AI Threat Taxonomy
Comprehensive classification of AI security threats, attack vectors, and mitigation strategies
T1: Memory & State Attacks
T1.1: Memory Poisoningcritical
Malicious actors inject harmful content into AI agent memory systems to influence future behavior and responses
T1.2: Context Window Manipulationhigh
Exploiting limited context windows to hide malicious instructions or bypass safety checks
T2: Tool & Integration Attacks
T2.1: Tool Misusecritical
AI agents use integrated tools inappropriately or maliciously, potentially causing system compromise
T2.2: Plugin/Extension Vulnerabilitieshigh
Exploiting vulnerabilities in third-party plugins or extensions
T3: Privilege & Access Control
T3.1: Privilege Compromisecritical
Unauthorized elevation or abuse of AI system privileges
T3.2: Cross-Tenant Data Leakagecritical
Data leaking between different users or organizations
T4: Information Integrity
T4.1: Cascading Hallucinationhigh
False information propagating through interconnected AI systems
T4.2: Misinformation Injectionhigh
Deliberate injection of false information into AI responses
T5: Goal & Alignment Attacks
T5.1: Goal Hijackingcritical
Manipulating AI system objectives to achieve unintended outcomes
T5.2: Alignment Bypasscritical
Circumventing safety alignment and ethical constraints
T6: Identity & Authentication
T6.1: Identity Spoofinghigh
AI systems impersonating legitimate users or entities
T6.2: Authentication Bypasscritical
Circumventing authentication mechanisms in AI systems
T7: Execution & Code Attacks
T7.1: Remote Code Executioncritical
Executing arbitrary code through AI system vulnerabilities
T7.2: Supply Chain Attackscritical
Compromising AI systems through dependencies
T8: Autonomous Agent Risks
T8.1: Rogue Agent Behaviorcritical
AI agents acting outside intended parameters
T8.2: Agent Collusionhigh
Multiple AI agents coordinating for malicious purposes
T9: Deception & Manipulation
T9.1: Capability Concealment (Sandbagging)high
Models hiding true capabilities during evaluation
T9.2: Strategic Deceptionhigh
Models providing misleading information about capabilities or intentions
Emerging AI Threats & Attack Vectors
Next-generation threats requiring proactive defense strategies and continuous research
Multimodal Fusion Attacks
Active researchAttacks exploiting vulnerabilities across different data types simultaneously
Complete model compromise
Implement cross-modal validation and consistency checks
Semantic Adversarial Examples
Emerging threatInputs maintaining semantic meaning while evading detection
Bypassed content filters
Deploy semantic analysis and contextual understanding
Collaborative Inference Attacks
Theoretical researchCoordinated attacks in distributed AI systems
System-wide compromise
Implement Byzantine fault tolerance and consensus mechanisms
Quantum Computing Threats
Future considerationFuture threats from quantum computing capabilities
Cryptographic vulnerabilities
Prepare post-quantum cryptography migration
Synthetic Data Poisoning
Active developmentPoisoning attacks using AI-generated synthetic data
Training data corruption
Implement data provenance and authenticity verification
Risk Assessment Matrix
| Impact | Unlikely | Possible | Likely | Certain |
|---|---|---|---|---|
| Critical | Medium | High | Extreme | Extreme |
| High | Low | Medium | High | Extreme |
| Medium | Low | Low | Medium | High |
| Low | N/A | N/A | N/A | N/A |