The proliferation of cloud-native applications in today’s business landscape has helped organizations streamline operations. Businesses can now monitor data, engage with customers and share insights in near-real time, helping them overcome inefficiencies that once stifled productivity. However, using the cloud also greatly expands a business’s exploitable attack surface.
The rapid adoption of cloud infrastructure and application security tools such as CSPM, CWPP, CNAPP, SAST, SCA, IaC, DAST, etc., is a direct result of this trend, which has helped security teams identify the new risks created by their expanded operating environments in the cloud.
Monitoring and alerting are necessary as many organizations pursue a more proactive approach to vulnerability management. However, with more tools comes more pieces that must work together.
Layering these tools on top of one another leaves the security data fragmented and is often counterproductive to the goal of clearly communicating cyber risk to the business. Further, doubling down on detection and alerting without tools to contextualize, prioritize and manage the remediation of risk can actually leave the organization more exposed to breaches.
Unifying the approach
Detecting vulnerabilities is only a small portion of the overall vulnerability risk management program. Many companies still pour resources into this area at the expense of quality and efficiency elsewhere in the risk management lifecycle. A comprehensive approach to cyber risk lifecycle management may start with vulnerability identification, but it doesn’t end there. Security teams looking to up-level their program must take a unified, automated approach to the cyber risk lifecycle and track their progress at every stage.
Step 1: Adopt a common language — Hundreds of tools scan software for security risks, but few offer security teams a way to integrate vulnerability data across tools. Without that integration, IT teams encounter disconnects between information gathered by disparate tools, which complicates and slows the ability to understand and respond to risk. To overcome this challenge, teams must find ways to create a standard “language” for internal use and synthesize their asset and vulnerability data into a common record.
Automation is critical in this endeavor, as it simplifies the process of unifying information from scanners without increasing workloads on already-strapped teams. It identifies redundant alerts and consolidates related information so security teams work from a single source of truth.
Step 2: Layer in Business Context — Addressing all vulnerabilities as they are detected isn’t achievable, and it isn’t the best path to reducing an organization’s overall risk. All risks are not equal, and security teams must not treat them as such. The CFO’s hacked laptop is a more urgent risk than a minor security gap on the company’s website. Still, many security tools don’t consider that context when generating tickets. They come in and are assigned — or ignored — chronologically. That approach causes significant problems for organizations.
Businesses must consider what specific vulnerabilities mean in relation to the larger organizational context. Teams should consider both statistical and tribal knowledge to gain a holistic view of the situation. Statistical knowledge, which includes quantifiable data about an organization, reveals the team members closest to a vulnerability and how many vulnerabilities they already have on their plates.
Tribal knowledge takes this a step further, accounting for business priorities not directly related to security that should influence the security team’s approach. Leveraging both is crucial to interdepartmental communication as it helps guide more-informed, streamlined responses.
Cost is also a factor, as leaders must choose plans of action based on broader organizational goals. Explaining the importance of addressing a particular vulnerability in financial or productivity-related terms helps business leaders understand those risks more fully.
Step 3: Assign clear ownership — The volume of information that different scanners provide, combined with a lack of clear asset inventory and infrastructural complexity, makes assigning ownership of risks challenging.
Applying automation to this task supports the timely and precise assignment of ownership when leveraged effectively. Modern vulnerability risk management tools rely on a clear inventory of assets across the attack surface and captured asset ownership information to assign remediation actions for prioritized vulnerabilities to the right owner. When automating this process, security teams should create rules that schedule tickets based on the vulnerability’s severity, type and estimated remediation timeline and consider whether a given issue requires immediate attention or can wait for regular patching windows.
Supporting timeliness with automation
In today’s business landscape, investing in tools that bring vulnerability data into comprehensive, easily digestible reports is the best way to secure a company’s operations and minimize exposure. When teams embrace a unified, automated approach to managing cyber risks across their organizations’ attack surfaces, they are taking an important step to enhance efficiency, reduce risks, minimize disruptions, increase credibility and support well-informed decisions.
Most breaches are due to known ― but not yet addressed ― vulnerabilities that get lost in isolated, layered monitoring tools that lack a unified understanding of business priorities. This approach offers data but not insight. A robust cyber risk lifecycle emphasizes business context and the ability to prioritize risks by providing holistic visibility into the assets and vulnerabilities that make up the attack surface. It emphasizes reporting and communication alongside continuous monitoring, and critically, it contextualizes risks in a way that business leaders can understand, which motivates them to act.