What the Financial Sector Needs Now: Risk-Based Vulnerability Management

According to the Verizon 2023 Data Breach Investigations Report, basic web application attacks, which consist largely of leveraging vulnerabilities and stolen credentials to get access to an organization’s assets, are the most prevalent pattern of attack against the financial services sector. So, for attendees at FS-ISAC APAC Summit in Singapore, July 11-12, vulnerability management and multifactor authentication should remain top priorities to combat threats.

If you’re attending the APAC Summit next week, we invite you to stop by and meet the ThreatQuotient team in Booth #3. We’d love the opportunity to show you how the ThreatQ Platform can help you prioritize vulnerability management based on risk to your organization.

A better understanding of likelihood
Risk-based vulnerability management includes measuring the likelihood of a vulnerability being exploited by analyzing not just internal data, but also external data. Historically, firms have focused primarily on internal data – whether the vulnerable asset is accessible to unauthenticated users, if it is directly contactable via the public internet, and how many of the vulnerable assets there are. But today, organizations also have access to a tremendous amount of external data which they can overlay with internal data to make more informed, data-driven decisions about what actions to take. While exposure is important, the likelihood of an exploit increases if the cost for adversaries to develop exploitation tools for the vulnerability is low, or if there is an off-the-shelf attack tool they can use. Likelihood also increases if the tool fits within a threat actor’s tools, techniques, and procedures (TTPs) sweetspot, and if they have been known to target your firm, industry, region, or your customers or partners.

Leveraging likelihood to get ahead of attacks
ThreatQuotient’s data-driven security operations platform, ThreatQ, with its DataLinq Engine provides visibility into these areas so you can get ahead of attacks that leverage these vulnerabilities and are potentially more likely to impact your firm. Specifically, the ThreatQ DataLinq Engine supports the first five phases of the typical vulnerability management framework and leverages automation to:

1. Ingest: The approach starts by collecting data from various sources, such as vulnerability scanners, configuration management tools and other security-related systems. This data can include vulnerability reports, system configurations, network maps and other relevant information.
2. Normalize: In this phase, the collected data is standardized and formatted to ensure consistency and compatibility across different systems and tools. This helps to eliminate errors and duplicates, making it easier to analyze and manage the data.
3. Correlate: The next step involves identifying relationships between different pieces of data and looking for patterns or trends. For example, correlating data from vulnerability scans with network maps can help identify which systems are at higher risk due to their location or accessibility.
4. Prioritize: Once the data has been correlated, it’s time to prioritize vulnerabilities based on their severity, impact, and likelihood of exploitation. This phase typically involves assigning a risk score to each vulnerability and ranking them based on the overall risk they pose to the organization.
5. Translate: The prioritized list of vulnerabilities needs to be translated into actionable steps for remediation. This may involve assigning tasks to specific teams or individuals, providing guidance on how to address each vulnerability, and tracking progress towards resolution.

With these steps well in hand, teams can focus on the remaining three steps – Document, Report, and Remediate – with greater confidence that they have identified and addressed the vulnerabilities threat actors are most likely to exploit to target their organization.

Vulnerability prioritization is just one of the top use cases for customers of the ThreatQ Platform. Others include Spear Phishing, Threat Hunting, Alert Triage, Incident Response, and Threat Intelligence Management.

Come by Booth #3 at the FS-ISAC APAC Summit to learn more about how ThreatQ uses its DataLinq Engine to fuse together disparate data sources and tools so that teams can more effectively and efficiently prioritize, automate and collaborate to mitigate risk.

We look forward to seeing you next week!

‍