OpenAI at the Core: How Cisco Turns Frontier AI into a Defender's Advantage

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The balance of power in cybersecurity is shifting. Attackers now use artificial intelligence to scale automated attacks and craft exploits at machine speed, and defending enterprise infrastructure requires a fundamentally different approach. Cisco—the company whose networking and security infrastructure underpins systems worldwide—is meeting this challenge by pairing its vast network telemetry with OpenAI's frontier AI reasoning. The goal is simple and urgent: give defenders the toolkit they need to outpace emerging threats.

Privacy Guarantees That Made Deployment Possible

For any organization handling sensitive telemetry, deploying frontier AI across mission-critical systems demands absolute confidence in data handling. OpenAI's rigorous approach to enterprise data privacy—centered on zero data retention, strict customer data boundaries, and verifiable isolation—gave Cisco that confidence. This meant Cisco could integrate frontier intelligence into its security operations without compromising customer priorities or exposing sensitive network data.

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Starting Where Threats Move: The Network

Cisco's defense begins at the network, where threats actually propagate. According to Patel, the company has shifted from a single security perimeter to controls distributed across microservices, containers, and clusters.

"We can put a mini security stack in front of every microservice, every Kubernetes container, and every Kubernetes cluster, and fuse security into the fabric of the network," Patel explains.

Application-level controls restrict communication to only the connections each service genuinely needs, reducing the paths an attacker can use to spread laterally. Security teams can also isolate affected systems more selectively—allowing unaffected services to keep running while they investigate and respond.

Combining this network intelligence with OpenAI's models allows Cisco to correlate signals at machine scale. "Two signals might seem benign in isolation, but together they can reveal a meaningful pattern," Patel says. "Network intelligence allows us to correlate data across the network and derive insights to inform secure operations."

From Investigation to Remediation

Patel points to a pressing challenge for defenders: the gap between how quickly attackers exploit a vulnerability and how long organizations take to patch it. AI helps narrow that gap, giving defenders the capacity to investigate more threats and respond faster.

"AI hands attackers speed and scale. Using AI for defense is a prerequisite for staying safe," Patel says.

He describes initiatives like Daybreak and GPT-6 Astra as advances that strengthen security for both Cisco and its customers. "We're able to find and patch vulnerabilities more efficiently, while shortening the time needed for investigation, response, and remediation," Patel notes. Crucially, these capabilities fit into existing scanning workflows, so teams don't have to fundamentally change how they operate.

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Rethinking Security for an Agentic World

As agents become more autonomous, security teams face a new challenge: distinguishing malicious interference from an agent pursuing a legitimate goal in an unintended way. That requires security telemetry alongside observability data, so teams can assess both threats and agent behavior.

Patel outlines three priorities guiding this shift:
Protect agents from malicious attacks
Detect and intercept unintended behavior
Operate in near real time with adaptive policies and controls

These priorities are steering the move toward policies and controls that adapt as agents act. Through the Daybreak Defense Network, Cisco and OpenAI are exploring how to help security teams triage exposure faster and enforce the right controls in Cisco Cloud Control—shifting the advantage back to defenders.

The Bottom Line

"OpenAI is shifting the advantage to defenders by allowing us to operate at machine speed and scale," Patel concludes.

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