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AI security records indexed from public vulnerability, risk, and attack datasets.
Showing 1481-1500 of 3623 records
Cyber offense is an AI risk.
Business and Data Understanding groups 12 AI defenses for the AI lifecycle.
Technical - Cyber groups 12 AI defenses by defense type.
Data Preparation groups 13 AI defenses for the AI lifecycle.
Use Pre-Trained Model is AI attack method AML.T0005.002 with evidence level: feasible. It includes 1 mitigation.
Resource Development is an ATLAS attacker goal with 13 related AI attack methods.
Supervision evasion propensity is an AI risk in 7. AI System Safety, Failures, & Limitations focused on 7.1 > AI pursuing its own goals in conflict with huma...
Privacy is an AI risk in 2. Privacy & Security focused on 2.1 > Compromise of privacy by leaking or correctly inferring sensitive information. It is most rel...
Privacy compromise is an AI risk in 2. Privacy & Security focused on 2.2 > AI system security vulnerabilities and attacks. It is most relevant during 2 - Pos...
Lack of transparency is an AI risk in 7. AI System Safety, Failures, & Limitations focused on 7.4 > Lack of transparency or interpretability. It is most rele...
Multimodal deepfakes is an AI risk in 4. Malicious Actors & Misuse focused on 4.3 > Fraud, scams, and targeted manipulation. It is most relevant during 2 - P...
Data-related (Manipulation of data by non-domain experts) is an AI risk in 7. AI System Safety, Failures, & Limitations focused on 7.3 > Lack of capability o...
Overreliance is an AI risk in 5. Human-Computer Interaction focused on 5.1 > Overreliance and unsafe use. It is most relevant during 2 - Post-deployment.
Deception - Synthetic identities is an AI risk in 4. Malicious Actors & Misuse focused on 4.3 > Fraud, scams, and targeted manipulation. It is most relevant...
Meta-cognition is an AI risk in 7. AI System Safety, Failures, & Limitations focused on 7.3 > Lack of capability or robustness. It is most relevant during 3...
Deep Learning Frameworks is an AI risk in 2. Privacy & Security focused on 2.2 > AI system security vulnerabilities and attacks. It is most relevant during 1...
Academic Misconduct is an AI risk in 4. Malicious Actors & Misuse focused on 4.3 > Fraud, scams, and targeted manipulation. It is most relevant during 2 - Po...
Factuality Errors is an AI risk in 3. Misinformation focused on 3.1 > False or misleading information. It is most relevant during 2 - Post-deployment.
ML Model Engineering groups 15 AI defenses for the AI lifecycle.
Hardware is AI attack method AML.T0010.000 with evidence level: feasible. It includes 1 related AI risk.