Tag: #machine-learning

Data Science and commercially available AI/ML implementations now make it possible to predict whether a vulnerability can be weaponized into malware. This could be a critical moment in cybersecurity as it allows vulnerability management to be truly proactive and reduces the remediation workload. But why bother with this? And even if we did, how could […]

It is my pleasure to share this blog article authored by Rohit Ghai, who we are fortunate to have as our advisor. Rohit is renowned in the industry and he currently serves as President, RSA Security. Recruiting machines to fight the vulnerability crisis A central pillar in any cyber resilience strategy is the idea of […]

What are reserved CVE’s ? Reserved CVE’s are NVD records for confirmed vulnerabilities with little to no information. In most cases there is no information available. ThreatWatch’s prediction model, “Coeus“ goes through all the related information about these CVE like attack vector type, social chatter and vendor advisories, and arrives at a CVSS vector and […]

Most organizations face challenges with prioritizing risk from a new vulnerability or threat. At times, late breaking threats do not provide a severity assessment. The standard way to identify the key characteristics of a threat is using CVSS (Common Vulnerability Scoring System). CVSS provides a Vector (based on key dimensions / attributes of the threat […]