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Recent Articles
Search ArticlesEvolving With Agentic Risk: Updating Our Integrated AI Security & Safety Framework
With research and development assistance from Konstantin Berlin, Edmund Dyer-Essig, Andy Hsu, and Karthick Kalyanasundaram Nine months ago, we introduced the Integrated AI Safety and Security Framework as a unified and comprehensive taxonomy to help organizations identify and mitigate the security and safety risks unique to AI systems. Existing frameworks remained essential, but they didn’t fully capture how AI could be manipulated, produce harmful outputs, or take unexpected actions.
Now generally available: See how Stack Automation by Quali cuts deployment time
If you’ve ever found yourself at 2 a.m. staring at page 242 of a configuration guide, hunting for the firmware version that will finally make your deployment work, you already understand the problem that Stack Automation by Quali, co-developed with Cisco, is here to solve. Manual infrastructure deployment is slow, error-prone, and expensive. Deployment cycles routinely stretch 6–12 weeks or more.
Cisco and Axis Communications: Greater camera visibility, scalability, and incident management
Consider a bustling coffee shop chain. To keep every guest connected, IT teams need centralized visibility into every access point—real-time performance and bandwidth insights, plus automated firmware updates and security patches across every location. The physical security cameras installed just inches away play an equally critical role.
Thrown into the SOC: A Black Hat First-Timer’s Story
What a short, intense rotation taught me about uncertainty, evidence, and working alongside AI in the SOC. Let me get one thing out of the way: I am not a career SOC analyst. I did not walk into Black Hat with years of incident-response experience or an encyclopedic knowledge of threat actors. I was there for a concentrated SOC rotation, stepping into an unfamiliar role for a limited time and trying to absorb as much as I could.
The Next Generation of Manufacturing Is Measured in Thousands of Decisions
What do frozen French fries have to do with artificial intelligence? More than you might think. When French fries come out of the fryer, they have to be cooled and frozen, fast. As they move through that process, heat, airflow, moisture, and temperature all influence the final quality of the product and how much can move through the production line.
ML-DSA Certificates on Cisco Routers – IPsec Series, Part 10
Part 9 made the key exchange quantum-safe. ML-KEM-768 is running on all three routers, fragmentation is handling the bigger messages, and the phased rollout lets you migrate at your own pace. But authentication is still a pre-shared key, and at scale that doesn’t work. This post closes the gap. We swap PSK forML-DSA certificates(FIPS 204), the same signature scheme from Parts 6-8 in the container labs.
Manage Cisco rugged switches right from your Meraki dashboard
Your campus network stops at the front door. Your operations don’t. A reliable, secure network keeps daily operations running smoothly and protects sensitive data from costly cyberattacks. That reliability has to extend beyond the building’s walls. Utility rooms, loading docks, and parking garages need the same connectivity and protection as the buildings they support.
Turning ocean data into impact: How AI, trusted data, and partnerships can help accelerate sustainability
Every day, thousands of data points are collected across our oceans — measuring temperature, salinity, carbon dioxide concentrations, and biodiversity. These insights are essential for understanding a changing climate. But collecting data is only the first step. The real challenge is transforming data into decisions — and decisions into meaningful, measurable actions. That challenge came to life for my Cisco colleagues and I during our recent visit aboard the Malizia Explorer.
Building a Risk-Based Secure Network Analytics Detection with Splunk Detection Editor (Alpha)
Building a detection usually involves more than writing a search. You need to understand the data, test the detection logic, normalize fields, decide how analysts will see the results, configure risk, and provide a path for further investigation. Those tasks can require moving between several different parts of Splunk. While developing a detection for Cisco Secure Network Analytics (SNA), I used the Splunk Detection Editor (Alpha) to bring much of that workflow into one place.
Distributed Latency Monitoring at Black Hat
With Matthew Bair 2026 marks the fourth consecutive year we’ve used ThousandEyes to monitor the Black Hat USA network for latency. Our first deployment in 2023 featured a small fleet of Raspberry Pi’s with (officially unsupported!) wireless NICs running the ThousandEyes Enterprise Agent in a custom build configuration.