AML.T0031
Erode AI Model Integrity

MITRE source definition

Adversaries may degrade the target model's performance with adversarial data inputs to erode confidence in the system over time. This can lead to the victim organization wasting time and money both attempting to fix the system and performing the tasks it was meant to automate by hand.

Source modified 2026-05-27. Reproduced from the pinned ATLAS release; inline technique links resolve to local reference pages.

Parent, sub-techniques and ATT&CK references

No explicit relationship in this pinned source.

Source-backed defensive context

MITRE mitigations

• AML.M0003 Predictive AI Model Hardening
• AML.M0006 Predictive AI Ensembles
• AML.M0010 Predictive AI Input Restoration
• AML.M0015 Predictive AI Adversarial Input Detection

MITRE case studies

• AML.CS0005 Attack on Machine Translation Services · Exercise
• AML.CS0006 ClearviewAI Misconfiguration · Incident
• AML.CS0009 Tay Poisoning · Incident
• AML.CS0019 PoisonGPT · Exercise
• AML.CS0025 Web-Scale Data Poisoning: Split-View Attack · Exercise
• AML.CS0064 Poisoned GGUF Templates: Inference-Time Supply Chain Attack · Exercise

These are explicit source relationships, not independently reproduced incidents or validated detection coverage.

Simulation and telemetry boundary

This is a technique reference page, not a runnable simulation. No ATLAS-specific telemetry mapping, local attack execution or detector validation is asserted. MITRE maturity describes its source evidence, not a 1200km lab result.

For broader context—not technique-specific control mappings—see AI Security, AI Security Course, and detection-validation methodology.

Provenance and attribution

Immutable MITRE ATLAS source · Import provenance · Attribution and transformation notice · Apache License 2.0

Copyright 2021-2026 MITRE. Source text and explicit relationships are retained; navigation, formatting and local links are provided by 1200km.

No explicit relationship in this pinned source.