From Discovery to Defense: Why AI Red Teaming Is the Next Step After AI-SPM

Snyk has launched Evo AI-SPM, the first operational layer of its AI Security Fabric, providing a system of record for AI risk by discovering AI models, frameworks, datasets, and agent infrastructures within code. This tool uncovers "Shadow AI" components hidden in repositories and developer environments, allowing them to be governed and assessed for security. Evo Agent Red Teaming automates adversarial testing by simulating attacks on AI endpoints to evaluate their security, focusing on scenarios like prompt manipulation and sensitive data exposure. The system provides structured findings that align with industry standards, enabling teams to understand vulnerabilities and demonstrate compliance. Evo's security lifecycle includes discovering AI assets, assessing their risk, testing under adversarial conditions, and feeding results into governance and remediation, offering a continuous validation cycle rather than isolated tools. This approach addresses the unique challenges of AI systems, which are prompt-driven, contextual, and non-deterministic, creating new attack surfaces that traditional security tools cannot effectively cover. Evo Agent Red Teaming integrates into developer workflows, allowing continuous security validation through local runs or CI/CD pipelines, thus making AI security testing part of everyday development rather than sporadic audits.