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Evidence record 12241 · automatically gathered

(A)iSpy: Parasitic Trojans for Machine Learning Infrastructure

Modern machine learning (ML) pipelines depend heavily on third party libraries for graph compilation and hardware acceleration. While current practices audit data and model artifacts or rely on file integrity checks, the execution environment remains implicitly trusted. This blind spot enables active threats where a malicious runtime module interacts directly with live training and inference dynamics: exploiting this interaction allows the Trojan to support complex objectives that are challengin

Record details

Published: 20 July 2026
Source: arXiv cs.CR (AI security)
Category: Research
Topics: Transparency · Environment
Retrieved: 21 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

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How to cite this record

ethics.ai (20 July 2026), “(A)iSpy: Parasitic Trojans for Machine Learning Infrastructure,” evidence record 12241, https://ethics.ai/record/12241 (originally published by arXiv cs.CR (AI security)).

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