To mitigate application risks, it is necessary to gather data from far-flung heterogeneous sources—data about assets, vulnerabilities, business impact, users, threat intelligence, remediation workflows and more. Mitigating application risks also calls for accurately identifying and triaging application risks and intelligently prioritizing mitigation or remediation efforts towards the most critical ones. Therefore, coherent data ontology can help ensure that application security is monitored continuously and efficiently.
Risk assessment and vulnerability reporting presents the first significant data management challenge faced by application security programs. The data management challenge becomes more daunting in the analysis, prioritization and remediation stages. For an analyst to accomplish these tasks effectively, technical assets, vulnerability, and threat intelligence information along with the business context should be integrated. Besides, risk remediation actions should be aligned with the existing IT service management systems and processes and as much context as possible should be incorporated.
Comprehensive, coherent data ontology can ensure that the analyst has a clear delineation of the relationships between numerous and disparate risk data points surrounding the app. Cyber risk data ontology will map each application risk data point to all the other relevant, connected pieces of information. Furthermore, data correlation and enrichment functions in cyber risk management solutions can build the relationships between the different data points in the ontology. In addition, it can also highlight the contexts necessary for informed decision-making.
In sum, application risk management is an essential component of an effective cybersecurity program. Application risk mitigation has to be data and context-driven. Otherwise, risk mitigation will be inefficient and deficient. Mitigating application risks successfully require tooling that can perform the challenging data management and analysis workloads demanded by the process. Furthermore, the right programs will build accurate data ontology, prioritize vulnerabilities intelligently, and track remediation continuously to deliver reliable, consistent improvements in the security posture.
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