This infographic outlines seven critical security principles for secure AI implementation. It warns that employees often use unsanctioned AI tools (“Shadow AI”), creating risks of data leakage and governance gaps. Organizations should gain visibility into AI usage, establish approved tools, and educate users. AI security must extend across the entire lifecycle, including data, models, APIs, and third-party components. Because AI heavily relies on open-source software, practitioners should use software composition analysis (SCA), maintain software bills of materials (SBOMs), and rigorously vet dependencies. The guide highlights emerging AI-specific threats such as prompt injection, model poisoning, data leakage, and AI-powered phishing and malware. It recommends adopting OWASP Top 10 for LL

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