AI’s capacity to consume, assimilate and use massive datasets from numerous resources is the driving force behind significant advancements in most industries. AI-driven technologies provide deeper data insights to improve health care outcomes and optimize operational processes in manufacturing, for example. AI technologies to improve security outcomes are also being deployed to detect and prevent cyberattacks. While these AI use cases differ in their procedures and goals, the common denominator is the value of leveraging data intelligence.
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- Blog
- How are collaborative AI agents (Agentic AI) reshaping offensive security?
- How can AI-driven validation drastically reduce the time between detection and remediation?
- How can you prove that a vulnerability represents a real breach risk?
- What do recent CVEs reveal about the most common mistakes in vulnerability management?
- What lessons can we learn from recent cases like the Salesforce token abuse or Fortra GoAnywhere CVEs?
- What makes Continuous Threat Exposure Management (CTEM) different from traditional penetration testing?
- What role does automation play in solving the “vulnerability overload” challenge?
- Why are API attacks still rising, and how can organizations prevent OAuth token abuse?
- Why do so many security teams prioritize irrelevant vulnerabilities while overlooking exploitable ones?