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 

🔭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

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

Letter V: Vulnerability Management: Best Practices for a Patchwork World Our ‘A to Z of Cybersecurity’ explores Vulnerability Management - the ongoing process of identifying, prioritizing, and remediating vulnerabilities in your systems and software. It's like patching the leaks in your digital fortress! In a world of constantly evolving threats, vulnerability management is a critical practice: The Vulnerability Landscape: · Software Vulnerabilities: New vulnerabilities are discovered all the time, so staying up-to-date is crucial. · Exploit Availability: Cybercriminals are quick to develop exploits for known vulnerabilities. · Patch Management Challenges: Deploying patches across a complex IT infrastructure can be challenging. Building a Strong Defense: · Vulnerability Scanning: Regularly scan your systems for known vulnerabilities using automated tools. · Prioritization & Remediation: Prioritize patching based on the severity of the vulnerability and the potential impact. · Patch Management Process: Develop a systematic process for deploying patches efficiently and testing for compatibility issues. Continuous Vigilance: · Staying Up-to-Date: Subscribe to security advisories from software vendors and relevant cybersecurity organizations. · Vulnerability Intelligence: Leverage threat intelligence feeds to stay informed about emerging vulnerabilities. · Penetration Testing: Regularly simulate cyberattacks to identify and address any remaining vulnerabilities. Vulnerability management is an ongoing process, not a one-time fix. By implementing a comprehensive strategy, you can proactively identify and address vulnerabilities before they can be exploited by attackers. #QuickHeal #Seqrite #Cybersecurity #VulnerabilityManagement

Are you addressing the root causes of your cloud security threats or just treating the symptoms? The Cloud Security Alliance's Top Threats to Cloud Computing 2024 report illuminates critical security challenges, but many of these threats result from overlooking foundational practices in favor of more complex solutions. My takeaways: 1️⃣ Misconfiguration and change control - Misconfigurations often signal that organizations advance to complex cloud setups without mastering the basics. For example, the Toyota data breach, where a decade-long exposure was due to human error and inadequate cloud configuration management, highlights the need for robust configuration management and continuous monitoring. 2️⃣ Identity & Access Management (IAM) - IAM issues frequently stem from inconsistent governance. The JumpCloud breach, where attackers exploited over-permissioned accounts and poor separation of duties, underscores the importance of regular policy reviews and strict governance practices. 3️⃣ Insecure interfaces and APIs - Securing APIs is crucial, but the rush to innovate can sometimes overshadow security. The Spoutible (an X alternative) API vulnerability, which exposed user data due to poor security practices, serves as a reminder to embed security into the API development process from the start. What can you do? 1) Focus on fundamentals: To address misconfigurations, prioritize strong configuration management and continuous monitoring. Look at tools like Prisma Cloud by Palo Alto Networks. 2) Regular governance reviews: Prevent IAM issues by regularly reviewing and adapting policies. Ensure all your applications are part of your IAM strategy, not just those supporting standards like SAML, OIDC, and SCIM. (Cerby can help you with these apps.) 3) Balanced innovation: Integrate security into development processes to avoid compromising security in a rush to innovate (see Secure by Design from the Cybersecurity and Infrastructure Security Agency). Focusing on the basics and doing them well can mitigate most of the risks in this report. Props to the authors Jon-Michael C. Randall, Alexander S. Getsin, Vic Hargrave, Laura Kenner, Michael Morgenstern, Stephen Pieraldi, and Michael Roza. #Cybersecurity #cloudsecurity #api Cloud Security Alliance

𝐂𝐥𝐨𝐮𝐝 𝐀𝐈 𝐒𝐞𝐜𝐮𝐫𝐢𝐭𝐲: 𝐖𝐡𝐚𝐭’𝐬 𝐋𝐮𝐫𝐤𝐢𝐧𝐠 𝐁𝐞𝐧𝐞𝐚𝐭𝐡 𝐭𝐡𝐞 𝐒𝐮𝐫𝐟𝐚𝐜𝐞? A recent report from #Tenable reveals a concerning reality: nearly 𝟕𝟎% of cloud AI workloads carry at least one unremediated #vulnerability—and the rest may simply be unaudited. The widespread reliance on default, overprivileged service accounts in platforms like Google Vertex AI (used by 𝟕𝟕% of organizations) is multiplying risks across every layer of the AI stack. From misconfigured data buckets to vulnerable open-source components, attackers have more entry points than ever—and the blast radius for even minor oversights can be enormous. The infamous OpenAI Redis library incident, which exposed user data, is just one example of how simple misconfigurations can lead to major privacy breaches. Security in cloud AI isn’t just about patching bugs—it’s about adopting a risk-based, platform-wide approach. Organizations need to merge human and machine identities, enforce least-privilege access, and embed security controls directly into the MLOps pipeline. As cloud AI workloads scale, so too must our security strategies. 𝐊𝐞𝐲 𝐭𝐚𝐤𝐞𝐚𝐰𝐚𝐲𝐬 𝟏. 𝐀𝐮𝐝𝐢𝐭 𝐚𝐧𝐝 𝐫𝐞𝐜𝐨𝐧𝐟𝐢𝐠𝐮𝐫𝐞 𝐝𝐞𝐟𝐚𝐮𝐥𝐭 𝐩𝐞𝐫𝐦𝐢𝐬𝐬𝐢𝐨𝐧𝐬—don’t let overprivileged accounts become your Achilles’ heel. 𝟐. 𝐀𝐝𝐨𝐩𝐭 𝐚 𝐮𝐧𝐢𝐟𝐢𝐞𝐝, 𝐫𝐢𝐬𝐤-𝐛𝐚𝐬𝐞𝐝 𝐬𝐞𝐜𝐮𝐫𝐢𝐭𝐲 𝐚𝐩𝐩𝐫𝐨𝐚𝐜𝐡—prioritize vulnerabilities by potential impact, not just technical severity. 𝟑. 𝐄𝐦𝐛𝐞𝐝 𝐬𝐞𝐜𝐮𝐫𝐢𝐭𝐲 𝐢𝐧𝐭𝐨 𝐞𝐯𝐞𝐫𝐲 𝐬𝐭𝐚𝐠𝐞 𝐨𝐟 𝐲𝐨𝐮𝐫 𝐀𝐈 𝐩𝐢𝐩𝐞𝐥𝐢𝐧𝐞—from data ingestion to model deployment. Let’s not just innovate—let’s protect. The future of AI depends on it. Security should be at the heart of every AI initiative, not just an afterthought. 𝐒𝐨𝐮𝐫𝐜𝐞: https://lnkd.in/gtQf-ZyG #AI #DigitalTransformation #GenerativeAI #GenAI #Innovation  #ArtificialIntelligence #ML #ThoughtLeadership #NiteshRastogiInsights