Automated Prediction Of Cybersecurity Vulnerabilities

Techniques are disclosed for predicting cybersecurity vulnerabilities automatically in IT assets/targets based on known vulnerabilities of various available technologies/products. This is accomplished by loading and linking one or more ontologies in a graph database containing vulnerability information about the technologies. The assets/targets preferably belong to a bug-bounty program. An optional discovery tool maps the attack surface of each target. A profiler collects the various technologies or traits used by the target and links them to the target. Then the graph database is queried to predict the cybersecurity vulnerabilities associated with the traits and consequently with the targets. The system is preferably implemented with a service-oriented architecture (SOA) so feedback/predictions can be provided to the user in near/real-time.