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VQV Signal

OPEN SOURCE SOURCE-BACKED TECHNICAL

CyberLLM: A Multi-Agent LLM Framework for Autonomous Detection and Guarded Response in Automotive Cybersecurity

Software-Defined Vehicles (SDVs) expand the automotive attack surface across source code, runtime logs, and deployment topologies, while safety constraints forbid autonomous agents from acting without oversight. This paper presents CyberLLM, a multi-agent, LL...

Source: arXiv · arxiv.org Published 2026-08-06T23:39:13+00:00 Detected 2026-08-10T05:17:41+00:00
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Software-Defined Vehicles (SDVs) expand the automotive attack surface across source code, runtime logs, and deployment topologies, while safety constraints forbid autonomous agents from acting without oversight. This paper presents CyberLLM, a multi-agent, LL...

Software-Defined Vehicles (SDVs) expand the automotive attack surface across source code, runtime logs, and deployment topologies, while safety constraints forbid autonomous agents from acting without oversight. This paper presents CyberLLM, a multi-agent, LLM-orchestrated framework that autonomously detects...

Signal Strength 95% Technical label SOURCE-BACKED Public Interest 18 Category OPEN SOURCE Reader Depth TECHNICAL

Signal Strength reflects source quality, relevance, freshness and evidence. Public Interest helps organize discovery; it is not proof of truth.

Public Interest components
Recognizable Entity Score 0 Practical Impact Score 0 Novelty Interest Score 48 Consequence Score 34 Curiosity Score 16 Shareability Score 17

VQV surfaced this signal because it is recent, relevant to AI Agents, connected to arXiv.