Synthetic Trust Attacks: Modeling How Generative AI Manipulates Human Decisions in Social Engineering Fraud
arXiv 2604.04951•a021f0e8fe1f66d61417f74c02f840cb5ef1aaf381fbbd332ee4eb07f2c6dbe1
IoT-securityLLM-agentsML-defenderNIDSRAGbackdoorblack-hole-attackcode-securitydata-exfiltrationdecision-layer-defensedeepfakeseBPFembedded-mlemotional-primingformal-verificationfraudgenerative-aimodel-governancepoisoningred-teamingretrieval-augmented-generationsafety-alignmentskill-exploitationsocial-engineeringvector-database
Paper metadata
- arXiv ID
- 2604.04951
- Version
- Not specified by this published record
- Category
- Computer Science — Cryptography and Security (cs.CR)
The PDF link points to arxiv.org. Baitaphish does not expose a private stored PDF.
Evidence and limitations
- Source ID
- arxiv_cs_cr
- Record identifier
- a021f0e8fe1f66d61417f74c02f840cb5ef1aaf381fbbd332ee4eb07f2c6dbe1
- Enrichment time
- 2026-04-08T07:23:34Z
- 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.