AI Supply Chain Security
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AI Safety Guide: 21 Risk Checklists and Defense Strategies for Artificial Intelligence Safety
Critical levels (6): cue injection, jailbreak cueing, AI supply chain compromise, training data poisoning, model inversion, deep faking
Advanced (10): model misuse, shadow cueing, cue obfuscation, adversarial cue chaining, internal misuse, regulatory non-compliance, AI social engineering, human error, watermark circumvention, algorithmic bias
Intermediate (4): data breach, brand damage, DoS attack, lack of auditability
Low-level (1): cross-model inconsistency -
AI Security: Building an Enterprise AI Security System Based on ATT&CK Methodology
This paper takes the AI security threat matrix as the core framework, and based on the mature ATT&CK methodology, it systematically elaborates on the full lifecycle security threats faced by AI systems, including key attack techniques such as data poisoning, model extraction, privacy leakage, confrontation samples, and cue word injection, etc., and puts forward the corresponding defense strategies and enterprise landing solutions, providing AI engineers, security engineers, and CSOs with professional technical Reference.
