INTEL_REPORT
arXiv — Cryptography & Security (cs.CR) · published 5/11/2026, 4:00:00 AM · TLP amber
Summary
Ingested excerpt (first ~500 chars of normalized text).
McNdroid: A Longitudinal Multimodal Benchmark for Robust Drift Detection in Android Malware arXiv:2605.06894v1 Announce Type: new Abstract: Machine learning (ML) in real-world systems must contend with concept drift, adversarial actors, and a spectrum of potential features with varying costs and benefits. Malware naturally exhibits all of these complexities, but for the same reason, it is challenging to curate and organize data to study these factors. We present McNdroid, to…
https://arxiv.org/abs/2605.06894
sha256:646fa5ea31cdc5c7f071fa2d72abc6f19faca6d160cb9c6c2c8136405e2deeee
What we pulled out
Deterministic extractor (IOC + allowlisted tokens + ATT&CK IDs present in DB).
Indicators
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No indicators linked for this report.
Malware families
Allowlist token matches only.
Threat actors mentioned
Allowlist mentions — not a formal attribution verdict.
ATT&CK techniques
MITRE IDs referenced in text and present in local technique table.
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