https://taxonomy.eticas.ai/risk/evasion-attacks
Maturity: established
Adversarial perturbations crafted to force misclassification or attacker-chosen outputs at inference time, with or without access to model internals. Narrowed from the former adversarial-attacks (which also covered poisoning and extraction) to evasion specifically; those concerns now live in data-poisoning and model-extraction respectively.
System type: ADM and LLM systems
Lifecycle stages: In Processing, Post Processing
| Framework | Reference |
|---|---|
| AIUC-1 — AI Underwriting Company Standard | Detect adversarial input |
| Framework | Reference |
|---|---|
| W3C Data Privacy Vocabulary — AI Extension | Adversarial Attack |
| MIT AI Risk Repository | AI system security vulnerabilities and attacks |
| IBM AI Risk Atlas | Inference → Robustness → Adversarial robustness |