AI Security Insights
413 results found
Partner POV | 5 Shifts CISOs Must Make for the Frontier AI Era
In the AI-driven security landscape, context is paramount. Traditional SOCs falter against machine-speed threats, necessitating a shift to real-time contextualization. By transforming raw telemetry into structured insights, organizations can enable machine-driven decisions, ensuring rapid, accurate responses. Embrace this evolution to define security success in the AI era.
Partner POV | SentinelOne + Claude: Integrations for AI Visibility, Governance, and Defense
SentinelOne enhances AI security by integrating Claude into existing platforms, offering comprehensive protection from infrastructure to user interactions. Through partnerships with Anthropic and others, it provides advanced threat detection and remediation. This approach empowers organizations to innovate with AI while maintaining robust security and minimizing risks.
Partner POV | The Industrialization of Exploitation: Why Defensive AI Must Outpace Offensive AI
Akamai explores the industrialization of exploitation, highlighting how AI-driven models rapidly uncover software vulnerabilities. As attackers leverage AI for swift exploitation, Akamai emphasizes proactive defense strategies, empowering human experts with AI to close the speed gap and protect infrastructures. The future of cybersecurity demands adaptive, resilient systems to counter evolving threats.
The Data Flywheel: How Kiewit Built a Foundation That Makes AI Actually Work
Kiewit's Chief Data and Analytics Officer, Matt Pappas, has spent 15 years building machine learning into one of the world's largest construction companies — long before "AI-ready" was a buzzword. In this episode of teh AI Proving Ground Podcast, he shares what he's learned about data culture, decision science, and the discipline most enterprises are skipping when it comes to driving AI strategy at scale.
Redefining application delivery for the AI era with F5 BIG-IP v21 and MCP
This blog explores how AI-driven and agentic applications are reshaping application delivery requirements and why traditional networking approaches are no longer sufficient. It highlights how F5 BIG-IP v21 and its native Model Context Protocol (MCP) capabilities enable context-aware traffic management, session persistence, and security governance, helping enterprises build resilient, secure, and AI-ready infrastructures at scale.
FortiSIEM + FortiEDR: Detection and Response in Minutes
Follow a SOC analyst as they trace a live intrusion from first alert to full root cause. FortiSIEM correlates the signals to show where to look; FortiEDR delivers the forensic detail to reveal what happened and how to respond, taking an analyst from detection to root cause to response in minutes.
Partner POV | AI Security is an Architectural Decision
Why governance must scale before AI Autonomy
AI Security Threats: Mythos, Project Glass Wing, and the New Cyber Resilience Framework
Explore how AI is transforming cybersecurity, the risks posed by advanced models like Mythos, and actionable strategies for building resilience against emerging threats.
WWT Innovation Vendor Spotlight - depthfirst
You're invited to our next WWT Innovation Vendor Spotlight, featuring a special session with depthfirst.
depthfirst is an AI-native security platform that understands your code, business logic, and infrastructure to find more vulnerabilities, slash false positives, and give developers actionable fixes in their workflows. The depthfirst platform provides continuous, closed-loop remediation from business logic vulnerabilities to external validation via dynamic testing.
World Wide Technology Launches 'Defending at the Speed of AI' Initiative with Horizon3.ai, Empirical Security, Infoblox and Cognition
Joint program with Horizon3.ai, Empirical Security, Infoblox and Cognition delivers integrated cybersecurity solution for AI-era threats
How to Choose the Right LLM
This hands-on lab teaches enterprise engineers how to systematically evaluate, benchmark, and select optimal large language models for distinct steps inside an agentic control plane.
Everyone Sees the Risk. Nobody Owns It.
You can hear the warning signs.
Security teams see them. Infrastructure teams see them. Data teams, compliance teams and AI leaders all see them.
The problem is they're often speaking different languages.
As organizations race to deploy agents and AI-powered workflows, a new challenge is emerging. The hardest questions aren't technical. They're organizational. Who owns the risk? Who makes the decisions? And who's responsible when AI starts operating across systems, teams and business functions?