Two independent studies found that advanced AI cybersecurity models, including Anthropic’s Claude Mythos Preview and OpenAI’s GPT-5.5, have exceeded previous benchmarks for autonomous cyberattack capability. Researchers from the UK AI Security Institute (AISI) and Palo Alto Networks said the models are now capable of chaining together complex multi-stage attack paths and identifying vulnerabilities at rates that significantly outpace earlier systems.
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- 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?