Cyberattacks tend to take the path of least resistance.
Automated discovery and attack tools enable threat actors to identify vulnerable systems and to exploit them with ease. Although most organizations understand the need for risk management, many of them are still relying on the manual creation and review of spreadsheets and configuration management databases (CMDB) to conduct their risk assessments. Manual and static risk assessments are often incomplete and can quickly become outdated, creating blind spots that can be exploited in an attack.
When threat actors can easily automate the process of discovering exposed endpoints and exploiting their vulnerabilities, manual risk management is destined to fall behind. What would it mean to automate the process of risk assessments and having the context to determine and prioritize risk reduction steps? It begins with comprehensive and real-time visibility.
Visibility is the foundation of effective risk assessments. Without it, organizations are operating in the dark, unaware of the potential vulnerabilities and exposures that threaten their digital landscape. Visibility exists across multiple dimensions, such as identifying every device connected to an organization’s network, as well as analyzing every aspect of those devices.
For example, a children’s hospital might want their patients to be able to play the newest video game consoles without considering that these are internet-connected devices. Without comprehensive visibility, security and risk management teams may never know these devices are connected to their network – potentially the same network that is used for medical assessments.
In fact, when organizations implement network monitoring solutions, they will typically discover thousands of unknown devices that were not recorded in their CMDB. Likewise, they typically discover numerous vulnerabilities and non-compliant devices. For example, Vedere Labs research revealed that 10 percent of the devices that have endpoint protection installed - have it disabled.
It just goes to show that static risk assessments tend to lack comprehensive visibility because they are taking a snapshot of an evolving, dynamic system as a moment frozen in time. It is like trying to solve a puzzle without knowing if you have all the pieces, or even what the picture looks like.
Real-time visibility is a game-changer. It provides organizations with an ongoing, dynamic understanding of their security posture. This includes not only identifying vulnerabilities but also understanding contextual risks based on current threats and potential attack vectors. By having a comprehensive view of the system's health at any given moment, organizations can proactively reduce their attack surface and respond to emerging threats.
Continuous Monitoring for Better System Health
Continuous monitoring goes hand-in-hand with comprehensive visibility to provide real-time insight into risks and threats. Continuous monitoring enables organizations to quickly identify when new devices are added to the network and the state of devices, as well as detecting potentially malicious and suspicious behavior. Some tools can even prioritize risk mitigation recommendations and check to make sure they have been completed.
The shift towards continuous monitoring represents a paradigm change in risk assessment methodology. Instead of a periodic and static evaluation, cybersecurity measures are now under constant scrutiny. This not only enhances an organization's ability to identify vulnerabilities promptly, but also improves its incident response capabilities and reduce risks.
Moreover, continuous monitoring aligns with the dynamic nature of modern IT infrastructures. With the proliferation of cloud services, remote work, and IIoT, the attack surface has expanded exponentially. Continuous monitoring allows for a real-time assessment of this ever-changing landscape.
Keeping Pace with Emerging Threats
Automation is the linchpin that ties visibility and continuous monitoring together to create an effective risk management strategy. Manual assessments can be time-consuming, resource-intensive and error-prone. In a fast-paced digital environment, human intervention alone can't keep up with the speed and sophistication of cyber threats.
Automating the risk assessment process means leveraging technology to collect, analyze and interpret vast amounts of data in real time. Machine learning algorithms can identify patterns, anomalies and potential risks that might elude manual analysis. This efficiency enables organizations to respond swiftly and make data-driven decisions to bolster their cybersecurity defenses.
Organizations need to be able to make informed decisions to address the risks, and often require guidance on what actions to take (especially in manufacturing). For example, if 80 percent of the devices are affected by the same vulnerability, patching it quickly brings down the risk. Similarly, focusing on seen exploitable vulnerabilities first helps use the limited security team resources effectively. Tools can help identify these patterns and suggest the best steps to take while taking into account the device context.
Static risk assessments represented by spreadsheets and CMDB can present challenges. To effectively mitigate cybersecurity risks, organizations must adopt a dynamic approach anchored in real-time visibility and continuous monitoring. Embracing automation to enhance the accuracy and efficiency of risk assessments is no longer an option—it's a necessity in the digital age. By doing so, organizations can fortify their defenses against the ever-evolving threat landscape.
