other ports open.
  • VPN servers that reject entities with invalid credentials but permit entities with valid credentials.
  • Antivirus software that blocks, quarantines, or deletes all known malware based on a database of defined “signatures” but permits all other perceived clean content.
  • Logging/monitoring systems, event and log aggregators, reporting engines, etc.

If the ASV scan cannot detect vulnerabilities on Internet-facing systems because an active protection system blocks it, those vulnerabilities will remain uncorrected and may be exploited by an attacker whose attack patterns don’t trigger the active protection mechanism.

Temporary configuration changes may need to be made by the scan customer to remove interference during an ASV scan.

Due to the remote nature of external vulnerability scans and the need mentioned previously to conduct an ASV scan without interference from active protection systems, certain temporary configuration changes to the scan customer’s network devices may be necessary to obtain a scan that accurately assesses the scan customer’s external security posture. Note, per above, that temporary configuration changes are not required for systems that consistently block attack traffic while consistently allowing non-attack traffic to pass (even if the non-attack traffic follows directly after attack traffic).

The changes in this section are considered temporary and are only required for the duration of the ASV scan. They only apply to external-facing components in scope for external vulnerability scans required by PCI DSS Requirement 11.3.2. Scan customers are encouraged to work with the ASV to perform secure scans at least once every three months that do not unnecessarily expose the scan customer’s network—but also do not limit the final results of the ASV scans—as follows:

  • Agree on a time for the ASV scan window to minimize how long changed configurations are in place.
  • Conduct the ASV scan during a maintenance window under the scan customer’s standard change control processes, with full monitoring during the ASV scan.
  • Configure the active protection systems to either Monitor and log, but not act against, the originating IP address(es) of the ASV or
  • Allow non-attack traffic to pass consistently (even if the non-attack traffic immediately follows attack traffic)

Reapply the previous configurations as soon as the ASV scan is complete.

Note: The intent of these temporary configuration changes is to ensure that an active protection system, such as an IPS reacting dynamically to traffic patterns, does not interfere with the ASV scan in a manner that would provide the ASV scan solution with a different view of the environment than the view an attacker would have. ASV scans tend to be “noisy” as they generate a lot of traffic in a short period of time. This is generally to ensure that an ASV scan can be completed as quickly as possible. However, this type of approach can also lead to a high rate of reaction by active intrusion-prevention systems. An attacker will generally attempt to restrict the volume of their scans so they are stealthier and less likely to trigger an event that may be noticed. Thus, the high-volume scans typically performed by ASVs are significantly more likely to trigger an active protection mechanism than those of an attacker.

Temporary configuration changes do not require the scan customer to “white list” or provide the ASV with a higher level of network access. Rather, the scan customer must ensure that any triggers, such as volume-based or correlated IP address thresholds, are not activated by the ASV scan and that the scan is allowed to complete. The intent is that the ASV be provided the same network-level view as an actual attacker throughout the scan.


The ASV Scan Process: Key Phases

The ASV scan process is structured to ensure comprehensive vulnerability assessment and remediation. Below is an overview of the major phases:

1. Scoping

  • The scan customer defines the scope of the scan, including all internet-facing IP addresses, domains, and system components. Proper segmentation must be implemented to exclude out-of-scope components.

2. Scanning

  • The ASV performs external vulnerability scans using its validated scan solution. The scans must be non-disruptive and should not interfere with the customer’s environment.

3. Reporting and Remediation

  • The ASV generates a detailed scan report highlighting vulnerabilities, their severity, and remediation steps. The customer must address all “High” and “Medium” severity vulnerabilities before achieving a passing scan.

4. Dispute Resolution

  • If the customer disputes any findings, they must provide evidence to the ASV, which evaluates the dispute and updates the report accordingly.

5. Rescan and Final Reporting

  • A rescan is conducted to verify that vulnerabilities have been resolved. The final report is then submitted, indicating whether the scan passed or failed.

Note: To be considered compliant with the external vulnerability scanning requirement of PCI DSS Requirement 11.3.2, the scan customer infrastructure must be tested and shown to be compliant in accordance with this document and applicable ASV Program requirements. Compliance with this external vulnerability scanning requirement only represents compliance with PCI DSS Requirement 11.3.2 and does not represent or indicate compliance with any other PCI DSS requirement.


Scan Reporting: What to Expect

A comprehensive scan report is a cornerstone of the ASV Program, providing critical insights into an entity’s vulnerability landscape. The report comprises three main sections:

1. Attestation of Scan Compliance

  • This summary indicates whether the scanned infrastructure met the PCI DSS requirements and achieved a passing scan. It includes details about the scan scope, the number of components scanned, and the compliance status.

2. ASV Scan Report Summary

  • A high-level summary of vulnerabilities by component, listing compliance-impacting issues and their remediation status. This section also includes “Special Notes to Scan Customer,” highlighting potential risks even if they do not result in automatic failure.

3. ASV Scan Vulnerability Details

  • A detailed listing of all vulnerabilities detected during the scan, including severity levels, CVE identifiers, CVSS scores, and compliance status. The report also lists open ports and services detected during the scan.

Vulnerability Severity Levels and Compliance

Vulnerabilities identified during ASV scans are categorized by their severity, which determines their impact on compliance:

  • High Severity (CVSS Score: 7.0-10.0): Failing vulnerabilities that must be remediated immediately.
  • Medium Severity (CVSS Score: 4.0-6.9): Failing vulnerabilities that require remediation before achieving a passing scan.
  • Low Severity (CVSS Score: 0.0-3.9): Passing vulnerabilities that do not impact compliance but should still be addressed to improve security.

Special Notes to Scan Customers

The scan report may include “Special Notes” for specific configurations or software that pose risks to the CDE. These notes do not result in automatic failure but require the customer to justify the presence of such configurations and confirm their secure implementation.

Examples of “Special Notes” include:

  • Embedded scripts on payment pages
  • Remote access software
  • Insecure services or protocols

The ASV must obtain the customer’s declaration for each special note before issuing a passing scan report.


FAQ

What is the PCI ASV Program?

The PCI ASV Program is a certification framework designed by the Payment Card Industry Security Standards Council (PCI SSC). It certifies organizations known as Approved Scanning Vendors (ASVs) to conduct external vulnerability scans of merchants and service providers. These scans are required as part of PCI DSS Requirement 11.3.2 to ensure compliance and maintain the security of cardholder data environments (CDEs).

What does an ASV do?

An Approved Scanning Vendor is responsible for conducting external vulnerability scans using validated scanning tools and methodologies. They help merchants and service providers identify system vulnerabilities, assess compliance with PCI DSS Requirement 11.3.2, and provide reports detailing findings and remediation steps.

Who needs to engage an ASV?

Any merchant or service provider that processes, stores, or transmits cardholder data and has external-facing systems or components connected to the internet must engage an ASV to perform quarterly external vulnerability scans.

Why is the ASV Program important?

The ASV Program ensures that businesses regularly assess their internet-facing systems for vulnerabilities. External scans help identify potential weaknesses before attackers can exploit them, reducing the risk of data breaches and non-compliance penalties.

ASV Scanning and Scope

What is the scope of an ASV scan?

The scope of an ASV scan includes all internet-facing system components that are either part of the cardholder data environment (CDE) or could provide a path to the CDE. This includes:

  • Web servers
  • Mail servers
  • Load balancers
  • Virtualization components
  • Cloud-based infrastructure
  • Remote access software
  • Any system or service that interacts with the CDE
Can a merchant or service provider perform their own external scans?

No, PCI DSS requires that a PCI SSC-certified ASV perform external vulnerability scans. While merchants or service providers may use internal tools for additional internal scans, only ASVs are authorized to perform external scans for compliance purposes.

What happens if a business excludes certain components from an ASV scan?

If a component is excluded from the scan scope but later becomes the source of a data breach, the scan customer (merchant or service provider) is held accountable. Proper segmentation and scoping are critical to ensuring compliance and security.

How are vulnerabilities categorized in an ASV scan?

Vulnerabilities are categorized using the Common Vulnerability Scoring System (CVSS) and assigned a severity level:

  • High Severity (CVSS 7.0–10.0): Failing vulnerabilities that must be remediated immediately.
  • Medium Severity (CVSS 4.0–6.9): Failing vulnerabilities that must be addressed to achieve compliance.
  • Low Severity (CVSS 0.0–3.9): Passing vulnerabilities that do not impact compliance but should still be remediated to improve security.
Can I do a sample?

No. You must include all external systems components that are in the CDE, provide access to the CDE, or could impact its security.

Scan Reporting and Compliance

What does an ASV scan report include?

An ASV scan report is divided into three main sections:

  • Attestation of Scan Compliance: A summary indicating whether the scan customer achieved a passing scan.
  • ASV Scan Report Summary: A list of vulnerabilities by component, showing compliance-impacting issues and remediation status.
  • ASV Scan Vulnerability Details: A detailed breakdown of all detected vulnerabilities, including severity levels, CVSS scores, and compliance status.
What are “Special Notes to Scan Customers”?

Special Notes are used to highlight specific configurations or software that may pose a risk to the CDE even if they do not result in an automatic failure. For example, the presence of remote access software or embedded payment page scripts may require the merchant to justify their use and confirm secure implementation.

What happens if an ASV scan fails?

If a scan fails due to high or medium-severity vulnerabilities, the scan customer must address the noted issues and request a rescan. Multiple scans may be aggregated to demonstrate that all vulnerabilities have been resolved during the scan period.

Can false positives be disputed?

Yes. If a scan customer believes a vulnerability has been incorrectly reported (false positive), they can provide evidence to the ASV for review. The ASV must investigate and update the scan report accordingly.

Technical and Security Considerations

What are some examples of vulnerabilities that result in an automatic failure?

Automatic failures occur when vulnerabilities violate PCI DSS requirements. Examples include:

  • The presence of SSL or early TLS protocols.
  • Open databases accessible from the internet.
  • Default or vendor-supplied passwords.
  • Unrestricted DNS zone transfers.
  • Directory browsing is enabled on web servers.
How does the ASV handle active protection systems like firewalls or intrusion prevention systems?

Active protection systems that interfere with scans may result in inconclusive or failed scans. The scan customer must work with the ASV to temporarily adjust configurations to allow the scan to complete without interference.

Are payment page scripts in scope for ASV scans?

Yes, payment page scripts that are loaded and executed in the consumer’s browser are within scope. However, these scripts must be validated for secure implementation to minimize the risk of data exfiltration or malicious modifications.

Additional Questions

How often must ASV scans be performed?

ASV scans must be conducted at least once every three months, aka “quarterly,” as being ‘At least once every 90 to 92 days, or on the nth day of each third month’, referred to as the “Scan Window”.

Rescans may also be required after vulnerabilities are remediated or when significant changes are made to the infrastructure.

What is the role of segmentation in ASV scans?

Proper segmentation isolates the CDE from the rest of the network, reducing the scope of PCI DSS assessments. Components excluded from the scan scope must be properly segmented and attested to by the scan customer.

Does PCI DSS require internal vulnerability scans?

Yes, PCI DSS also requires internal vulnerability scans (Requirement 11.3.1). However, internal scans are not part of the ASV Program and do not need to be conducted by an ASV.

Conclusion

The PCI ASV Program is an indispensable component of PCI DSS compliance. It ensures that vulnerabilities in external-facing systems are identified and addressed proactively. By partnering with an Approved Scanning Vendor, businesses can enhance their security posture, mitigate risks, and maintain the trust of their customers and payment partners.

However, achieving compliance is not a one-time effort. It requires ongoing vigilance, regular scans, and a commitment to addressing vulnerabilities promptly. With the right approach and the support of a qualified ASV, businesses can navigate the complexities of PCI DSS and build a secure environment for cardholder data.

By embracing the PCI ASV Program, you’re not just meeting regulatory requirements—you’re investing in your organization’s long-term security and success.

You can find a copy of the ASV Program guide on the PCI Couciles website here. All ASV customers and companies are required to read and understand the guide.

The post Understanding the PCI Approved Scanning Vendor (ASV) Program: A Comprehensive Guide appeared first on .

Uncategorized

The Convergence of Generative AI and Cybersecurity: Navigating Emerging Threats and Defenses

Generative AI is reshaping the cybersecurity landscape, enabling sophisticated threats while prompting innovative defensive measures. This reimagining of threats demands a nuanced understanding of the challenges and opportunities generative AI introduces. Below is a refined exploration of this evolving domain.

Unveiling the Threat Landscape: Generative AI in Cybersecurity

Generative AI-Powered Threats

Generative AI’s ability to create authentic-looking content opens avenues for unprecedented cyber threats:

  • Deepfakes: Manipulated videos or images that can influence public opinion or deceive individuals.
  • AI-Enhanced Phishing: Hyper-personalized attacks leveraging AI to mimic trusted sources convincingly.

The realistic nature of these AI-generated threats challenges traditional security frameworks, necessitating new detection and response strategies.

Vulnerabilities in the AI Age

AI-powered systems, while advanced, are not immune to exploitation:

  • Adversarial Attacks: Malicious inputs crafted to deceive AI algorithms.
  • AI-Generated Malware: Evasive code that can adapt to detection mechanisms.

Integrating generative AI into cybersecurity demands reevaluating defensive measures to safeguard digital infrastructure from sophisticated attacks.

Adaptive Defenses: Innovating Against AI-Driven Threats

The Evolution of Defensive Strategies

To counter generative AI threats, the cybersecurity field is advancing:

  • AI-Powered Threat Detection: Using machine learning to identify anomalies in real-time.
  • Anomaly Detection Techniques: Tailored solutions to distinguish between genuine and AI-manipulated content.

Collaboration among researchers, developers, and stakeholders fosters innovation and resilience in defense mechanisms.

Cognitive Security and Behavioral Analytics

The advent of cognitive security leverages AI to enhance threat detection:

  • Behavioral Analytics: Using generative AI to detect unusual user or network behaviors.
  • Pattern Recognition: Empowering cybersecurity teams with predictive insights to neutralize AI-driven threats proactively.

Addressing Human Vulnerabilities in Cybersecurity

The Role of Education and Awareness

The human element remains a key vulnerability in cybersecurity:

  • Training Programs: Equipping individuals to recognize AI-manipulated content and phishing attempts.
  • Cyber Hygiene: Promoting practices that reduce susceptibility to threats.

Augmenting human expertise with AI tools creates a holistic defense framework against generative AI threats.

Case Study: Deepfake CEO Fraud

In 2019, attackers used a deepfake voice to impersonate a CEO, resulting in a $243,000 financial loss. This example underscores the importance of verifying communications and integrating advanced detection systems to counter AI-enabled deception.

Ethical and Regulatory Dimensions of Generative AI in Cybersecurity

Navigating Ethical Considerations

The ethical use of generative AI in cybersecurity requires adherence to the principles of:

  • Transparency and Accountability: Ensuring AI applications are auditable and explainable.
  • Privacy Preservation: Balancing AI’s capabilities with the imperative to protect user data.

Regulatory Frameworks

Comprehensive regulations are vital to mitigating AI-generated threats:

  • Defining Permissible Use: Setting clear boundaries for AI deployment in cybersecurity.
  • Fostering Transparency: Encouraging responsible AI practices across industries.

Regulatory collaboration among governments, organizations, and experts is crucial to creating a robust framework for generative AI use.

Innovations in Cybersecurity: Staying Ahead of AI-Powered Attacks

Adversarial Training for AI Models

Adversarial training equips AI systems to resist manipulative inputs, enhancing their resilience.

Leveraging Generative AI for Defense

Generative AI can model potential threats, enabling proactive responses and better preparation against evolving attack vectors.

Case Study: Adversarial Machine Learning in Autonomous Vehicles

Research has demonstrated vulnerabilities in AI systems, such as manipulated road signs tricking autonomous vehicles. This highlights the need for robust safeguards in AI deployments.

Collaborative Efforts and Knowledge Sharing

The Power of Unified Defense

Collaboration is key to addressing generative AI threats:

  • Information Sharing: Industry-wide consortiums facilitate real-time threat intelligence exchange.
  • Interdisciplinary Partnerships: Combining expertise from AI, cybersecurity, and ethical governance strengthens defenses.

Unified vigilance and knowledge sharing amplify collective resilience against AI-enabled incursions.

Conclusion: Innovation, Security, and Responsibility in the AI Era

Generative AI presents both profound challenges and transformative opportunities in cybersecurity. Addressing these threats requires a balanced approach that combines technological innovation with ethical and regulatory stewardship. Through collaboration, adaptive strategies, and a focus on education, the cybersecurity community can build robust defenses to safeguard against the multifaceted risks of generative AI.


FAQs

  1. What is generative AI, and how does it pose cybersecurity threats? Generative AI creates realistic content that can be exploited for deepfakes, phishing, and malware, challenging traditional cybersecurity defenses.
  2. How can cybersecurity professionals detect AI-generated threats? Advanced techniques like anomaly detection, adversarial training, and AI-based behavioral analytics help identify and mitigate threats.
  3. What are adversarial attacks in the context of AI? Adversarial attacks involve manipulating inputs to deceive AI systems, highlighting the need for robust model training and monitoring.
  4. What role do regulations play in managing AI-powered cybersecurity risks? Regulations ensure responsible AI use, define permissible applications, and promote transparency to mitigate risks.
  5. How can organizations combat deepfake threats? To reduce susceptibility to these attacks, organizations can leverage AI detection tools, educate employees, and adopt verification protocols.

If you want to read more about this topic and more, check out my book Humanity & Machines: A Guide to our Collaborative Future with AI.

The post The Convergence of Generative AI and Cybersecurity: Navigating Emerging Threats and Defenses appeared first on .

Uncategorized

Navigating the Complex Dance of Innovation and Regulation: Why Disruption Must Embrace Compliance

When most people think about disruption in business and technology, they imagine breakthrough innovations and radical new ideas. However, after spending three decades helping companies navigate the intersection of innovation and regulation, I’ve learned that successful disruption isn’t just about breaking things – it’s about breaking things responsibly.

Let me share a story that really drives this home. A few years back, I worked with a promising fintech startup that had developed an incredible new payment processing system. The technology was revolutionary, the team was brilliant, and the market opportunity was massive. There was just one small problem: they’d completely overlooked regulatory requirements. The result? Months of delays, hefty fines, and a painful restructuring that could have been avoided with proper compliance planning.

The Reality Check

Here’s the truth that many innovators don’t want to hear: disruption doesn’t exist in a vacuum. Every groundbreaking idea exists within a framework of laws, regulations, and enforcement mechanisms designed to protect consumers, ensure fair competition, and maintain market stability.

Think about it this way: if you’re building a house, you must follow building codes. They might seem restrictive, but they exist to ensure the house doesn’t collapse. The same principle applies to business innovation.

Key Areas Where Compliance Matters

  1. Data Privacy and Protection
    In today’s digital world, data is gold. But with great data comes great responsibility. Companies need to understand and comply with:
    • GDPR, CCPA, and other privacy regulations
    • Industry-specific data protection requirements
    • International data transfer regulations
  2. Financial Services and Banking
    The financial sector is perhaps the most heavily regulated, with good reason. Key considerations include:
    • Anti-money laundering (AML) requirements
    • Know Your Customer (KYC) protocols
    • Securities regulations
    • Payment processing rules
  3. Consumer Protection
    No matter how innovative your product or service, you can’t ignore:
    • Truth in advertising requirements
    • Product safety standards
    • Fair lending practices
    • Warranty obligations

The Cost of Non-Compliance

Let’s talk numbers for a moment. Noncompliance costs aren’t just about fines (though those can be substantial). The actual costs include:

  • Legal expenses and settlements
  • Reputation damage
  • Lost business opportunities
  • Time and resources spent on remediation
  • Potential criminal penalties

Smart Disruption: A Better Approach

So, how do successful companies balance innovation with compliance? Here’s what I’ve seen work:

  1. Build Compliance into Innovation
    Don’t treat compliance as an afterthought. Make it part of your development process from day one. This means:
    • Involving legal and compliance teams early
    • Understanding regulatory requirements before building solutions
    • Designing systems with compliance in mind
  2. Stay Ahead of Regulatory Changes
    Regulations evolve constantly. Successful disruptors:
    • Monitor regulatory developments
    • Participate in industry groups
    • Maintain open dialogue with regulators
    • Plan for future compliance requirements
  3. Create a Culture of Compliance
    This isn’t just about rules and procedures. It’s about:
    • Training employees at all levels
    • Encouraging ethical decision-making
    • Rewarding compliance-conscious behavior
    • Making compliance part of your company’s DNA

Real-World Success Stories

I’ve seen companies turn compliance into a competitive advantage. One healthcare technology firm I worked with made HIPAA compliance a key selling point, using its robust privacy protections to win business from more established competitors. Another company in the cryptocurrency space proactively developed compliance frameworks that later became industry standards.

Looking Forward

As technology advances and markets become more complex, the relationship between disruption and compliance will only become more critical. Successful innovators will be those who understand that compliance isn’t a barrier to disruption—it’s an essential component of sustainable innovation.

The Bottom Line

Here’s the bottom line: true disruption isn’t about breaking the rules. It’s about finding better ways to achieve objectives while respecting necessary protections. It’s about being smart, not revolutionary.

Remember, the goal isn’t to avoid regulation – it’s to innovate within its framework while helping shape its evolution. That’s how you create lasting change that benefits everyone.

A Final Thought

If you’re working on something disruptive (and these days, who isn’t?), take a step back and ask yourself: Have we considered the compliance implications? Are we building something that can scale within regulatory frameworks? Are we creating sustainable innovation or just temporary disruption?

The answers to these questions might just be the difference between being a footnote in history and changing the world.

After all, the most successful disruptors aren’t just the ones who think outside the box – they’re the ones who understand why the box exists in the first place.

The post Navigating the Complex Dance of Innovation and Regulation: Why Disruption Must Embrace Compliance appeared first on .

Uncategorized

The Nexus of Generative AI-Powered Threats and Cybersecurity Defenses

In the wake of the proliferation of generative AI technologies, the cybersecurity landscape finds itself at a critical juncture, navigating the emergence of novel threats and the imperative to fortify defenses against AI-powered attacks. This chapter delves into the dynamic interplay between generative AI-powered threats and the evolving strategies for cybersecurity defense, shedding light on the intricate challenges and opportunities that define this intersection.

Unmasking Generative AI-Powered Threats

Generative AI, with its capacity to synthesize realistic content and manipulate digital information, has opened unforeseen avenues for malicious actors to orchestrate sophisticated cyber-attacks. From AI-generated deepfake videos that can manipulate public discourse and deceive individuals to AI-aided phishing attacks that exploit human vulnerabilities, the spectrum of generative AI-powered threats poses a formidable challenge to traditional cybersecurity defenses. The nuances of these threats, often cloaked in the veneer of authenticity and realism, necessitate a paradigm shift in cybersecurity strategies and threat detection methodologies.

Vulnerabilities in the Age of Generative AI

The infusion of generative AI into the cybersecurity domain has brought to the forefront an array of vulnerabilities that demand meticulous scrutiny. Adversarial attacks, wherein AI-generated inputs are engineered to deceive machine learning algorithms, underscore the susceptibility of AI systems to manipulation. Moreover, the potential for AI-generated malware and stealthy cyber intrusions heightens the complexity of safeguarding digital assets and infrastructures. As the boundaries between genuine and AI-fabricated content blur, the traditional tenets of cybersecurity defense confront unprecedented challenges.

The Cat-and-Mouse Game: Adapting Cybersecurity Defenses

In response to the evolving landscape of generative AI-powered threats, cybersecurity professionals and researchers are engaged in a relentless pursuit of adaptive defense mechanisms. Advanced threat detection systems leveraging machine learning and AI, anomaly detection techniques tailored to discern AI-generated content, and robust authentication protocols represent pivotal facets of the evolving cybersecurity arsenal. Additionally, the collaborative efforts of industry stakeholders, cybersecurity experts, and AI developers are essential in fostering a proactive ecosystem for anticipating and mitigating generative AI-powered threats.

Ethical Implications and Regulatory Imperatives

The deployment of generative AI in the context of cyber threats amplifies the ethical and regulatory considerations that underscore its application. The responsible use of generative AI for cybersecurity purposes, the imperative to uphold privacy and data integrity, and the ethical ramifications of leveraging AI in offensive cyber operations necessitate a comprehensive framework for ethical governance. Regulatory imperatives aimed at mitigating the risks posed by AI-generated threats, fostering transparency in AI applications, and delineating the boundaries of permissible use are pivotal in shaping the ethical contours of this paradigm.

As we navigate the intricate terrain of generative AI-powered threats and the evolving strategies for cybersecurity defense, it becomes evident that the symbiosis of innovation and security demands a proactive and adaptive stance. In the ensuing chapters, we will delve deeper into the proactive measures and emerging technologies that underpin cybersecurity defenses against generative AI-powered threats, illuminating the dynamic interplay between innovation, resilience, and responsible stewardship in the digital realm.

Innovations in Cybersecurity Defense

Amid the evolving landscape of generative AI-powered threats, the realm of cybersecurity defense is propelled by a wave of innovations aimed at fortifying digital fortresses against AI-enabled incursions. Novel approaches such as AI-driven threat hunting, leveraging generative AI for proactive threat modeling, and the integration of adversarial training to bolster the resilience of AI systems against manipulative inputs stand as exemplars of the proactive strategies employed to preempt and counteract emerging threats. The amalgamation of human expertise and technological acumen embodies the vanguard of cybersecurity defense in the era of generative AI.

Cognitive Security and Behavioral Analytics

The convergence of generative AI and cybersecurity defense heralds the advent of cognitive security, leveraging AI algorithms to discern patterns, anomalies, and behavioral indicators that underpin threat detection. Behavioral analytics, underpinned by generative AI, offer a nuanced understanding of user behaviors, network activities, and potential incursions, empowering cybersecurity professionals with the insights necessary to preclude and mitigate AI-generated threats. The synthesis of cognitive security and behavioral analytics represents a pivotal stride in fortifying defenses against the dynamic contours of generative AI-powered threats.

Addressing the Human Element in Cybersecurity

Beyond technological fortifications, the human element in cybersecurity assumes paramount significance in the context of generative AI-powered threats. Education and awareness initiatives are tailored to equip individuals with the acumen to discern AI-manipulated content, recognize the hallmarks of AI-generated phishing attempts, and cultivate a culture of cyber hygiene that embodies indispensable facets of cybersecurity resilience. Additionally, the collaboration between human expertise and AI-augmented defenses fosters a symbiotic ecosystem that bolsters the capacity to anticipate and mitigate the evolving threat landscape.

Collaborative Imperatives and Knowledge Sharing

The ethos of collaborative imperatives permeates the fabric of cybersecurity defense in the age of generative AI-powered threats. Industry collaboration, information-sharing consortiums, and interdisciplinary partnerships form the bedrock of a proactive ecosystem that transcends organizational boundaries, engendering a collective resilience against AI-enabled incursions. The exchange of insights, threat intelligence, and best practices embodies a force multiplier in the endeavor to fortify cybersecurity defenses, underscoring the imperative of unified vigilance against the multifaceted challenges posed by generative AI-powered threats.

As we unravel the intricate interplay between generative AI-powered threats and the dynamic strategies for cybersecurity defense, it becomes evident that the synthesis of innovation, resilience, and collaborative stewardship embodies the fulcrum of cybersecurity fortification in the digital age. In the ensuing chapters, we will venture further into the ethical and regulatory considerations that underpin the application of generative AI for cybersecurity purposes, offering insights and perspectives that navigate the complex terrain of responsible stewardship and technological innovation in the digital realm.

Ethical Considerations in AI-Powered Cybersecurity

The ethical dimensions of leveraging generative AI for cybersecurity defense manifest as pivotal in navigating the intersection of innovation and responsible stewardship. Ethical frameworks underpinning the deployment of AI-driven threat detection, the responsible use of generative AI for defensive operations, and the imperative to uphold privacy and data integrity embody the ethical imperatives guiding this paradigm’s ethical contours. The ethical dimensions of leveraging generative AI in the context of cybersecurity defense necessitate a comprehensive framework for ethical governance underpinned by transparency, accountability, and the principles of responsible AI stewardship.

Regulatory Imperatives and Governance

The regulatory imperatives delineating the contours of permissible use and ethical governance in the domain of generative AI-powered cybersecurity represent a linchpin in shaping a responsible and resilient ecosystem. Regulatory frameworks aimed at mitigating the risks posed by AI-generated threats, fostering transparency in AI applications, and delineating the boundaries of permissible use embody the regulatory imperatives that underscore the responsible deployment of generative AI for cybersecurity purposes. The collaboration between regulatory bodies, industry stakeholders, and cybersecurity experts forms the nucleus of a harmonized framework that augments this paradigm’s ethical and regulatory dimensions.

As we navigate the complex terrain of generative AI-powered threats and the evolving strategies for cybersecurity defense, it becomes evident that the symbiosis of innovation, security, and responsible stewardship necessitates a comprehensive framework that navigates this paradigm’s ethical and regulatory dimensions. In the forthcoming chapters, we will delve deeper into the regulatory imperatives that underscore the deployment of generative AI for cybersecurity defense, offering insights and perspectives illuminating the dynamic interplay between innovation, governance, and responsible stewardship in the digital realm.

In the upcoming posts, we will unravel the multifaceted dimensions of generative AI’s impact on cybersecurity, examining the intricate interplay between innovation, security, and responsibility in the digital age. By delving into the ethical and regulatory considerations, we aim to illuminate the imperative of navigating the complex terrain of generative AI-powered cybersecurity with an unwavering commitment to responsible stewardship and technological innovation.


Humanity & Machines

If you want to read more about how AI and Humanity can coexist, check out my book, Humanity & Machines: A Guide to Our Collaborative Future with AI.

Get Your Copy Now:
Amazon

In Humanity & Machines: A Guide to Our Collaborative Future with AI, discover how artificial intelligence reshapes every aspect of our world—from business and healthcare to ethics and national security. This comprehensive guide takes you on a journey through the fascinating history of AI, its groundbreaking technological advancements, and the profound ethical challenges accompanying it. 

This book explores how AI can be a powerful force for good, driving economic growth, solving global problems, and enhancing human creativity. It also takes an honest look at AI’s dangers: job displacement, biased algorithms, and the risk of creating autonomous weapons. 

At the heart of the discussion is a call for responsible AI development, collaboration between humans and machines, and global cooperation. Whether you’re a professional looking to understand how AI will impact your industry or simply curious about the future, The Humanity & Machines: A Guide to Our Collaborative Future with AI provides the insights and practical advice you need to navigate the rapidly evolving AI landscape.

The post The Nexus of Generative AI-Powered Threats and Cybersecurity Defenses appeared first on .