After working with hundreds of security professionals and covering over 1 million assets at some of the world’s most innovative brands, the team at Axonius has identified 5 things that security teams discover when they automate cybersecurity asset management. In this short paper, we’ll review each of these findings, discuss their security implications, and show how automating asset management can both find and resolve these challenges.
Eight years after former Forrester analyst John Kindervag introduced the Zero Trust model, the concept has hit the mainstream. As current Forrester analyst Chase Cunningham says, 85% of his calls involve zero trust. With the amount of interest in the concept, many organizations are rushing to understand how to implement the zero-trust model. In this guide, we’ll look at the first step to implementing zero trust: asset management.
Today, security professionals face many challenges in cybersecurity asset management, from aggregating disparate data sets to establishing real-time visibility in a fluid environment. Emerging technology, such as IoT deployments, and workplace modernization like BYOD continue to complicate this situation. Organizations must understand the depth and breadth of the devices on their network.
At its core, patch management is a discipline that combines both knowledge and action. It requires IT and security teams to understand which devices are known and unknown, the version and subsequent vulnerabilities of software being used, and the impact of change. In an environment complicated by always-on, smart devices, a new approach is needed to address what’s known as well as the unknowns that should be known.
IT and security teams are already struggling to find new management and security tools that can keep up. VMs, new devices, and new device types are driving complexity. Most say that they already have too many tools, yet still report visibility gaps in what they can see versus what they want to see across cloud, mobile, and IoT environments. This gap directly translates into added security risk. 85% of organizations plan to increase investment in asset management to help overcome these issues.
By seamlessly integrating with over 200 security and IT management solutions, Axonius deploys in hours (not weeks) to improve threat and vulnerability management, security operations, incident response, and overall security posture.
In this short paper, we’ll look at what constitutes an “unmanaged” device, approaches to discovery, and how continuous data aggregation and correlation helps automate unmanaged device discovery.
Enterprises need to be confident in their ability to reduce security risk and achieve business agility without sacrificing one for the other.
Detecting and protecting from threats requires systems and analysts to proactively and reactively analyze large volumes of data. The volume and speed of the data coming in prevents users from performing even the most basic security analysis for much of the data. Deploying systems to store, organize, and analyze the data is a lengthy and expensive process.
While moving to cloud services, businesses find challenges such as: limited visibility, changing business demands and hackneyed cloud provisioning, to name a few. How do you reduce security risk when the game keeps changing?
Good APIs are hard to come by and inefficient coding has far reaching implications. DevOps teams working to spin up and integrate newer applications will find it difficult to understand and interact with poorly written APIs, and they might need to write additional, more complex code in order to use them.
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