Abstract: 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.

Abstract: This invention discloses systems and methods for detecting vulnerabilities in IT assets by utilizing crowdsourcing techniques. A corpus containing vulnerability data of IT assets with known vulnerabilities is established. Vulnerability data in the corpus comprises security aspects or attributes related to the IT assets. The security aspects of an IT asset constitute its attack surface which is represented as a feature vector in a feature space. A determination is made as to how similar/close a target asset whose unknown vulnerabilities are to be detected, is to the rest of the IT assets in the corpus. This determination is made based on a measure of similarity/distance between the respective feature vectors in the feature space. Based on the review of similarity results by a community of researchers/experts, a determination of unknown vulnerabilities in the target system is made.

Abstract: This invention discloses systems and methods for detecting vulnerabilities in IT assets by utilizing crowdsourcing techniques. A corpus containing vulnerability data of IT assets with known vulnerabilities is established. Vulnerability data in the corpus comprises security aspects or attributes related to the IT assets. The security aspects of an IT asset constitute its attack surface which is represented as a feature vector in a feature space. A determination is made as to how similar/close a target asset whose unknown vulnerabilities are to be detected, is to the rest of the IT assets in the corpus. This determination is made based on a measure of similarity/distance between the respective feature vectors in the feature space. Based on the review of similarity results by a community of researchers/experts, a determination of unknown vulnerabilities in the target system is made.

Abstract: This invention discloses systems and methods for detecting vulnerabilities in IT assets by utilizing crowdsourcing techniques. A corpus containing vulnerability data of IT assets with known vulnerabilities is established. Vulnerability data in the corpus comprises security aspects or attributes related to the IT assets. The security aspects of an IT asset constitute its attack surface which is represented as a feature vector in a feature space. A determination is made as to how similar/close a target asset whose unknown vulnerabilities are to be detected, is to the rest of the IT assets in the corpus. This determination is made based on a measure of similarity/distance between the respective feature vectors in the feature space. Based on the review of similarity results by a community of researchers/experts, a determination of unknown vulnerabilities in the target system is made.