Embedding Inference Attack
2026-07-03T07:23:36Z•94efb37ee1071cf0d0bf263558270671f0f0e24882bf0d2200cbcc937906f150
CPS recoveryIDSLLM safetyLVLMML surrogatesRAGadversarial triggersblack-box attackscognitive firewallembedding inferencefederated learningforensics and detection gaps','malware detection','hamm-grams','generative AIhardware trojansidentity document forgeryintrusion detectionmemory corruptionmodel fingerprintingoverthinking slowdownphysical-world attacksretrieval-augmented-generationrobotics securitystandard cell librarysupply-chain riskzero-trust
What happened
This feed contains multiple 2026 security-relevant arXiv papers spanning ML/LLM safety, hardware supply-chain threats, CPS/robotics resilience, IDS, and document forensics. Key findings include: a new embedding inference attack that fingerprints hidden embedding models from only retrieved document sets (black-box); the Cognitive Firewall, a multi-gate, zero‑trust runtime oversight that substantially reduces LLM jailbreak success; a survey on generative AI + federated learning for IDS highlighting dual-use risks and dataset/benchmark gaps; a practical threat model demonstrating stealthy supply‑
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_cr
- Record identifier
- 94efb37ee1071cf0d0bf263558270671f0f0e24882bf0d2200cbcc937906f150
- Enrichment time
- 2026-07-03T07:23:36Z
- AI-assisted enrichment
- Yes
This record may overlap with other records. Its enrichment can be incomplete or wrong, and machine assistance was used. Validate consequential decisions against the linked source and your own environment.