MITRE AI Red Team demonstrates physical evasion attack on face identification
Attack on AI1 Research / proof of conceptAdversarial evasion
Researchers demonstrated a physical-domain evasion attack on a commercial face identification service to induce misclassification. The exercise combined traditional enterprise techniques with adversarial machine learning steps.
Details
- type
- Attack on AIAn AI model, agent or AI-powered product was the thing exploited, abused or leaked.
- categories
- Adversarial evasionInputs crafted to make a model misclassify or miss detections (perturbations, evasion of AI-based defences).
- Adversarial evasion
- owasp llm top 10
- no entry for these categories
- mitre atlas
- Both rows are derived from the type and categories (OWASP 2025 edition, ATLAS release 2026.09), not classified per record. How
- severity
- 1 · Research / proof of conceptDemonstrated by researchers; no known real-world exploitation.
- targets
- Enterprise deployment
- products
- Commercial Face Identification Service
- incident date
- 31 Mar 2023
- first reported
- 31 Mar 2023
- origin
- AVID
- classifier confidence
- 0.90 · published at or above 0.80; see the methodology
- tags
- mitre · adversarial-ml · evasion · avid
- record
- created 2026-10-18 06:56Z · updated 2026-10-18 06:56Z · json
Sources · 2
- 2023-03-31AVID-2023-V012: MITRE's AI Red Team demonstrated a physical-domain evasion attack on a commercial face identification service with the intention of inducing a targeted misclassification.AVID · github.com/avidml/avid-db/blob/main/vulnerabilities/2023/AVID-2023-V012.json
- 2023-03-31Face Identification System Evasion via Physical CountermeasuresMITRE ATLAS · atlas.mitre.org/studies/AML.CS0012
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