Cisco’s AI Security Innovations to Combat Evolving Threats

The growth of AI deployments across global enterprises has created an equally rapid expansion of cyber vulnerabilities.

Organisations face a confluence of challenges: increasingly sophisticated AI-enabled attacks, a widening cybersecurity talent gap and insufficient security controls for rapidly evolving AI systems.

Security professionals report growing concerns about novel attack vectors targeting machine learning (ML) models, data poisoning attempts and adversarial manipulations designed to compromise AI integrity.

This troubling situation is compounded by most organisations lacking adequate security frameworks specifically designed for AI infrastructure.

Tackling these concerns, Cisco has announced a suite of security innovations designed to address cyber challenges amongst AI’s evolution.

The bigger cybersecurity picture

The company revealed at RSA Conference 2025 in San Francisco that 86% of organisations worldwide have experienced AI-related security incidents in the past 12 months, according to its forthcoming 2025 Cybersecurity Readiness Index.

Now, Cisco’s innovations aim to support security professionals in managing increasingly sophisticated threats whilst contending with talent shortages across the cybersecurity sector.

“The cybersecurity threat landscape has never been more dynamic and complex, with adversaries constantly emboldened and enabled by AI to drive new attacks and exploits,” says Jeetu Patel, Executive Vice President and Chief Product Officer at Cisco.

“To fight back, understaffed security operations and IT leaders need AI power of their own.”

The announcement encompasses open-source security models, AI agent technology and Internet of Things (IoT) advancements integrated with the Cisco Security Cloud platform.

How Cisco XDR and Splunk Security are enhancing detection capabilities 

Security operations centres face thousands of threat alerts daily, creating significant challenges for teams tasked with identifying genuine threats.

XDR platform
Cisco's Extended Detection and Response (XDR) platform addresses this through a correlation of data across network infrastructure, endpoints, cloud environments and email systems.

Instant Attack Verification
The platform now also incorporates a feature called Instant Attack Verification, which integrates data from the Splunk platform – a data analytics software designed for searching, monitoring and analysing machine-generated data – with additional information from endpoints, networks and threat intelligence sources.

This integration uses agentic AI to create and execute investigation plans automatically.

XDR Forensics and XDR Storyboard
Additional functionality includes XDR Forensics, providing enhanced visibility into endpoint activity and XDR Storyboard, which visualises attack patterns to expedite response times.

Splunk Enterprise Security 8.1 and Splunk SOAR
Splunk Enterprise Security 8.1 and Splunk SOAR (Security Orchestration, Automation and Response) 6.4 have additionally been enhanced to provide improved threat visibility and automated workflows when combined with Cisco XDR.

Frank Dickson, Group Vice President of Security & Trust at IDC, says: “Cisco XDR aims to address key challenges in the SOC with its focus on 'Clear Verdict. Decisive Action. AI Speed.'

“The combination of Instant Attack Verification, XDR Storyboard visualisations and automated XDR Forensics offers a streamlined approach to threat management.”

Cisco and ServiceNow’s enhanced collaboration

Building on its recent AI Defense initiative, Cisco has announced a deeper integration with ServiceNow to enhance AI risk management and governance capabilities.

The first integration will bring together Cisco AI Defense with ServiceNow SecOps – a platform that automates and streamlines security incident and vulnerability management by integrating security and IT operations – to provide more holistic AI risk management and governance.

Foundation AI
The company has introduced Foundation AI, a team formed from its acquisition of Robust Intelligence, focusing on developing technology to address security challenges in the AI era. This team has released an open-source reasoning model specifically designed for security applications.

The Foundation AI team will also provide benchmarks for evaluating cybersecurity models against real-world security scenarios, alongside tools for teams to adapt these models for specific requirements.

AI Supply Chain Risk Management controls
Cisco has also developed AI Supply Chain Risk Management controls to secure AI application components.

These controls address vulnerabilities present even before model deployment, such as malware in AI model files and compromised datasets from open-source repositories.

The controls combine threat assessment and detection with network enforcement to identify and block malicious AI model files, detect and block files with restrictive open-source software licences that might create compliance risks and enforce policies against models from prohibited suppliers.

Enhanced Industrial Threat Defense solution
Meanwhile, for industrial sectors, Cisco has enhanced its Industrial Threat Defense solution through integrations with Cisco Cyber Vision, including Cisco Vulnerability Management and Splunk Asset and Risk Intelligence to prioritise operational technology cyber risks.

Additional integrations include Cisco Secure Firewall for automating industrial network segmentation and the Splunk OT Security add-on for unified IT and operational technology visibility within security operations centres.

“Cisco is continuing its mission to secure AI and leverage AI for security with novel open-source models and tools, new AI agents and IoT advancements, alongside the full breadth of the Cisco Security Cloud,” Jeetu says.

“Together, these innovations will help level the playing field and deliver AI innovation that makes all businesses more secure.”

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