Introduction to Cisco AI Defense - 5/24/2025
A hands-on learning lab that introduces Cisco AI Defense, covering AI security threats, model validation, runtime protection, and best practices for securing enterprise AI across its lifecycle
Introduction to Cisco AI Defense Lab
Cisco AI Defense is a comprehensive enterprise solution designed to secure artificial intelligence systems throughout their entire lifecycle, from development and deployment to runtime usage. This learning lab provides a structured, hands-on introduction to AI Defense, guiding learners through real-world AI security challenges and demonstrating how Cisco’s tools protect AI applications from emerging threats.
As organizations rapidly adopt AI technologies, they encounter new and complex risks that traditional security solutions are not equipped to handle. According to Cisco’s 2024 AI Readiness Index, fewer than one-third of organizations feel confident in their ability to detect or prevent tampering with AI systems. The Cisco AI Defense lab addresses this gap by teaching participants how to gain visibility, validate AI systems, and enforce protections in enterprise environments.
🎯 Understanding AI Security Threats
The lab begins by exploring the unique threat landscape surrounding AI. Participants learn about common attack vectors such as:
- Prompt Injection - Manipulating AI systems through crafted inputs
- Model Poisoning - Compromising training data or model weights
- Jailbreaking - Bypassing safety controls and guardrails
- Denial-of-Service - Overwhelming AI systems with malicious requests
- Data Exfiltration - Extracting sensitive information through AI interfaces
These threats highlight why AI requires specialized security controls beyond conventional application and network defenses.
🛡️ Key Components of Cisco AI Defense
Cisco AI Defense is built on three core pillars that are explored throughout the lab:
Discover: AI Cloud Visibility
Focuses on identifying and inventorying AI assets across distributed environments. Learners see how organizations can automatically discover AI models, applications, and data sources, assess associated risks, and monitor compliance with internal policies.
Detect: AI Model and Application Validation
Introduces automated and AI-driven testing techniques. Through algorithmic red teaming and continuous assessments, AI Defense evaluates models against hundreds of potential vulnerabilities while aligning with industry standards such as NIST AI-RMF, MITRE ATLAS, and the OWASP LLM Top 10.
Protect: AI Runtime Protection
Demonstrates how AI Defense enforces real-time guardrails to block adversarial behavior. Participants learn how the platform mitigates prompt injections, prevents harmful outputs, detects misuse, and adapts dynamically as new threats emerge.
🔗 Integration and Threat Intelligence
The lab also highlights how AI Defense integrates seamlessly into Cisco’s Security Cloud, providing unified visibility and enforcement across the network. By leveraging Cisco’s mesh of security enforcement points and intelligence from Cisco Talos—the largest commercial threat intelligence team—AI Defense ensures protection against the latest AI-specific attack techniques.
💡 Hands-On Learning and Best Practices
Throughout the lab, learners deploy AI Defense components, test APIs and gateways, validate AI models, and observe how runtime protections operate in practice. The experience concludes with a summary of best practices, reinforcing how organizations can securely scale AI adoption while maintaining governance, compliance, and resilience.
This learning lab equips developers, security professionals, and IT teams with the foundational knowledge and practical skills needed to protect enterprise AI systems in an increasingly complex threat landscape.