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Drishti: AI-Led Human-Directed Vulnerability Auditing for 5G Cores

Drishti pairs AI-driven defect candidate generation with expert human triage for 5G core codebases, tackling the validation bottleneck that limits AI-assisted vulnerability discovery at scale.

Summary written by editorial AI · Source link below

Filed by arXiv Crypto & Security1 min readRead at source ↗

arXiv:2608.30112v1 Announce Type: new Abstract: Candidate generation for open-source vulnerabilities is no longer scarce. AI-assisted code review now produces defect candidates cheaply, and industry programs pair them with expert human triage. The remaining scarcity is validation and impact assessment, and the gap is largest in critical-infrastructure software like 5G cores. Here, validation has four costs: verification, reachability, impact, and fix-completeness. We present Drishti, an AI-led

Editorial Analysis

Why it matters

As European telcos roll out 5G under NIS2 obligations, scalable vulnerability auditing of open-source 5G components is critical to infrastructure resilience.

What to do

Assess AI-augmented code-auditing workflows for your critical open-source dependencies, prioritising components in regulated infrastructure.

Board brief

AI-assisted security auditing of 5G infrastructure can uncover vulnerabilities at scale — important as telecom becomes a NIS2-critical sector.

Forward-looking interpretation drafted by editorial AI under human review — not a reproduction of the source. See methodology.

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