Cloud Security Vulnerability Management

Most vulnerability management programs are just… scanning. And the CEO thinks they’re “covered.” I’ve sat with too many executives who believed: “We scan. We patch. We do a yearly pentest. We’re good.” Then something small turned into something expensive. 🧙🏼♂️This is how you prevent a $3M incident from starting as a $1k misconfiguration. Here’s what a real Vulnerability Management program should look Program Management → You can't manage this without people, they need to be on top of everything going on. → Every risk has an owner, a deadline, and a business decision attached. → Without this, findings sit in dashboards. You need a risk register for anything delayed or accepted. Attack Surface Management → You must look beyond your walls and see your business from their POV → Finds exposed assets you didn’t know were there → If attackers can see it, it’s in scope. You need continuous external discovery, not a once-a-year review. DevSecOps → If you write code, it needs to be tested, safe and not just once pre-production. → Prevents new weaknesses from being built into software before release. → Security checks must be part of dev, not bolted on after launch. Continuous Pentesting → Just like the dashboard lights on your car, they don't just check once a year. → Tests are always running to catch risks before attackers do. → Your world changes. Validation has to keep up, not wait for next year’s report. Red Team → A standard test kicks in the door, this is sneaky sneaky real.  → Simulates a real attacker moving quietly over time to find gaps. → This tests maturity. It tests detection, response, and leadership visibility. Context & Threat Intel → Without context everything is "critical," you want to prioritize to reduce efforts long term. → Focuses on weaknesses attackers are actually using, not just what exists. → Your business is not every business. Pentesting (Point in Time) → You need skilled and creative people to put your protection to the test. → Shows how attackers break in and what damage they can do. → Validate controls and reset assumptions. It’s a snapshot, not a strategy. Patch & Remediation Management → Finding all this issues means nothing if you don't fix them. Lots of people power needed here. → Fixes known weaknesses fast to reduce downtime and breach risk. → Measure time-to-fix, enforce deadlines, escalate delays. Otherwise “critical” becomes normal. Vulnerability Scanning → This is day 1 stuff ignoring this is like leaving your front door open. → Finds known weaknesses across your systems. → Scan consistently across servers, endpoints, cloud, and apps. If you’re a business leader you need to understand:  Vulnerability management is not a security activity. It’s a risk decision system. Most companies won’t mature past scanning. The ones that do outperform in resilience, deal confidence, and audit outcomes. 💾 Save this as your benchmark. 🔁 Repost for other leaders who think scanning equals protection.

"The vulnerability backlog is only the mirror and not the picture." This was the concluding thought of my previous post, where I emphasized the importance of enhancing traditional, reactive Vulnerability Management processes with data-driven root cause analysis practices. By doing so, organizations can enable informed decision-making and prioritize strategic investments more effectively. To highlight the power of data analysis and data visualization in Vulnerability Management (VM), I created a sample report in Power Bi using dummy data that illustrates the Chrome update process on end-user devices. The report correlates typical scanning data with software inventory data, which is commonly accessible through MDM solutions, to provide deeper insights. A typical scan report provides a list of CVEs along with metadata such as affected devices, severity, descriptions, and details like the fixed version. What VM tools often fail to reveal, however, is whether the assumed patching processes are functioning consistently and effectively over time. By correlating scan data with MDM data it becomes quickly apparent that the patch process of Google Chrome has some issues: - 40% of the devices are on N-2 or even older versions. This implies that the update process is not working, given the 3 days patch target. - 2 devices are stuck on an old Chrome version, indicating a local issue. - 36% of the devices successfully updated to the latest version within 2 days. - The Average Exposure Windows looks bad, but putting that number into context clearly surfaces the underlying problems. Although this little demonstration focuses on a specific example, the same approach can be applied in all the domains of VM (endpoint, cloud, servers, AppSec). Adopting this approach has several positive impacts: ✅ Improved security posture. ✅ Better value proposition of the VM program. ✅ Better ROI of the tools by utilizing the data more. ✅ Build reliable patch processes. ✅ Better collaboration with the technical teams. ✅ Enabling leadership to make risk based decisions. ✅ More tailored, meaningful policies. ✅ Setting realistic SLAs and KPIs. ✅ Better job satisfaction by reducing CVE fatigue. ✅ More efficient use of resources. An increasing vulnerability backlog is not something we have to live with. With a little mindset change and smarter use of the data that is already at our disposal we can make significant improvements without onboarding yet another tool. Hope you got inspired! Happy Holidays!🎄🎁 PS: Dear VM Vendors, if you could make better use of the data you already have an create more intuitive UI and/or build easy-to-use APIs, that would be great! That's my professional wish for 2025! 🙂 ❤️ #vulnerabilitymanagement #riskmanagement #cybersecurity #infosecurity

Here's what 𝗠𝗼𝗱𝗲𝗿𝗻 𝗥𝗶𝘀𝗸 𝗮𝗻𝗱 𝗘𝘅𝗽𝗼𝘀𝘂𝗿𝗲 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 looks like in 2025, based on practitioner interviews, vendor briefings, deep evaluation of emerging as well as established players and countless hours spent in researching. Report link: https://lnkd.in/gUS-z327 Vulnerability management isn’t what it was in the 2000s. The days of telling people to scan their assets for vulnerabilities, counting number of remediated CVEs and relying on CVSS scores are behind us. This report highlights key challenges that practitioners voiced, deep dive into innovative ways vendors are evolving under risk and exposure management category, using our DDPER (Deployment, Data Collection, Prioritization, Exposure, Remediation) framework, practical 5 step guide for practitioners and our prediction. 1️⃣ 𝗘𝘅𝗽𝗼𝘀𝘂𝗿𝗲 𝗜𝘀 𝗕𝗲𝗶𝗻𝗴 𝗥𝗲𝗱𝗲𝗳𝗶𝗻𝗲𝗱 Modern platforms move beyond traditional configuration reads to define exposure. We see solutions using innovative ways to not just define but validate exposure. Taking approaches such as true network reachability analysis, detection of compensating controls in place, ingesting unstructured data, and even assessing social chatter to define exploitation probability, beyond KEV and EPSS databases. 2️⃣ 𝗖𝗮𝗽𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗖𝗼𝗻𝘃𝗲𝗿𝗴𝗲𝗻𝗰𝗲 𝗜𝘀 𝗔𝗰𝗰𝗲𝗹𝗲𝗿𝗮𝘁𝗶𝗻𝗴 Acronyms like VM, RBVM, ASM, CAASM, ASPM, BAS, CTEM, and CNAPP are no longer independent. The future lies in all of these platforms delivering dynamic scoring and context-driven risk and exposure management. 3️⃣ 𝗔𝗴𝗴𝗿𝗲𝗴𝗮𝘁𝗼𝗿 𝘃𝘀. 𝗣𝘂𝗿𝗲-𝗣𝗹𝗮𝘆 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺𝘀 We’re seeing two clear market paths emerge: 𝗔𝗴𝗴𝗿𝗲𝗴𝗮𝘁𝗼𝗿 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺𝘀: Unify vulnerability data from external scanners into a normalized risk view - ideal for organizations with diverse vulnerability tooling already in place. 𝗣𝘂𝗿𝗲 𝗦𝗰𝗮𝗻𝗻𝗶𝗻𝗴 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺𝘀: Conduct continuous native scanning across cloud, infrastructure, identity, and data (such as CNAPP platforms) - ideal for organizations looking for a single solution coverage. 4️⃣ 𝗥𝗲𝗺𝗲𝗱𝗶𝗮𝘁𝗶𝗼𝗻 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀 𝗮𝗿𝗲 𝗾𝘂𝗶𝗰𝗸𝗹𝘆 𝗴𝗮𝗶𝗻𝗶𝗻𝗴 𝗽𝗿𝗲𝗰𝗲𝗱𝗲𝗻𝗰𝗲 Leading platforms now bridge security and IT with bi-directional ticketing, in-depth recommendations, SLA tracking, and fix validation turning findings into measurable risk reduction. 5️⃣ 𝗧𝗵𝗲 𝗣𝗿𝗮𝗰𝘁𝗶𝘁𝗶𝗼𝗻𝗲𝗿’𝘀 𝗣𝗹𝗮𝘆𝗯𝗼𝗼𝗸 Selecting the right platform now requires a structured approach, one that maps business needs, operational maturity, and desired automation outcomes to the right vendor model. This 5 step guide is to provide organizations with a quick way to evaluate how to approach the market. Top Vendors evaluated in-depth: Astelia  Axonius  Cogent Security Orca Security Seemplicity Tonic Security XM Cyber Nagomi Security Zafran Security 

Qualys has introduced a new approach to vulnerability management called "patchless patching"[1]. This technique aims to address critical security vulnerabilities without the need for traditional patching methods, offering significant advantages for Managed Security Service Providers (MSSPs) and their clients[1]. The patchless patching solution utilizes Qualys' Cloud Agent to deploy custom scripts that mitigate vulnerabilities by modifying system configurations or implementing workarounds[1]. This approach allows organizations to protect their systems from potential exploits quickly and efficiently, without waiting for official patches from software vendors or disrupting critical business operations[1]. Key benefits of Qualys' patchless patching include: 1. Rapid response to zero-day vulnerabilities 2. Reduced downtime and operational impact 3. Improved security posture for legacy systems 4. Enhanced flexibility for MSSPs in managing client environments By leveraging this new technology, MSSPs can offer their clients a more agile and effective vulnerability management solution, helping to minimize security risks and maintain compliance with industry regulations[1]. As the cybersecurity landscape continues to evolve, innovative approaches like patchless patching are likely to play an increasingly important role in protecting organizations from emerging threats. MSSPs and their clients should consider exploring this new technology to enhance their overall security strategy and stay ahead of potential attackers. Citations: [1] https://lnkd.in/gXaivZSV

Dear Business & IT Audit Leaders, Cloud environments are not inherently secure. They are only as resilient as the questions we ask. As a cybersecurity audit leader, I don’t begin any cloud assessment without interrogating the architecture through 8 critical dimensions. These aren’t just technical checks, they’re strategic filters that reveal business risk, regulatory exposure, and operational blind spots. Whether you're migrating, auditing, or optimizing your cloud stack, these questions reveal the real posture of your environment. They cut through vendor promises and dashboards to expose what matters: risk, resilience, and regulatory readiness. Here’s the framework I use to guide CISOs, CTOs, and audit teams: 📌 Business Purpose & Data Sensitivity Every cloud asset must be mapped to its business function and data classification. If you don’t understand the value and risk of what’s hosted, you’re auditing in the dark. 📌 Cloud Service Model & Deployment Type IaaS, PaaS, SaaS, and Public, Private, Hybrid, each shift the shared responsibility model. Misidentifying this leads to control gaps and audit failures. 📌 Identity, Access & Privileged Account Management IAM policies, MFA enforcement, and least privilege aren’t optional, they’re the backbone of cloud security. I assess not just design, but operational discipline. 📌 Encryption at Rest & In Transit I validate cryptographic standards, key lifecycle management, and segregation of duties. Weak encryption is a silent breach waiting to happen. 📌 Network & Perimeter Defense Firewalls, segmentation, and intrusion prevention must be tested for effectiveness, not just existence. I look for real-world resilience, not checkbox compliance. 📌 Vulnerability Management & Threat Detection Scanning cadence, patch velocity, and incident response maturity determine whether threats are contained or compounded. I benchmark against threat intelligence and business risk. 📌 Business Continuity & Disaster Recovery Validation RTO/RPO metrics are meaningless without tested recovery capabilities. I simulate failure scenarios to assess readiness under pressure. 📌 Regulatory Compliance & Governance Frameworks From HIPAA to NIST to ISO 27001, I verify not just policy alignment but operational execution. Governance must be embedded, not just documented. These 8 dimensions form the backbone of my cloud audit methodology. They help organizations move from reactive security to proactive resilience. If you're leading cloud transformation, audit readiness, or cybersecurity strategy, this is where your assessment should begin. Let’s discuss: Which of these questions do you think is most overlooked in your organization? #CloudSecurity #CyberAudit #ITAudit #AIaudit #RiskManagement #CloudSecurityRisk #CyVerge #CloudSecurityAudit #Cyberverge #Governance #CloudResilience #CloudGovernance

A few years ago, I watched a company scramble to patch thousands of “critical” vulnerabilities after a vulnerability scan lit up like a Christmas tree. They poured weeks of effort, burned through budget, and celebrated the zero criticals dashboard moment. Then, two weeks later their customer portal went down. Revenue stopped flowing. The outage had nothing to do with any of those “critical” vulnerabilities. It was caused by a single, unpatched system that supported a Critical Business Function... ...the system that processed payments. Ironically, it was categorized as “medium risk.” Lessons learned? We don’t protect everything equally. We protect what drives the business. Vulnerability management isn’t about CVEs, patch cadence, or SLA reports. It’s about understanding where vulnerabilities intersect with the functions that make money and aligning your effort to protect them. When your vulnerability management policy is mapped to Critical Business Functions, magic happens... Prioritization becomes surgical. Conversations with leadership become strategic. Security transforms from overhead to business enablement. Executives don’t care about CVSS scores... they care about continuity, predictability, and revenue flow. Vulnerability management without business context is just busy work. With business context, vuln management becomes a competitive advantage. Stop patching noise. Start protecting what matters. #CISO #vulnerabilitymanagement #riskmanagement #infosec #leadership #security

The Cloud Security Alliance published a strategy briefing yesterday titled "The AI Vulnerability Storm: Building a Mythos-ready Security Program." It was authored by Gadi Evron, Rich Mogull, and Robert T. Lee, with input from over 50 CISOs and practitioners. I've worked directly with several of the authors and reviewers. When this group converges on a set of recommendations, it's worth paying attention. The context: Anthropic's Claude Mythos Preview autonomously discovered thousands of zero-day vulnerabilities across every major OS and browser, with a 72% exploit success rate and the ability to chain bugs into working attack paths without human guidance. Time between disclosure and weaponization has compressed to hours. Other frontier models will reach comparable levels within months. The briefing's most important recommendation is also its least surprising: execute the fundamentals. Patching. Segmentation. Egress filtering. MFA. These controls increase the cost of exploitation regardless of whether the vulnerability was found by a human or a model. Here's the math that should keep you up at night: half of organizations take five or more days to patch critical vulnerabilities, and 94% haven't fully automated their endpoint management. When time-to-exploit was measured in weeks, that was a calculated risk. When it's measured in hours, it's an open door. The near-term answer isn't waiting for AI to defend you. It's automating the operational work that should have been automated already, so your team has the capacity to absorb what's coming. I wrote up a full breakdown of the briefing's implications for endpoint management, including the 90-day board-level action plan and where Automox fits: https://lnkd.in/eu7sAhZn

🔭A vulnerability was recently discovered in HTTP requests within web applications managing AWS infrastructure. These vulnerabilities could potentially allow attackers to capture access keys and session tokens (which are often temporarily shared with external users, who can upload device logs to CloudWatch), enabling unauthorized access to backend IoT endpoints and CloudWatch instances. What is at risk: 📛Attackers can intercept these credentials in clear text, potentially uploading false logs or sending MQTT messages to IoT endpoints. This not only compromises data integrity but also increases operational costs through fraudulent activities. 📞The PoC showed a peer-to-peer screen sharing application built on AWS that HTTP made requests to specific endpoints that could expose sensitive credentials. 🗒Two unique endpoints were found: ‘/createsession’ and ‘/cloudwatchupload’. When a request was sent to the ‘/createsession’, the web application responded with access keys and session tokens corresponding to an AWS IOT endpoint. These keys were successfully used to send MQTT messages to the AWS IOT endpoint. 🛠Recommended Actions: Data should be routed through an internal server that validates and securely forwards it to AWS services. Implementing centralized auditing, logging, and rate limiting will further enhance security. This case serves as a stark reminder of the ongoing risks and design flaws prevalent in integrating web applications with backend cloud services. #CyberSecurity #AWS #InfoSec #CloudSecurity #DataProtection

Unpopular opinion… you got a Vulnerability scanner expecting clarity but got 500,000 findings instead. 🤐 Some try to throw basic prioritization at it. 👀 Auto-label severity. Generate Jira tickets. Congrats! Now you have 500,000 "enhanced" problems. :) After decades in Cloud and years in AI for large enterprise i can safely say: Cloud security doesn’t fail because of lack of visibility. It fails because we operate at the wrong unit of work. Most teams triage at the finding level. Attackers don’t care about findings. They exploit patterns, while we look for a needle in a haystack One vulnerable base image. One bad IAM module. One Terraform pattern reused 200 times. One dependency sprayed across 40 services. Fix one root cause, and make dozens of vulnerabilities disappear. This is where AI can really help Today i see mature teams make the following shift: - Killing vulnerability classes - Designing remediation into agentic workflows - Use AI to prioritize what’s actually reachable - Route fixes to real owners (not security backlogs) - Offer usable options when the “perfect” fix breaks prod Shoutout to Maze who recently released their AI remediation agents which sparked this post. They are using AI for root cause, fix aggregation, environment-specific guidance, and routing to actual owners which feels like this shift in practice. Worth a look if you're staring at a wall of red. They are also the sponsor of this post but views are mine. Curious: When you hit your first wall of red…what did you do? #maze #sponsored

Traditional scanning tools can flood your team with alerts, but they often miss the real risk: what’s actually exploitable in your cloud workloads. In our blog with the AWS Partner Network, we show how Orca Security’s Reachability Analysis helps shift focus from “all vulnerabilities” to “vulnerabilities that matter in this environment.” ✅ Agentless + dynamic inspection across workloads (without heavy agents) ✅ Identifying which vulnerable components are actually executed at runtime ✅ Reducing alert noise and focusing remediation where it counts ✅ Environments on AWS (ECR, EC2, Lambda, EKS, ECS) - mapped, analyzed, prioritized ✅ Dramatic reduction in exploitable vulnerabilities (up to ~90% less) If you’re responsible for cloud security, operations, or architecture on AWS, have a read. https://lnkd.in/deGN7imH