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Data, data everywhere, and not a drop of insight. The enterprise collects terabytes of data from hundreds of different, disconnected security tools. Yet, while organizations have vast amounts of data, they struggle to be data-driven.   Internal stakeholders have their own tools to help them make tactical decisions. The compliance and audit team may use a governance, risk, and compliance (GRC) platform or Microsoft Excel. The security analysts may have a security information and event management (SIEM) tool, or two (maybe one cloud-delivered and one on-premises). The IT team might be using a ticketing system to manage issues like applying security updates to vulnerable devices. Disconnected metrics create challenges as the enterprise attempts moving from a tactical to a strategic cybersecurity program. Siloed data limits usability as collecting the required metrics and statistics is time-consuming and, often, inaccurate. Consider the following examples and how connecting these metrics would provide holistic insights:  Inability to identify and connect responsible parties to non-compliance reports identifying gaps that were addressed, prioritized, or partially resolved   No clear call to action for security analysts reviewing metrics that threat blocking and vulnerability patching  No business context connecting to technical data about networks, systems, and devices   This will help turn tactical data into strategic actions. Security data fabrics can be leveraged by enterprises for a modern data architecture that streamlines their analytics processes while providing everyone access to - and strategic insight from - the data they need.  If you’d like to learn how DataBee® from Comcast Technology Solutions can help you collect and utilize outcome-driven and actional contextual insights, we partnered with analyst firm IDC to help customers leverage a data fabric to enhance existing capabilities. Download the free report now: “IDC Spotlight: Principles of Being a Data-driven Cybersecurity Leader”. 

Why do monitoring and logging matter?   Although this is a foundational question in cybersecurity and networking, National Cybersecurity Awareness Month makes this a great time to (re)visit important topics.   Monitoring and logging are very similar to security cameras and home alarm systems. They help you keep an eye on what’s happening in your applications and systems. If – when – something unusual occurs, analysts can leverage information from monitoring and logging solutions to respond and manage potential issues.  In this blog, I explore some tips from my experience as a DevOps and Systems Engineer.  10 tips for effective monitoring and logging:  Set up alerts for unusual activity  Use monitoring tools to set up alerts for machine or human behaviors that don’t seem right. This could be, for example, a user who has experienced multiple failed logins attempts or a server with a sudden spike in traffic. This way, you can prioritize and quickly investigate suspicious activities.   If it’s important, log it  Adversaries are becoming clever in hiding their tracks. This makes logging key events, such as user logins, changes to business-critical data, and system errors, important. The information gleaned from logs can help shed light on a bad actor’s trail.  Regularly review log  Don’t just collect logs—make it a habit to review them regularly. Collaborate with your team and experts to capture and understand details from logs. Look for patterns or anomalies that could indicate a security issue.   Leverage SIEMs   Security Information and Event Management (SIEM) tools are great to collect and analyze log data from different sources, helping you detect security incidents more efficiently.   Retain logs for digital forensics  Your industry regulations may already require this, but storing your logs will not only keep you compliant but can also help you perform security investigations. SIEMs can be expensive depending on the throughput of your organization. Security data fabrics, such as DataBee, can help you decouple storage and federate security data to a centralized location like a data lake, making it easier to search through raw logs or optimized datasets to help you catch important information.  Establish a response plan  Ideally before a security event occurs, your team should have a plan in place to respond to an incident. This should include who to contact and the steps to contain any potential threats.  Educate your team  Make sure everyone on your team understands the importance of monitoring and logging. Training can help them recognize potential security threats and respond appropriately.  Keep your tools updated  Regularly update your monitoring and logging tools to ensure you’re protected against the latest threats. Outdated tools might miss important security events.  Test your monitoring setup  Running tabletops can help you test your monitoring systems and response plans to ensure they’re working correctly. Simulate incidents to see if your alerts trigger as expected.  Stay informed  Keep up to date with the latest security trends and threats. This knowledge can help you improve your monitoring and logging practices continuously.  By following these tips, you can enhance your organization's security posture and respond more effectively to potential threats. Monitoring and logging might seem like technical tasks, but they play a vital role in keeping your systems safe! 

Like many cybersecurity vendors, we like to keep an eye out for the publication of the Verizon Data Breach Investigations Report (DBIR) each year. It’s been a reliable way to track the actors, tactics and targets that have forced the need for a cybersecurity industry and to see how these threats vary from year to year. This information can be helpful as organizations develop or update their security strategy and approaches.    All of the key attack patterns reported on in the DBIR have been mapped to the Critical Security Controls (CSC) put out by the Center for Internet Security (CIS), a community-driven non-profit that provides best practices and benchmarks designed to strengthen the security posture of organizations. According to the CIS, these Controls “are a prescriptive, prioritized and simplified set of best practices that you can use to strengthen your cybersecurity posture.”  Many organizations rely on the Controls and Safeguards described in the CIS CSC document to guide how they build and measure their security program. Understanding this, we thought it might be useful to map the Incident Classification Patterns described in the 2024 DBIR report, to the guidance provided in the CIS Critical Security Controls, Version 8.1, and then to the CSC Controls and Safeguards that DataBee for Continuous Controls Monitoring (CCM) reports on. As you’ll see, CCM – whether from DataBee or another vendor (😢) – is a highly useful way to measure progress toward effective controls implementation.  The problem, proposed solutions, and how to measure their effectiveness   The 2024 DBIR identifies a set of eight patterns for classifying security incidents, with categories such as System Intrusion, Social Engineering, and Basic Web Application Attacks leading the charge. Included in the write-up of each incident classification is a list of the Safeguards from the CIS Critical Security Controls that describe “specific actions that enterprises should take to implement the control.” These controls are recommended for blocking, mitigating, or identifying that specific incident type. CIS Controls and Safeguards recommended to combat System Intrusion, for example, include: 4.1, Establish and Maintain a Secure Configuration Process1; 7.1, Establish and Maintain a Vulnerability Management Process2; and 14, Security Awareness and Skills Training3. Similar lists of Controls and Safeguards are provided in the DBIR for other incident classification patterns.   Continuous Controls Monitoring (CCM) is an invaluable tool to measure implementation for cybersecurity controls, including many of the CIS Safeguards. These might include measuring the level of deployment for a solution within a population of assets, e.g., is endpoint detection and response implemented on all end user workstations and laptops? Or has a task been completed within the expected timeframe, such as the remediation of a vulnerability, closure of a security policy exception, or completion of secure code development training? While reporting on these tasks individually may seem easy enough, CCM takes it to the next level by reporting on a large set of controls through a single interface, rather than requiring users to access a series of different interfaces for every distinct control. Additionally, CCM supports the automation of data collection and then refreshing report content so that the data being reported is kept current with significantly less effort.   Doing (and measuring) “the basics”  The CIS CSCs are divided into three “implementation groups.” The CIS explains implementation groups this way: “Implementation Groups (IGs) are the recommended guidance to prioritize implementation of the CIS Critical Security Controls.” The CIS defines Implementation Group 1 (IG1) as “essential cyber hygiene and represents an emerging minimum standard of information security for all enterprises.” In the CIS CSCs v8.1, there are 56 Safeguards in implementation group 1, slightly more than a third of the total Safeguards. Interestingly, most of the Safeguards listed by Verizon in the DBIR are from implementation group 1, the Safeguards for essential cyber hygiene, that is, “the basics.”   Considering “the basics,” a few years ago, the 2021 Data Breach Investigations Report made this point:   “The next time we are up against a paradigm-shifting breach that challenges the norm of what is most likely to happen, don’t listen to the ornithologists on the blue bird website chirping loudly that “We cannot patch manage or access control our way out of this threat,” because in fact “doing the basics” will help against the vast majority of the problem space that is most likely to affect your organization.” (page 11)  Continuous controls monitoring is ideally suited to help organizations measure their progress when implementing essential security controls. That is, those controls that will help against “the vast majority of the problem space.” These essential controls are the necessary foundation on which more specialized and sophisticated controls can be built.  Moving beyond the basics  Of course, CCM is not limited to reporting on the basics. As Verizon notes, the CIS Safeguards listed in the 2024 DBIR report are only a small subset of those which could help to protect the organization, or to detect, respond to, or recover from an incident. Any control which lends itself to measurement, especially when expressed as a percentage of implementation, is a viable candidate for CCM. Additionally, the measurement can be compared against a target level of compliance, a Key Performance Indicator (KPI), to assess if the target is being met, exceeded, or if additional work is needed to reach it.   The Critical Security Controls from CIS provide a pragmatic and comprehensive set of controls for organizations to improve their essential cybersecurity capabilities. CCM provides a highly useful solution to measure the progress towards effective implementation of the controls, both at the organization level, and the levels of management that make up the organization.   Mapping incident classification patterns to CIS controls & safeguards to DataBee for Continuous Controls Monitoring dashboards  DataBee’s CCM solution provides consistent and accurate dashboards that measure how effectively controls have been implemented, and it does this automatically and continuously. Turns out, it produces reports on many of the Controls and Safeguards detailed in the CIS CSC. Here are some examples:  The DBIR recommends Control 04, "Secure Configuration of Enterprise Assets and Software," as applicable for several Incident Classification Patterns, namely System Intrusion, and Privilege Misuse. The Secure Configuration dashboard for DataBee for Continuous Controls Monitoring reports on this CSC Control and many of its underlying Safeguards.  Control 10, “Malware Defenses,” is also listed as a response to System Intrusion in the DBIR. The Endpoint Protection dashboard supports this control. It shows the systems protected by your endpoint detection and response (EDR) solutions and compares them to assets expected to have EDR installed. DataBee reports on the assets missing EDR and which consequently remain unprotected.  “Security Awareness and Skills Training,” Control 14, is noted in the DBIR as a response to patterns System Intrusion, Social Engineering, and Miscellaneous Errors. The DataBee Security Training dashboard can provide status on training from all the sources used by your organization.  In addition to supporting the controls and safeguards listed in the DBIR, the DataBee dashboards also report on CSC controls such as Control 01, “Inventory and Control of Enterprise Assets.” While the DBIR does not list Control 01 explicitly, the information reported by the Asset Management dashboard in DataBee is needed to support Secure Configuration, Endpoint Protection, and other dashboards. That is, the dashboards that do support the CIS controls listed in the DBIR.   With the incident patterns in the 2024 Verizon Data Breach Investigations Report mapped to the Critical Security Controls and Safeguards provided by the Center for Internet Security, security teams are given a great start – or reminder – of the best practices and tools that can help them avoid falling ‘victim’ to these incidents. Continuous controls monitoring bolsters an organization’s security posture even more by delivering dashboards that report on the performance of an organization’s controls; reports that provide actionable insights into any security or compliance gaps.   If you’d like to learn more about how DataBee for Continuous Controls Monitoring supports the Controls and Safeguard recommendations provided in the CIS CSC, be in touch. We’d love to help you get the most out of your security investments. 

We are proud to announce that DataBee is recognized as one of only 35 companies to achieve the AWS Security Competency in Threat Detection and Response. We have worked diligently to help customers gain faster, better insights from their security data, making today meaningful to us as a team. This exclusive recognition underscores the value and impact that DataBee’s advanced capabilities bring to customers. Achieving an AWS Security Competency requires us to have deep technical AWS expertise. Inspired by Comcast's internal CISO and CTO organization, the DataBee platform connects disparate security data sources and feeds, enabling customers to optimize their AWS resources. Our AWS Competency recognition validates our ability to leverage our internal, technical AWS knowledge so that customers can achieve the same proven-at-scale benefits. More importantly, earning this badge is a testament to the success we have achieved in partnering with our customers, and validates that DataBee has enabled customers to transform vast amounts of security data into actionable insights for threat detection and response. Our continued collaboration with AWS reflects our dedication to driving innovation and delivering high-quality security solutions that meet the evolving needs of our customers. We are proud to be recognized for our efforts and remain committed to helping our customers achieve their security goals efficiently and effectively.

Recently, DataBee hosted a webinar focused on the Digital Operational Resilience Act (DORA), a pivotal piece of EU legislation that is set to reshape the cybersecurity landscape for financial institutions. The talk featured experts Tom Schneider, Cybersecurity GRC Professional Services Consultant at DataBee and Annick O'Brien, General Counsel at CybSafe, who delved into the intricacies of DORA, its implications, and actionable strategies for compliance. 5 Key Takeaways for mastering DORA compliance and enhancing resilience: In an effort to open dialogue and help organisations that need to comply with the DORA compliance legislations, we are sharing the takeaways from our webinar. The Essence of DORA: DORA is not just another cybersecurity regulation; it addresses the broader scope of operational risk in the financial sector. Unlike frameworks that focus solely on specific cybersecurity threats or data protection, DORA aims to ensure that organisations can maintain operational resilience, even in the face of significant disruptions. This resilience means not just preventing breaches but also being able to recover swiftly when they occur. Broad Applicability: DORA's reach extends beyond traditional banks, capturing a wide array of entities within the financial ecosystem, including insurance companies, reinsurance firms, and even crowdfunding platforms. The act emphasizes that any organisation handling financial data needs to be vigilant, especially as DORA becomes fully enforceable in January 2025. Third-Party Risks: A significant portion of the webinar focused on the risks associated with third-party service providers, particularly cloud service providers. DORA places the onus on financial institutions to ensure that their third-party vendors are compliant with the same rigorous standards. This includes having robust technical and operational measures, conducting regular due diligence, and ensuring these providers can maintain operational resilience. Concentration of Risk: DORA introduces the concept of concentration risk, which refers to the potential danger when an entire industry relies heavily on a single service provider. The webinar highlighted recent incidents, such as the CrowdStrike and Windows issues, underscoring the importance of not only identifying these risks but also diversifying to mitigate them. Principles-Based Approach: Unlike prescriptive regulations, DORA is principles-based, focusing on the outcomes rather than the specific methods organisations must use. This approach requires financial institutions to continuously assess and update their operational practices to ensure resilience in a rapidly evolving technological landscape. Moving Forward: As the January 2025 deadline approaches, organisations are urged to review their existing compliance frameworks and identify how they can integrate DORA's requirements without reinventing the wheel. Many of the principles within DORA overlap with other frameworks like GDPR and NIST, providing a foundation that organisations can build upon. For those grappling with the complexities of DORA, the webinar emphasized the importance of preparation, regular testing, and continuous improvement. By leveraging existing policies and procedures, financial institutions can align with DORA's objectives and ensure they are not only compliant but also resilient in the face of future challenges. Databee can significantly enhance compliance with DORA by streamlining the management of information and communication technology (ICT) assets. DataBee for Continuous Controls Monitoring (CCM) offering weaves together data across multiple sources, enabling organisations to automate the creation of a reliable asset inventory. By providing enriched datasets and clear entity resolution, Databee reduces complexity of managing and monitoring ICT assets, improves auditability, and ensures that compliance and security measures are consistently met across the enterprise, ultimately supporting the resilience and security of critical business operations. Watch the recording of the webinar here or request a demo today to discover how DataBee can help you become DORA compliant.

Artificial intelligence (AI) and music are a lot alike. When you have the right components together, like patterns in melodies and rhythms, music can be personal and inspire creativity. In my experience having worked on projects that developed AI for IT and security teams, data can help recognize patterns from day-to-day activities and frustrations that can be enhanced or automated. I started working in AI technology development nearly a decade ago. I loved the overlaps between music and programming. Both begin with basic rules and theory, but it is the human element that brings AI (and music) to life. Recently, we launched BeeKeeper AI™ from DataBee, a generative AI (genAI) tool that uses patent-pending entity resolution technology to find and validate asset and device ownership. Inspired by our own internal cybersecurity and operations teams struggles of chasing down ownership, which sometimes added up to 20+ asset owner reassignments, we knew there was a better way forward. Through integrations with enterprise chat clients like Teams, BeeKeeper AI uses your data to speak to your end users, replacing the otherwise arduously manual process of confirming or redirecting asset ownership. What’s the buzz about BeeKeeper AI from DataBee?   Much like how a good song metaphorically speaks to the soul, BeeKeeper AI’s innovative genAI approach is tuned to leverage ownership confidence scores that prompt it to proactively reach out to end users. Now, IT admins and operations teams don’t have to spend hours each day reaching out to asset owners who often become frustrated over having their day interrupted. Further, by using BeeKeeper AI for ‘filling in the blanks’ of unclaimed or newly discovered assets, you have an improved dataset of who to reach out to when security vulnerabilities and compliance gaps appear. BeeKeeper AI, a part of DataBee for Security Hygiene and Security Threats, uses an entity resolution technology to identify potential owners for unclaimed assets and devices based on a few factors such as comparing authentication logs. BeeKeeper AI is developed with a large language model (LLM) that features strict guardrails to keep conversations on track and hallucinations at bay when engaging these potential owners. This means that potential asset owners can simply respond “yes” or suggest someone else and move on with their day. Once users respond, BeeKeeper AI can do the rest – including looking for other potential owners, updating the DataBee platform, and even updating the CMDB, sharing its learnings with other tools. Automatic updates to improve efficiency and collaboration  Most IT admins and operations teams heave a sigh every time they have to manually update their asset inventories. If you’ve been using spreadsheets to maintain a running, cross-referenced list of unclaimed devices and potential owners, then you’re singing the song of nearly every IT department globally.   This is where BeeKeeper AI harmonizes with the rest of your objectives. When BeeKeeper AI automatically updates the DataBee platform, everyone across the different teams have a shared source of data, including:  IT  Operations  Information security  Compliance   Unknown or orphaned assets are everyone’s responsibility as they can become a potential entry point for security incidents or create compliance gaps. BeeKeeper AI can even give you insights from its own activity, allowing you to run user engagement reports to quantify issues like:   Uncooperative users   Total users contacted and their responses  Processed assets, like validated and denied assets  Since it automatically updates the DataBee platform, BeeKeeper AI makes collaboration across these different teams easier by ensuring that they all have the same access to cleaner and more complete user and asset information that has business context woven in. Responsible AI for security data  AI is a hot topic, but not all AI is the same. At DataBee, we believe in responsible AI with proper guardrails around the technology’s use and output. As security professionals, we understand that security data can contain sensitive information about your people and your infrastructure. BeeKeeper AI starts from your clean, optimized DataBee dataset and works within your contained environment. Unique to each organization’s data, BeeKeeper AI’s guardrails keep sensitive data from leakage. This is why BeeKeeper AI sticks to what it knows, even when someone tries to take it off task. Our chatbot isn’t easily distracted and refocuses attempts to engage back to its sole purpose - identifying and finding the right asset owners. Making honey out of your data with BeeKeeper AI  BeeKeeper AI leverages your security data to proactively reach out to users and verify whether they own assets. With DataBee, you can turn your security data into analytics-ready datasets to get insights faster. Let BeeKeeper AI manage your hive so you can focus on making honey out of your data. If you’re ready to reduce manual, time-consuming, collaboration-inhibiting processes, request a custom demo to see how DataBee for Security Hygiene can help you sing a sweeter tune.

2024 has been a big “events” year for DataBee as we’ve strived to raise awareness of the new business and the DataBee Hive™ security, risk and compliance data fabric platform. We’ve participated in events across North America and EMEA including Black Hat USA, the Gartner Security & Risk Management Summits, FS-ISAC Summit, Snowflake Data Cloud Summit and AWS re:Inforce, and of course, the RSA Conference. At RSA, we introduced to the community our sweet (haha) and funny life-size bee mascot, who ended up being a big hit among humans and canines alike. Participation in these events has been illuminating on many important fronts. For the DataBee “hive” it’s been invaluable, not only for the conversations and insights we gain from real users across the industry, but also for the feedback we receive as we share the story of DataBee’s creation and how it was inspired by the security data fabric that Comcast’s Global CISO, Noopur Davis, and her team developed. In general, we’ve been thrilled with the response that DataBee has received, but consistently, there’s one piece of attendee feedback that really gives us pause: “Why would Comcast Technology Solutions enter the cybersecurity solutions space?” In other words, “what the heck is Comcast doing here?” This statement makes it pretty clear: Comcast might be synonymous with broadband, video, media and entertainment services and experiences, but may be less associated with cybersecurity. But it should be. While Comcast and Xfinity may not be immediately associated with cybersecurity, Comcast Business, a $10 billion business within Comcast, has been delivering advanced cybersecurity solutions to businesses of all sizes since 2018. With our friends at Comcast Business, the DataBee team is working hard to change perceptions and increase awareness of Comcast’s rich history of innovation in cybersecurity. Let’s take a quick look at some of the reasons why the Comcast name should be synonymous with cybersecurity Comcast Business Comcast Business is committed to helping organizations adopt a cybersecurity posture that meets the diverse and complex needs of today’s cybersecurity environment. Comcast Business’ comprehensive solutions portfolio is specifically engineered to tackle the multifaceted challenges of the modern digital landscape. With advanced capabilities ranging from real-time threat detection and response, Comcast Business solutions help protect businesses. Whether through Unified Threat Management systems that simplify security operations, cloud-based solutions that provide flexible defenses, or DDoS mitigation services that help preserve operational continuity, Comcast Business is a trusted partner in cybersecurity. Comcast Business provides the depth, effectiveness, and expertise necessary to enhance enterprise security posture through: SecurityEdge™ Offering advanced security for small businesses, SecurityEdge™ is a cloud-based Internet security solution that helps protect all connected devices on your network from malware, phishing scams, ransomware, and botnet attacks. SD-WAN with Advanced Security Connect users to applications securely both onsite and in the cloud Unified Threat Management (UTM) Delivered by industry leading partners, UTM solutions provide an integrated security platform that combines firewall, antivirus, intrusion prevention, and web filtering to simplify management and enhance visibility across the network. DDoS Mitigation Security for disruption caused by Distributed Denial of Service attacks by helping to identify and block anomalous spikes in traffic while allowing for desired functionality of your services. Secure Access Service Edge (SASE) Integrating networking and security into a unified cloud-delivered service model, our SASE framework supports dynamic secure access needs of organizations, facilitating secure and efficient connectivity for remote and mobile workers. Endpoint Detection and Response (EDR) Help safeguard devices connected to your enterprise network, using AI to detect, investigate, remove, and remediate malware, phishing, and ransomware Managed Detection and Response (MDR) Extend EDR capabilities to the entire network and detect advanced threats, backed up with 24/7 monitoring by a team of cybersecurity experts. Vulnerability Scanning and Management Helps identify and manage security weaknesses in the network and software systems, a proactive approach that helps protect potential entry points for threat actors. Comcast Ventures Did you know that Comcast has a venture capital group that backs early-to-growth stage startups that are transforming sectors like cybersecurity, AI, healthcare, and more? Some of the innovative cybersecurity, data and AI-specific companies that Comcast Ventures has invested in include: BigID SafeBase HYPR Resemble AI Bitsight Uptycs Recently, cybersecurity investment and advisory firm NightDragon announced a strategic partnership with Comcast Technology Solutions (CTS) and DataBee that also included Comcast Ventures. As a result of this strategic partnership, CTS, Comcast Ventures and DataBee will gain valuable exposure to the new innovations coming from NightDragon companies. Comcast Cybersecurity As I write this, Comcast Corporation is ranked 33 on the Fortune 500 list, so – as you might guess – it has an expansive internal cybersecurity organization. With $121 billion+ in annual revenues, over 180,000 employees around the globe, and a huge ecosystem of consumers and business customers and partners, Comcast takes its security obligations very seriously. Our cyber professionals collectively hold and are awarded multiple patents each year. We lead standards bodies, and we participate and provide leadership in multiple policy forums. Our colleagues contribute to Open-Source communities where we share our security innovations. We are an integral part of the global community of cybersecurity practitioners – we present at conferences, learn from our peers, hold multiple certifications, and publish in various journals. We are a contributing member of the Communications ISAC, and the CISA Joint Cyber Defense Collaborative. A sampling of internal research and development efforts within Comcast’s cybersecurity organization include: One-time secure secrets sharing Security data fabric (Note: the inspiration for DataBee®) Anomaly detection AI-based secrets detection in code AI-based static code analysis for privacy Crypto-agility risk assessment Machine-assisted security threat modeling Scoping of threats against AI/ML apps Persona-based privacy threat modeling PKI and token management systems Certificate lifecycle management and contribution to industry IoT stock R&D for BluVector Network Detection and Response (NDR) product The Comcast Cyber Security (CCS) Research team, “conducts original applied and fundamental cybersecurity research”.  Selected projects that the team is working on include research on security and human behavior, security by design, and emerging technologies such as post quantum cryptography. CCS works with technology teams across Comcast to identify and explore security gaps in the broader cyber ecosystem. The Comcast Cybersecurity team’s work developing and implementing a security data fabric platform was the inspiration for what has become DataBee. Although the DataBee team has architected and built its commercial DataBee Hive™ security, risk and compliance data fabric platform from “scratch” (so to speak), it was Comcast’s internal platform – and the great results that it has, and continues, to deliver – that proved such a solution could be a game-changer, especially for large, complex organizations. While DataBee Hive has been designed to address the needs and scale of any type of enterprise or IT architecture, we were fortunate to be able to tap into the learnings that came from the years and countless person hours of development that went into building Comcast’s internal security data fabric platform, and then operating it at scale. DataBee Cybersecurity Suite Besides being home to the DataBee Hive security data fabric platform and products, it’s worth noting that the DataBee business unit of Comcast Technology Solutions is also home to BluVector, an on-premises network detection and response (NDR) platform. Comcast acquired BluVector in 2019, which was purpose-built to protect critical government and enterprise networks. BluVector continues to deliver AI-powered NDR for visibility across network, devices, users, files, and data to discover and hunt skilled and motivated threats. Comcast and cybersecurity? Of course. So, the next time you come across DataBee, from Comcast Technology Solutions, and you think to yourself “why is Comcast in the enterprise security market with DataBee?!” – think again. From small and mid-size organizations to large enterprises and government agencies; and from managed services to products and solutions; and from on-premises to cloud-native… Comcast’s complete cybersecurity “portfolio” covers the gamut. Want to connect with someone to determine what’s right for your organization? Contact us, and in “Comments”, let us know if you’d like to evaluate solutions from both DataBee and Comcast Business. We’ll look forward to exploring options with you!

If the proverb is, it takes a village to raise a child, then the corollary in the business world is that it takes a village to get compliance right. And in this analogy, compliance officers are the mayor of this village. Compliance officers schedule audits, coordinate activities, oversee processes, and manage documentation. They are the often-unsung heroes whose work acts as the foundation of your customers’ trust, helping you achieve certifications and mitigate risk. While your red teamers and defenders get visibility because they sit at the frontlines, your compliance team members are strategizing and carving paths to reduce risk and enable programs. For this National Compliance Officer Day, we salute these mayors of the compliance village in their own words. Feeling Gratitude There is a great amount of pride when compliance officers are able to help you build trust with your customers, but there is also an immense amount of gratitude from the compliance teams  for the internal relationships built within the enterprise Yasmine Abdillahi, Executive Director of Security Risk and Compliance and Business Information Security Officer at Comcast, expressed gratitude for executive leader Sudhanshu Kairab whose ability to grasp the core business fundamentals have allowed Comcast to implement robust compliance frameworks that mitigate risks and support growth and trust. “[Sudhanshu] consistently demonstrates a keen awareness of industry trends, enabling us to stay ahead of emerging challenges and opportunities. His ability to sustain and nurture a strong network, both internally and externally, has proven invaluable in fostering collaboration and ensuring we remain at the forefront of GRC best practices. His multifaceted approach to leadership has not only strengthened our risk posture but has also positioned our GRC function as a key driver of innovation and business growth.” Compliance professionals rely on their strategic internal business partners to succeed. When enterprise leaders empower the GRC function, compliance and risk managers can blossom into their best business enabling selves. In return, compliance leaders allow the enterprise to provide customers with the assurance they need. In today’s “trust but verify” world, customers trust the business when the compliance function can verify the enterprise security posture. Collaboration, Communication, and Education At its core, your compliance team acts as the communications glue that binds together the various cybersecurity functions. For Tom Schneider, who is a part of the DataBee team as a Cybersecurity GRC Professional Services Consultant, communication has been essential to his career. When working to achieve compliance with a control, communicating clearly and specifically is critical, especially when cybersecurity is not someone’s main responsibility. Clear communication educates both sides of the compliance equation. “Throughout my career, I have learned from the many people I’ve worked with. They have included management, internal and external customers, and auditors. I’ve learned from coworkers that were experts in some specific technology or process, such as vulnerability management or identity management, as well as from people on the business side and how things appear from their perspective.” GRC’s cross-functional nature makes compliance leaders some of the enterprise’s most impactful teachers and learners. Compliance officers collaborate across different functions - security, IT, and senior leadership. As they learn from their internal partners, they, in turn, educate others. Compliance officers are so much more than the controls they document and the checklists they review. They facilitate collaboration because they can communicate needs and build a shared language. Compliance Officers: Keeping It All Together A compliance officer’s role in your organization goes far beyond their job descriptions. They are cross-functional facilitators, mentors, learners, leaders, enablers, and reviewers. They are the ones who double check the organization’s cybersecurity work. Every day, they work quietly in the background, but for one day every year, we have the opportunity to let them know how important they are to the business. DataBee from Comcast Technology Solutions gives your compliance officer a way to keep their compliance and business data together so they can communicate more effectively and efficiently. Our security data fabric empowers all three lines of defense - operational managers, risk management, and internal audit - so they can leave behind spreadsheets and point-in-time compliance  reporting relics of the past. By leveraging the full power of your organization’s data, compliance officers can implement continuous controls monitoring (CCM) with accurate compliance dashboard and reports for measuring risk and reviewing controls’ effectiveness. From our Comcast compliance team to yours, thank you for all you do. We see you and appreciate you - today and every day.

For planning compliance with the Payment Card Industry Data Security Standard (PCI DSS), the PCI Security Standards Council (SSC) supplies a document that provides excellent foundational advice for both overall cybersecurity, and PCI DSS compliance. Organizations may already be aware of it, but regardless, it is a useful resource. And, it is interesting to read with Continuous Controls Monitoring (CCM) in mind. The document lists 10 Recommendations for best practices which are useful, not just for PCI DSS compliance, but for overall security and compliance with organizational policies as well as frameworks and regulations to which the entity is subject. The best practices place a strong emphasis on ongoing, continuous compliance. That is, for organizations “to protect themselves and their customers from potential losses or damages resulting from a data breach, they must strive for ways to maintain a continuous state of compliance throughout the year rather than simply seeking point-in-time validation.” While the immediate goal may be to attain a compliant Report on Compliance (ROC), that immediate goal, and the longer-term viability of the security program, are aided by establishing a program around continuous compliance and the ability to measure it. Here are the SSC’s 10 Best Practices for Maintaining PCI DSS Compliance: Develop and Maintain a Sustainable Security Program Develop Program, Policy, and Procedures Develop Performance Metrics to Measure Success Assign Ownership for Coordinating Security Activities Emphasize Security and Risk Management to Attain and Maintain Compliance Continuously Monitor Security Controls Detect and Respond to Security Control Failures Maintain Security Awareness Monitoring Compliance of Third-Party Service Providers Evolve the Compliance Program to Address Changes Some detail around the 10 The first recommendation, “Develop and Maintain a Sustainable Security Program” is short, but notes that, “Any cardholder data not deemed critical to business functions should be removed from the environment in accordance with the organization’s data-retention policies… In addition, organizations should evaluate business and operating procedures for alternatives to retaining cardholder data.” Outsourcing the processing of cardholder data to entities that specialize in this work is an option that many organizations take. When that is not a viable option, minimizing the amount of data collected, and securely deleting it as specified in the organization’s data retention policy is the next best option. “Develop Program, Policy, and Procedures” is the second recommendation. Along with developing and maintaining these documents, accountability must be assigned “to ensure the organization's sustainable compliance.” Additionally, PCI DSS v4.0 has a requirement under each of the twelve principal requirements stating that “Roles and responsibilities for performing activities” for each principal requirement “are documented, assigned, and understood.” If this role does not already exist, something for organizations to consider would be designating a “compliance champion” for each business unit. The compliance champions could work with their management to assume accountability for the control compliance for assets and staff assigned to the business unit. “Develop Performance Metrics to Measure Success” follows. This recommendation includes “Implementation metrics” (which measure the degree to which a control has been implemented, and are usually described as percentages), and “Efficiency and Effectiveness Measures” (which evaluate attributes such as completeness, consistency, and timeliness). These metrics show if a control has been implemented over the expected range of the organization’s assets, if it has been implemented consistently, and is being executed when expected. These metrics play a key role in assessing compliance in a continuous way. Measurement of implementation metrics and effectiveness metrics for completeness and consistency are core components of DataBee for CCM. For example, in the case of Asset Management, users can see if assets in scope for PCI DSS are flagged as being in scope correctly, if the asset owner is accurate, and if other data points such as physical location are present. The ability to see continuously refreshed data on a CCM dashboard, as opposed to having to create a point in time report, or have the knowledge to access this data through a product specific portal, makes it practical for teams to see accurate metrics in an efficient way. The fourth recommendation is to “Assign Ownership for Coordinating Security Activities.” An “individual responsible for compliance (a Compliance Manager)” is the main point of this recommendation. However, the recommendation notes that Compliance Manager should be “given adequate funding and resources… and granted the proper authority to effectively organize and allocate such resources.” The effective organization of resources could include delegating tasks throughout the organization to managers over units within the larger organization. This recommendation ends by noting that the organization must ensure that “the goals and objectives of its compliance program are consistently achieved despite changes in program ownership (i.e., employee turnover, change of management, organization merger, re-organization, etc.). Best practices include proper knowledge transfer, documentation of existing controls and the associated responsible individual(s) or team(s).” Using the DataBee for CCM dashboards to assign accountability for assets and staff to the appropriate business units helps with this recommendation. It clarifies the delegation of responsibility for assets and staff to the business unit’s management. Furthermore, it would help drive the effective achievement of objectives of the compliance program during transitions in the Compliance Manager role. Delegation of control compliance to the business unit’s management would enable them to continue with their tasks while a new Compliance Manager is hired and during the time needed for the Compliance Manager to adjust to their role. “Emphasize Security and Risk Management to Attain and Maintain Compliance,” the fifth recommendation asserts that “PCI DSS provides a minimum set of security requirements for protecting payment card account data…,” and that “Compliance with industry standards or regulations does not inherently equate to better security.” This point cannot be emphasized highly enough: “A more effective approach is to focus on building a culture of security and protecting an organization’s information assets and IT infrastructure and allow compliance to be achieved as a consequence.” The ongoing measurement of control implementation by CCM supports a culture of security. Organizations can use the information provided by DataBee for CCM to not only enable continuous reporting, but through it to support continuous remediation of control failures. The next recommendation, “Continuously Monitor Security Controls,” describes how “the use of automation in both security management and security-control monitoring can provide a tremendous benefit to organizations in terms of simplifying monitoring processes, enhancing continuous monitoring capabilities, and minimizing costs while improving the reliability of security controls and security-related information.” Ongoing monitoring of data that is frequently refreshed can be a core component for ongoing compliance. Ultimately, implementing a continuous controls monitoring program will help reduce extra workload as the PCI DSS assessment date approaches. DataBee for CCM is a tool that supports the necessary continuous monitoring. The seventh recommendation, “Detect and Respond to Security Control Failures,” applies to two situations: controls which have failed, but with no detectable consequences, and control failures that escalate to security incidents. PCI SSC notes that, “The longer it takes to detect and respond to a failure, the higher the risk and potential cost of remediation.” Continuous monitoring can help the organization to reduce the time it takes to detect a failed control. Recommendation eight, “Maintain Security Awareness” speaks to the need to train the workforce, especially regarding how to respond to social engineering. Security training, both for the staff in general and role-based training for specific teams, is one of the requirements that DataBee for CCM reports on through its dashboards. Recommendation nine is “Monitoring Compliance of Third-Party Service Providers,” and ten is “Evolve the Compliance Program to Address Changes.” A robust compliance program that is in place throughout the year can be more capable of evolving and adapting to change than an assessment focused program that allows controls to drift out of compliance between assessments. Continuous monitoring is key for combating compliance drift once an assessment has been completed. After the ten recommendations, the main body of the document concludes with a section about the “Commitment to Maintaining Compliance.” Two of the key actions for maintaining continuous compliance are, “Assigning responsibility for ensuring the achievement of their security goals and holding those with responsibility accountable,” and “Developing tools, techniques, and metrics for tracking the performance and sustainability of security activities.” DataBee for CCM enables both these tasks. The main theme of the “Best Practices for Maintaining PCI DSS Compliance” is that continuous compliance with PCI DSS that is maintained throughout the year is the goal. Ultimately, this helps improve the overall security posture of the organization. Making the required compliance activities business as usual tasks that are continuous throughout the year can also help with the specific goal of achieving a compliant result for a PCI DSS assessment when it comes due. How DataBee for CCM fits in We envisioned and realized DataBee for CCM as a fantastic fit for an evolving compliance program. Using the DataBee dashboards, with their continuously updated information that can be accessible to everyone who needs to see it, help free up time for GRC and other teams to focus on the evolution of the cybersecurity program. Given the rapid change in the cyber-threat landscape, and the frequent changes in security controls and regulatory requirements, turning report creation over to CCM to give time back to your people for higher value work is a win for your organization. DataBee for CCM helps by providing consistent data to all teams, GRC, executive management, business management, IT, etc., so that everyone is working from the same information. This helps to delegate control compliance, and clearly identify accountable and responsible parties. Furthermore, DataBee for CCM shows executives, GRC, business managers and others content for multiple controls, from many different tools, through a single interface (as opposed to GRC needing to create multiple reports, or business managers and others having to create their own, possibly erroneous, reports). Additional dashboards can be created to report on other controls that are in scope for PCI DSS, such as secure configuration, business continuity, and monitoring the compliance of third-party service providers. Any control for which data is available to create useful dashboard content is a candidate for a DataBee for CCM dashboard.

During my time as a SOC analyst, triaging and correlating alerts often felt like solving a puzzle without the box or knowing if you had all the pieces.   My days consisted of investigating alerts in an always-growing incident queue. Investigations could start with a single high or critical alert and then hunt through other log sources to piece together what happened. I had to ask myself (and my team) if this alert and that alert had any identifiable relationships or patterns with the ones they investigated that day, even though the alerts looked unrelated by themselves. Most investigations inevitably relied on institutional knowledge to find the pieces of your puzzle, searching by IP for one data source and the computer name in another. Finding the connections between the low and slow attacks in near real-time was a matter of chance and often discovered via threat-hunting efforts, slipping through the cracks of security operations. This isn’t an uncommon story and it's not new either – it’s the same problems faced during the Target 2013 breach and the National Public Data Network 2024 breach.  That’s why we launched automated detection chaining as part of the DataBee for Security Threats solution. Using a patent-pending approach to entity resolution, the security data fabric platform can chain together alerts from disjointed tools that could be potentially tied to an advanced persistent threat, insider threat, or compromised asset. What I like to call a “super alert” is presented in DataBee EntityViews™, which aggregates alerts into a time-series, or chronological, view. Now it’s easier to find attacks that span security tools and the MITRE ATT&CK framework. With our out-of-the-box detection chain, you can automatically create a super alert before the adversary reaches the command-and-control phase.   Break free from vendor-specific detections with Sigma Rules  Once a security tool is fully deployed in the network and environment, it becomes near impossible to change out vendors without significant operational impact. The impact is more than just replacing the existing solution, it's also updating all upstream and downstream integration points, such as custom detection content or log parsers. This leads to potential gaps in coverage due to limitations in the tooling deployed and the tools desired. Standard logging is done to a vendor-agnostic schema, and then an open-source detection framework is applied.   The DataBee Platform automated migrating to the Open Cybersecurity Schema Framework (OCSF), which has become increasingly popular with security professionals and is gaining adoption in some tools. Its vendor-agnostic approach standardizes disparate security logs and data feeds, giving SOC teams the ability to use their security data more effectively. Active detection streams in DataBee apply Sigma formatted rules over security data that is mapped to a DataBee-extended version of OCSF to integrate into the existing security ecosystem with minimal customizations. DataBee handles the translation from the Sigma taxonomy to OCSF to help lower the level of effort needed to adopt and support organizations on their journey to vendor-agnostic security operations. Sigma-formatted detections are imported and managed via GitHub to enable treating detections as code. By breaking free of proprietary formats, teams can more easily use vendor-agnostic Sigma rules to gain security insights from across all their tools, including data stored in security data lakes and warehouses.  The accidental insider threat  Accidental insider threats often begin with a phishing attack containing a malicious link or download that tricks the user. The malware is too new or has morphed to evade your end point detection. Then it spreads to whatever other devices it can authenticate to. Detecting the scope of the lateral movement of the malware is challenging because there is so much noise to search through. With DataBee EntityViews, SOC teams can easily review the historical information connected to the organization’s real-world people and devices, giving them a way to trace the progression of events.   Looking at a user’s profile shows relevant business contexts that can aid the investigation:  Job Title to hint at what is normal behavior  Manager to know who to go to for questions or if action needs to be taken  Owned assets that may be worth investigating further  The Event Timeline shows the various types of OCSF findings associated with the user.   By scrolling through the list of findings, a SOC analyst can quickly identify several potential issues, including malware present within the workstation. Most notable, the MITRE ATT&CK detection chain has triggered. In this instance, we had multiple data sources that alerted on different parts of the ATT&CK chain producing a super alert. The originating events are maintained as evidence and easily accessible to the analyst: EntityViews allow for bringing the events from devices that the current user owns to help simplify the process of pulling together the whole story. In our example the device is the user’s laptop so it's likely that all of the activity is carried out by the user:   The first thing of note is the unusual number of authentication attempts to devices that seem atypical for a developer such as a finance server. As we continue to scroll through the user’s timeline, reviewing events from a variety of data sources, we finally come across our smoking gun. In this instance, we are able to see the phishing email that user clicked the link on that is our initial point of compromise:  It’s clear the device has malware on it, and the authentication attempts imply that the malware was looking to spread further in the network. To visualize this activity, we can leverage the Related Entities graphical view in the Activity section of EntityViews. SOC analysts can use a graphical representation and animation of the activity to visualize the connections between the compromised user and the organization. The graph displays other users and devices that have appearances in security findings, authentication, and ownership events. In our example, we can see that the user has attempted to authenticate to some atypical devices such as an HR system:   Filtering enables more targeted investigations, like focusing on only the successful authentication attempts:   Visualizations such as this in DataBee enable more accurate, timely and complete investigations. From this view, the SOC analysts can select any entity to see their EntityView with the activity associated with the related users and devices. Rather than pivoting between multiple applications or waiting for data to be reprocessed, they have real-time access to information in an easy to consume format.   Customizing detection chains to achieve organizational objectives  Detection Chains are designed to enable advanced threat modeling in a simple solution. Detection Chains can be created in the DataBee platform leveraging all kinds of events that flow through the security data fabric. DataBee ships with 2 detection chains to get you started:   MITRE ATT&CK Chain: Detect advanced low and slow attacks that span the MITRE ATT&CK chain before reaching Command & Control.   Potential Insider Threat: Detect insider threats who are printing out documents, emailing personal accounts, and messing with files in the file share.  These chains serve as a starting point. The intent is that organizations add and remove chains based on their specific needs. For example, you may want to extend the potential insider threat rule to include more potential email domains or limit file share behavior to accessing files that contain trade secrets or sales information. Automated detection chains are nearly infinity flexible. By chaining together detections from the different data sources that align to different parts of the attack chain specific to a user or device, DataBee enables building advanced security analytics for hunting the elusive APTs and getting ahead of pesky ransomware attacks.  Building a better way forward with DataBee  Every organization is different, and every SOC team has unique needs. DataBee’s automated detection chaining feature gives SOC analysts a faster way to investigate complex security incidents, enabling them to rapidly and intuitively move through vast quantities of historical data.   If you’re ready to gain the full value of your security data with an enterprise-ready security, risk, and compliance data fabric, request a custom demo to see how DataBe for Security Threats can turn static detections into dynamic insights. 

Organizations often adopt data tiering to reduce the amount of data that they send to their analytics tools, like Security Information and Event Management (SIEM) solutions. By diverting data to an object store or a data lake, organizations are able to manage and lower costs by minimizing the amount of data that their SIEM stores. Although they achieve this tactical objective, the process creates data silos. While people can query the data in isolation, they often fail to glean collective insights across the silos.   Think of the problem like a large building with cameras across its perimeters. The organization can monitor each camera’s viewpoint, but no individual camera has the full picture, as any spy movie will tell you. Similarly, you might have different tools that see different parts of your security picture. Although SIEMs originally intended to tie together all security data into a composite, cloud applications and other modern IT and cybersecurity technology tool stacks generate too much data to make this cost-effective.   As organizations balance saving money with having an incomplete picture, a high-quality data fabric architecture can enable them to build more sustainable security data strategies. From default to normalized When you implement a data lake, the diverted data remains in its default format. When you try to paint a composite picture across these tools, you rely on what an individual data set understands or sees, leaving you to pick out individual answers from these siloed datasets. Instead of asking a question once, you need to ask fragments of the question across different data sets. In some cases, you may have a difficult time ensuring that you have the complete answer.   With a security data fabric, you can normalize the data before landing it in one or more repositories. DataBee® from Comcast Technology Solutions uses extract, transform, and load processes to automatically parse security data, then normalizes it according to our extended Open Cybersecurity Schema Framework (OCSF) so that you can correlate and understand what’s happening in the aggregate picture. By normalizing the data on its way to your data lake, you optimize compute and storage costs, eliminating some of the constraints arising from other data federation approaches.  Considering your constraints Federation reduces storage costs, but it introduces limitations that can present challenges for security teams.   Latency  When you move data from one location to another, you introduce various time lags. Some providers will define the times per day or number of times that you can transfer data. For example, if you want data in a specific format, some repositories may only manage this transfer once per day.   Meanwhile, if you want to stream the data into a different format for collection, the reformatting can also create a time lag. A transformation and storage process may take several minutes, which can impact key cybersecurity metrics like mean time to detect (MTTD) or mean time to respond (MTTR).   When you query security datasets to learn what happened over the last hour, a (near) real-time data source will contribute to an accurate picture, while a delayed source may not have yet received data for the same period. As you attempt to correlate the data to create a timeline, you might need to use multiple data sources that all have different lag times. For example, some may be mostly real-time while another sends data five minutes later. If you ask the question at the time an event occurred, the system may not have information about it for another five minutes, creating a visibility gap.    Such gaps can create blind spots as you scale your security analytics strategy. The enterprise security team may be asking hundreds of questions across the data system, and the time delay can create a large gap between what you can see and what happened.   Correlation Correlating activities from across your disparate IT and security tools is critical. Data gives you facts about an event while correlation enables you to interpret what those facts mean. When you ask fragments of a question across data silos, you have no way to automate the generation of these insights. For example, a security alert will give you a list of events including hundreds of failed login attempts over three minutes. While you have these facts, you still need to interpret whether they describe malicious actors using stolen credentials or a brute force attack.   To improve detections and enable faster response times, you need to weave together information like:   The IP address(es) involved over the time the event occurred  The user associated with the device(s)  The user’s geographic location  The network access permissions for the user and device(s)  You may be storing this data in different repositories without correlation capabilities. For example, you may have converged all DNS, DHCP, firewall, EDR, and Proxy data in one repository while combining user access and application data in another. To get a complete picture of the event, you need to make at least, although likely more than, two single-silo queries.   While you may have reduced data storage costs, you have also increased the duration and complexity of investigating incidents, which gives malicious actors more time in your systems, making it more difficult to locate them and contain the threat. Weaving together federated data with DataBee Weaving together data tells you what and when something happened, enabling insights into activity rather than just a list of records. With a fabric of data, you can interpret it to better understand your environment or gain insights about an incident. With DataBee, you can focus on protecting your business while achieving tactical and strategic objectives.  At the tactical level, DataBee fits into your cost management strategies because it focuses on collecting and processing your data in a streamlined affordable way. It ingests security and IT logs and feeds, including non-traditional telemetry like organizational hierarchy data, from APIs, on-premises log forwarders, AWS S3s, or Azure Blobs then automatically parses and maps the data to the OCSF. You can use one or more repositories, aligning with cost management goals. Simultaneously, data users can access accurate, clean data through the platform to build reliable analytics without worrying about data gaps.   The platform enriches your dataset with business policy context and applies patent-pending entity resolution technology so you can gain insights based on a unified, time-series dataset. This transformation and enrichment process breaks down silos so you can efficiently and effectively correlate data to gain real-time insights, empowering operational managers, security analysts, risk management teams, and audit functions.  

Data can come in all shapes and sizes. As the “data guy” here at DataBee® (and the “SIEM guy” in a past life), I’ve worked plenty with logs and data feeds in different formats, structures, and sizes delivered using different methods and protocols.  From my experience, when data is inconsistent and lacks interoperability, I’m spending most of my time trying to understand the schema from each product vendor and less time on showing value or providing insights that could help other teams. That’s why I’ve become involved in the Open Cybersecurity Schema Framework (OCSF) community. OCSF is an emerging but highly collaborative schema that aims to standardize security and security-related data to improve consistency, analysis, and collaboration.  In this blog, I will explain why I believe OCSF is the best choice for your data lake. The problem of inconsistency When consuming enterprise IT and cybersecurity data from disparate sources, most of the concepts are the same (like an IP address or a hostname or a username) but each vendor may use a different schema (like the property names) as well as sometimes different ways to represent that data.  Example: How different vendors represent a username field  Vendor Raw Schema Representation Vendor A (Firewall) user.name Vendor B (SIEM) username Vendor C (Endpoint) usr_name Vendor D (Cloud) identity.user Even if the same property name is used, sometimes the range of values or classifications might vary.  Example: How different vendors represent “Severity” with different value ranges  Vendor Raw Schema Representation Possible Values Vendor A (Firewall) severity low, medium, high Vendor B (SIEM) severity 1 (critical), 2 (high), 3 (medium), 4 (low) Vendor C (Endpoint) severity info, warning, critical Vendor D (Cloud) severity 0 (emergency) through 7 (debug) In a non-standardized environment, these variations require custom mappings and transformations before consistent analysis can take place.   That’s why data standards can be helpful to govern how data is ingested, stored, and used, maintaining consistency and quality so that it can be used across different systems, applications, and teams.  How can a standard help? In the context of data modeling, a "standard" is a widely accepted set of rules or structures designed to ensure consistency across systems. The primary purpose of a standard is to achieve normalization—ensuring that data from disparate sources can be consistently analyzed within a unified platform like a security data lake or a security information event management (SIEM) solution.  From a cyber security standpoint, this becomes evident in at least a few common scenarios: Analytics: A standardized schema enables the creation of consistent rules, models, and dashboards, independent of the data source or vendor. For example, a rule to detect failed login attempts can be applied uniformly, regardless of whether the data originates from a firewall, endpoint security tool, or cloud application.  Threat Hunting - Noise Reduction: With normalized fields, filtering out irrelevant data becomes more efficient. For instance, if every log uses a common field for user identity (like username), filtering across multiple log sources becomes much simpler.  Threat Hunting - Understanding the Data: Having a single schema instead of learning multiple vendor-specific schemas reduces cognitive load for analysts, allowing them to focus on analysis rather than data translation.  For log data, several standards exist. Some popular ones are: Common Event Format (CEF), Log Event Extended Format (LEEF), Splunk's Common Information Model (CIM), and Elastic’s Common Schema (ECS). Each has its strengths and limitations depending on the use case and platform. Why existing schemas like CEF and LEEF fall short  Common Event Format (CEF) and Log Event Extended Format (LEEF) are widely used schemas, but they are often too simplistic for modern data lake and analytics use cases.  Limited Fields: CEF and LEEF offer a limited set of predefined fields, meaning most log data ends up in custom fields, which defeats the purpose of a standardized schema.  Custom Fields Bloat: In practice, most data fields are defined as custom, leading to inconsistencies and a lack of clarity. This results in different interpretations of the same data types, complicating analytics.  Overloaded Fields: Without sufficient granularity, crucial data gets overloaded into generic fields, making it hard to distinguish between different event types.  Example: Overloading a single field like “message” to store multiple types of information (e.g., event description, error code) creates ambiguity and reduces the effectiveness of automated analysis.  The limits of CIM and ECS: vendor-specific constraints  Splunk CIM and Elastic ECS are sophisticated schemas that better address the needs of modern environments, but they are tightly coupled to their respective ecosystems.  Proprietary Optimizations:  CIM: Although widely used within Splunk, CIM is proprietary and lacks an open-source community for contributions to the schema itself. Its design focuses on Splunk’s use cases, which can be limiting in broader environments.  ECS: While open-source, ECS remains heavily influenced by Elastic’s internal needs. For instance, ECS optimizes data types for Elastic’s indexing and querying, like the distinction between keyword and text fields. Such optimizations can be unnecessary or incompatible with non-Elastic platforms.  Field Ambiguity:  CIM uses fields like src and dest, which lack precision compared to more explicit options like source.ip or destination.port. This can lead to confusion and the need for additional context when performing cross-platform analysis. Vendor-Centric Design:  CIM: The field definitions and categories are tightly aligned with Splunk’s correlation searches, limiting its relevance outside Splunk environments.  ECS: Data types like geo_point are unique to Elastic’s product features and capabilities, making the schema less suitable when integrating with other tools.  How OCSF addresses these challenges The OCSF was developed by a consortium of industry leaders, including AWS, Splunk, and IBM, with the goal of creating a truly vendor-neutral and comprehensive schema.  Vendor-Neutral and Tool-Agnostic: OCSF is designed to be applicable across all logs, not just security logs. This flexibility allows it to adapt to a wide variety of data sources while maintaining consistency.  Open-Source with Broad Community Support: OCSF is openly governed and welcomes contributions from across the industry. Unlike ECS and CIM, OCSF’s direction is not controlled by a single vendor, ensuring it remains applicable to diverse environments.  Specificity and Granularity: The schema’s granularity aids in filtering and prevents the overloading of concepts. For example, OCSF uses specific fields like identity.username and network.connection.destination_port, providing clarity while avoiding ambiguous terms like src.  Modularity and Extensibility: OCSF’s modular design allows for easy extensions, making it adaptable without compromising specificity. Organizations can extend the schema to suit their unique use cases while remaining compliant with the core model.  In DataBee’s own implementation, we’ve extended OCSF to include custom fields specific to our environment, without sacrificing compatibility or requiring extensive custom mappings.  For example, we added the assessment object, which can be used to describe data around 3rd party security assessments or internal audits.  This kind of log data doesn’t come from your typical security products but is necessary for the kind of use cases you can achieve with a data lake.  Now that we have some data points about my own experiences with some of the industry’s most common schemas, it’s natural to share a visualization through a comparison matrix of OCSF and two leading schemas.  OCSF Schema Comparison Matrix  Aspect OCSF Splunk CIM Elastic ECS Openness Open-source, community and multi-vendor-driven  Proprietary, Splunk-driven  Open-source, but Elastic-driven  Community Engagement Broad, inclusive community, vendor-neutral  Limited to Splunk community and apps  Strong Elastic community, centralized control  Flexibility of Contribution Contributable, modular, actively seeks community input  No direct community contributions  Contributable, but Elastic makes final decisions  Adoption Rate  Early but growing rapidly across multiple vendors High within Splunk ecosystem  High within Elastic ecosystem  Vendor Ecosystem  Broad support, designed for multi-vendor use  Splunk-centric, limited outside of Splunk Elastic-centric, some third-party integrations  Granularity and Adaptability  Structured and specific but modular; balances adaptability with detailed extensibility  Moderately structured with more generic fields; offers broad compatibility but less precision  Highly granular and specific with tightly defined fields; limited flexibility outside Elastic environments Best For  Flexible, vendor-neutral environments needing both detail and adaptability  Broad compatibility in Splunk-centric environments  Consistent, detailed analysis within Elastic environments  The impact of OCSF at DataBee In working with OCSF, I have been particularly impressed with the combination of how detailed the schema is and how extensible it is. We can leverage its modular nature to apply it to a variety of use cases to fit our customers' needs, while re-using most of the schema and its concepts. OCSF’s ability to standardize and enrich data from multiple sources has streamlined our analytics, making it easier to track threats across different platforms and ultimately helping us deliver more value to our customers. This level of consistency and collaboration is something that no other schema has provided, and it’s why OCSF has been so impactful in my role as a data analyst.  If we have ideas for the schema that might be usable for others, the OCSF community is receptive to contributions.  The community is already brimming with top talent in the SIEM and security data field and is there to help guide us in our mapping and schema extension decisions. The community-driven approach means that I’m not working in isolation; I have access to a wealth of knowledge and support, and I can contribute back to a growing standard that is designed to evolve with the industry. Within DataBee as a product, OCSF enables us to build powerful correlation logic which we use to enrich the data we collect.  For example, we know we can track the activities of a device regardless of whether the event came from a firewall or from an endpoint agent, because the hostname will always be device.name.  Whenever our customers have any questions about how our schema works, the self-documenting schema is always available at ocsf.databee.buzz (which includes our own extensions).  This helps to enable as many users as possible to gain security and compliance insights.   Conclusion As organizations continue to rely on increasingly diverse and complex data sources, the need for a standardized schema becomes paramount. While CEF, LEEF, CIM, and ECS have served important roles, their limitations—whether in scope, flexibility, or vendor-neutrality—make them less ideal for a comprehensive data lake strategy.  For me as a Principal Cybersecurity Data Analyst, OCSF has been transformative and represents the next evolution in standardization. With its vendor-agnostic, community-driven approach, OCSF offers the precision needed for detailed analysis while remaining flexible enough to accommodate the diverse and ever-evolving landscape of log data.