AI introduces risk across every traditional security domain — plus entirely new risk categories that existing frameworks don't fully address. This section maps the landscape.
Risk Description Impact
Prompt Injection Untrusted input hijacks model behavior Data breach, unauthorized actions Data Poisoning Compromised training/fine-tuning data Backdoored model behavior Model Theft Extraction of proprietary model weights IP loss, competitive damage Adversarial Evasion Crafted inputs bypass AI-powered security Security control failure Hallucination Confident generation of false information Bad decisions, legal liability Training Data Leakage Model memorizes and reveals sensitive data Privacy violation, regulatory breach
Risk Description Impact
Model Drift Performance degrades over time Unreliable outputs Dependency on Third-Party Models Vendor lock-in, API changes Business continuity Shadow AI Employees using unauthorized AI tools Data leakage, compliance gaps Automation Bias Over-reliance on AI recommendations Poor human decision-making
Risk Description Impact
Privacy Violations PII in training data or outputs GDPR/CCPA fines IP Infringement Model generates copyrighted content Litigation Bias & Discrimination Model outputs reflect training data biases Regulatory action, reputational harm Lack of Explainability Can't explain AI decision-making Regulatory non-compliance
Risk Description Impact
Competitive Disadvantage Failing to adopt AI effectively Market share loss Reputational Damage AI system causes public harm Brand damage Regulatory Uncertainty Evolving AI regulations Compliance gaps