Gutsy

We helped a large financial institution integrate process intelligence into its vulnerability management program. The result: they reduced the time taken to remediate critical vulnerabilities by 35%, ensuring that their systems remained secure against known threats. Here's 3 reasons why adding a layer of process intelligence to your 𝙚𝙭𝙞𝙨𝙩𝙞𝙣𝙜 vulnerability management program works: #vulnerabilitymanagement #processmining #datascience #processintelligence

Every day we see how data science helps security teams solve their unique problems by: - Enabling a real understanding of how their organizations actually work - Identifying the most critical risks - Automatically measuring KPIs to mitigate them Quick example: 📊 You design a vulnerability management process for patching critical vulnerabilities within 30 days. 🌟 You now think you’re on your way to mitigating critical risks, and you are... except for that other 20%. 🛑 In just a few months that 20% of inconsistencies can accrue to hundreds or thousands of systems with unpatched critical vulnerabilities. Historically, it’s been really hard for organizations to zoom out and understand 𝘩𝘰𝘸 𝘢𝘯𝘥 𝘸𝘩𝘺 their security processes get off track.  That's why creating a larger zoomed out view that enables understanding of the sources of inconsistencies can help organizations get back on track - and undo any damage done by that 20% of inconsistencies. One way to course correct and mitigate future deviations is to automatically set KPIs and take corrective actions when processes get off track. [𝗪𝗮𝘁𝗰𝗵] 𝗨𝘀 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗲 𝗮 𝗞𝗣𝗜 𝗧𝗿𝗮𝗰𝗸𝗶𝗻𝗴 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝘆 𝘁𝗼 𝗶𝗺𝗽𝗿𝗼𝘃𝗲 𝗿𝗲𝗺𝗲𝗱𝗶𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗱𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻 𝗿𝗮𝘁𝗲𝘀. [Read] https://lnkd.in/g9vrm4GP #vulnerabilitymanagement #MTTR #MTTD #datascience #processmining

With oceans of data to navigate, a lot of organization's natural response to survive is to invest in more detection tools to help stay afloat. Despite this increased investing, many organizations still find themselves still struggling with the timely patching of known critical vulnerabilities. In this video, we explore how the addition of AI and process mining to a vulnerability management program can help organizations stop struggling with foundational fixes such as unresolved patches and other known, but incomplete, remediation efforts. Read more: https://lnkd.in/gu9vv3Z2 #vulnerabilitymanagement #remediation #artificialintelligence #processmining #AI

We built our daily vulnerability management data fabric reports to 𝙤𝙣𝙡𝙮 𝙨𝙚𝙣𝙙 𝙬𝙝𝙚𝙣 𝙣𝙚𝙬 𝙧𝙚𝙨𝙪𝙡𝙩𝙨 𝙖𝙧𝙚 𝙛𝙤𝙪𝙣𝙙. Because we also can't stand unnecessary noise. Learn how our security process fabric is different: https://lnkd.in/di7Cpifg #vulnerabilitymanagement #processintelligence

Applying the data science of process mining to vulnerability management delivers better security outcomes. 🏆 In one case, a large U.S. healthcare organization, heavily invested in AWS security services, used our process aware capabilities to identify high-leverage automation opportunities. 🏆 In another, we helped a global manufacturing company streamline their data gathering process, accelerating their ability to collect and analyze data. This freed up staff to focus on priority improvements to improve overall operational efficiency. How does this work? Process mining is a family of data science techniques that helps you understand and improve complex processes that span multiple systems, like how you find and fix vulnerabilities. By connecting to each of the systems in a process, Gutsy collects the events that they perform individually, and then rationalizes and correlates workflows from end-to-end. That process-centric data is used to help you visualize: ✅ Root cause detection to remediation ✅ Code fixes to deployments ✅ Answer hard questions, with Gutsy AI, about this complex data. Learn more: https://lnkd.in/gJ_S-D_P

You want to make sure your vulnerability management program is as efficient as possible. ✔ Gutsy AI can give you the answers you need to make that happen (with the tools you already have - regardless of location across your cloud estate). Learn more at https://lnkd.in/gpfHXCbV #vulnerabilitymanagement #artificialintelligence #AI #processmining #datascience

Security teams are overwhelmed with vulnerability alerts. But these alerts lack context of how vulnerabilities impact specific environments. More importantly, they don’t help teams understand how effectively they are actually remediating them. Gutsy is the first to apply the data sciences of process mining to cyber. Why do this? To provide a process-aware understanding of how vulnerability management teams, tools, and services are actually working together. This video goes deeper into the problem we are solving: #vulnerabilitymanagement #detection #remediation #processmining #datascience

Most CISOs and their teams have clear metrics to assess progress on handling vulnerabilities, such as: ▶ MTTR ▶ MTTD ▶ % of critical vulnerabilities unpatched ▶ Time to patch In theory, tracking these metrics should drive progress because teams are aware that is how they will be judged. But metrics alone can't tell the whole story. 📚 Metrics alone can't optimize the security efficiency of any team. 🔐 𝙏𝙝𝙞𝙨 𝙞𝙨 𝙗𝙚𝙘𝙖𝙪𝙨𝙚 𝙢𝙚𝙩𝙧𝙞𝙘𝙨 𝙘𝙖𝙣 𝙗𝙚 𝙜𝙖𝙢𝙚𝙙, 𝙖𝙣𝙙 𝙩𝙝𝙚𝙮 𝙬𝙤𝙣'𝙩 𝙩𝙚𝙡𝙡 𝙮𝙤𝙪 𝙝𝙤𝙬 𝙖𝙣𝙙 𝙬𝙝𝙞𝙘𝙝 𝙥𝙧𝙤𝙗𝙡𝙚𝙢𝙨 𝙬𝙚𝙧𝙚 𝙨𝙤𝙡𝙫𝙚𝙙. Example: A security team modifies the vulnerability policy to add exceptions, but neglects to note that the vulnerability was never fixed. ... Yet the metric shows the alert was silenced ... 🔕 Explore more about this false sense of security and why transparency of security processes is becoming even more critical ⤵ https://lnkd.in/dGieg6D6

Shifting from a reactive vulnerability management program ➡ a proactive approach is where most modern organizations want to be heading. 🤩 But they can go a step further and transform their operations into a streamlined and predictive machine with the application of process mining enhanced with AI. 𝘏𝘦𝘳𝘦'𝘴 𝘩𝘰𝘸 𝘪𝘵 𝘤𝘢𝘯 𝘮𝘢𝘬𝘦 𝘢 𝘥𝘪𝘧𝘧𝘦𝘳𝘦𝘯𝘤𝘦: 𝗩𝗶𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆 𝗶𝗻𝘁𝗼 𝗥𝗲𝗺𝗲𝗱𝗶𝗮𝘁𝗶𝗼𝗻 𝗪𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀: Process mining provides a clear view of the entire remediation process, from detection to resolution. By mapping out each step, organizations can identify where delays are occurring and take action to streamline these processes. 𝗔𝗜-𝗗𝗿𝗶𝘃𝗲𝗻 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀: Analyze massive amounts of complex data sets from various detection tools and provide actionable insights. This lets security teams quickly prioritize vulnerabilities based on risk so the most critical issues are addressed first. 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱 𝗗𝗲𝗰𝗶𝘀𝗶𝗼𝗻 𝗠𝗮𝗸𝗶𝗻𝗴: AI can assist in making real-time decisions about remediation efforts. For instance, it can recommend the most effective approach to a specific vulnerability, or execute some remediation tasks automatically. This lessens the workload on human teams and accelerates the entire process. 💡 We've seen how pairing process intelligence + AI helped large enterprises improve MTTR by 40% ... 💡 And others used it to decrease their handling of low-priority vulnerabilities by 30% .... Read all about it 📖 https://lnkd.in/gu9vv3Z2

You know you have vulnerabilities. Process intelligence lets you remediate them faster.