Choosing a Cyber Risk Intelligence Platform

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To achieve proactive cyber risk management, teams need the proper tools to anticipate, identify and respond to threats effectively. A cyber risk intelligence platform is a great place to start in responding to risk indicators proactively.

When selecting such a platform, consider the following features and functionality:

Feature / Functionality
Value
Multifaceted intelligence
Relying on one score for overall cybersecurity posture is insufficient. Look for platforms that offer several different ways of identifying and communicating risk, such as a cyber rating for overall posture, cyber risk quantification (CRQ) and indicators of susceptibility to ransomware events. This multidimensional approach offers a clearer and more actionable picture.
Open standards
The platform should leverage commonly used open standards (e.g., MITRE’s Att&ck Framework, Open FAIR™) rather than proprietary algorithms. Open frameworks are transparent and widely accepted by practitioners, making their findings more objective and reliable. For example, if one platform rates something as low severity and another as medium, the rating based on open standards is more trustworthy.
Data Accuracy
Sharing inaccurate intelligence with a vendor can damage trust and hamper future communications. Ensure the platform provides a confidence level for each piece of intelligence so you can gauge its reliability before acting.
Speed of Intelligence
If a platform delivers information too late, it loses its value. For instance, if a vulnerability like MOVEit, exploited by the CL0P ransomware group, is reported weeks after its discovery, it's too late to mitigate the risk effectively.
Interpretability
The platform should make it easy to interpret findings, understand asset vulnerability and define remediation steps. With clear insights and action items, it’s easier to communicate and collaborate with vendors and other stakeholders to remediate issues.
AI and machine learning capabilities
Technology like AI/ML can quickly analyze vast amounts of data and identify patterns that indicate emerging threats. It can automate threat detection, predict potential attacks, and provide actionable insights, allowing teams to respond faster and more effectively. AI also aids in compliance, quickly mapping internal documentation to frameworks like NIST and ISO to evaluate gaps in compliance.
Third-party incident response workflows
These features help manage and coordinate the response to third-party security incidents. They provide capabilities for investigating incidents, tracking remediation efforts, and documenting the response process. Efficient incident response is critical for minimizing the impact of a third-party breach.
Multifaceted intelligence
Relying on one score for overall cybersecurity posture is insufficient. Look for platforms that offer several different ways of identifying and communicating risk, such as a cyber rating for overall posture, cyber risk quantification (CRQ) and indicators of susceptibility to ransomware events. This multidimensional approach offers a clearer and more actionable picture.
Open standards
The platform should leverage commonly used open standards (e.g., MITRE’s Att&ck Framework, Open FAIRTM) rather than proprietary algorithms. Open frameworks are transparent and widely accepted by practitioners, making their findings more objective and reliable. For example, if one platform rates something as low severity and another as medium, the rating based on open standards is more trustworthy.
Data accuracy
Sharing inaccurate intelligence with a vendor can damage trust and hamper future communications. Ensure the platform provides a confidence level for each piece of intelligence so you can gauge its reliability before acting.
Speed of intelligence
If a platform delivers information too late, it loses its value. For instance, if a vulnerability like MOVEit, exploited by the CL0P ransomware group, is reported weeks after its discovery, it's too late to mitigate the risk effectively.
Interpretability
The platform should make it easy to interpret findings, understand asset vulnerability and define remediation steps. With clear insights and action items, it’s easier to communicate and collaborate with vendors and other stakeholders to remediate issues.
AI and machine learning capabilities
Technology like AI/ML can quickly analyze vast amounts of data and identify patterns that indicate emerging threats. It can automate threat detection, predict potential attacks, and provide actionable insights, allowing teams to respond faster and more effectively. AI also aids in compliance, quickly mapping internal documentation to frameworks like NIST and ISO to evaluate gaps in compliance.
Third-party incident response workflows
These features help manage and coordinate the response to third-party security incidents. They provide capabilities for investigating incidents, tracking remediation efforts, and documenting the response process. Efficient incident response is critical for minimizing the impact of a third-party breach.

In addition to the features above, look for tools with robust integrations to complement these capabilities.

Key integrations to prioritize include vulnerability management systems, which help identify and prioritize vulnerabilities based on their potential impact, threat intelligence feeds to provide real-time information about the latest threats and vulnerabilities, and Security Information and Event Management (SIEM) systems, which collect and analyze security data from various sources to detect suspicious activities and potential breaches. Other key integrations include Governance, Risk, and Compliance (GRC) tools to manage policies, control user access and streamline compliance requirements and Vendor Risk Management (VRM) tools to pinpoint and mitigate risks associated with vendors.

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