INTEL_REPORT
arXiv — Cryptography & Security (cs.CR) · published 6/18/2026, 4:00:00 AM · TLP amber
Summary
Ingested excerpt (first ~500 chars of normalized text).
TIGER: Inverting Transformer Gradients via Embedding-Subspace Distance Optimization arXiv:2606.18312v1 Announce Type: new Abstract: Federated learning allows multiple clients to jointly train a shared model by sending gradient updates to a central server while keeping raw inputs local. However, prior gradient inversion attacks show that these updates can reveal enough information to reconstruct client inputs. Existing attacks on transformers either optimize dummy inputs to m…
https://arxiv.org/abs/2606.18312
sha256:f36c162223aaeffb3a382d2789c3cb8edd682b3a11ed33c4b96a24c0522d78b7
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Indicators
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Malware families
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Threat actors mentioned
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ATT&CK techniques
MITRE IDs referenced in text and present in local technique table.
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