Finding zero-days with any model
Guest Post: Vulnerability discovery is an orchestration problem, not a frontier-model problem.
Tag: Artificial Intelligence
Rising CVEs in the AI epoch
Vulnerability disclosures are rising sharply, but that does not mean risk is increasing. As AI-driven discovery floods defenders with more data but not more threats, success now depends on identifying what matters and acting faster.
Notes from NANOG 97
AI eats the world, geolocation, measuring IPv6, and the cost of SSH from NANOG 97.
Rethinking vulnerability management in the age of AI and CI/CD
Guest Post: AI-driven development is accelerating how software changes and how vulnerabilities are fixed. Traditional models like CVE and CVSS are struggling to keep pace.
Non-Human Identity for workloads: Securing the next phase of automation
Guest Post: Non-Human Identity is evolving as automation and AI increase machine-to-machine connections. Short-lived, key-based credentials address long-standing risks, but industry now needs clear assurance levels for workload identities. Collaboration will shape the next phase of NHI standards.
Level up your network engineering skills with LLMs
Guest Post: Practical tips, real-world examples, and the pitfalls of using Large Language Models for network management.
IETF setting standards for AI preferences
Guest Post: The AIPREF Working Group will standardize building blocks for expressing preferences on how content is collected and processed for AI model development, deployment, and use.
Network automation and AI at NANOG 93
Integrating network command and control automation with AI management tools.