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AI agents automate IoT vulnerability exploitation with 95% success rate

By PulseAugur Editorial · [2 sources] ·

Researchers have developed VEXAIoT, an autonomous multi-agent framework designed to discover and exploit vulnerabilities in Internet of Things (IoT) devices. This system leverages Large Language Model (LLM) agents and offensive security tools to automate reconnaissance, attack planning, and execution. Evaluated in controlled environments like IoTGoat and Metasploitable, VEXAIoT demonstrated a high success rate of up to 95% across various attack scenarios mapped to OWASP IoT vulnerabilities, with most attacks completing in under two minutes. AI

IMPACT Automates IoT security testing, potentially accelerating vulnerability discovery and patching cycles.

RANK_REASON The cluster contains an academic paper detailing a new AI framework for security research.

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

AI agents automate IoT vulnerability exploitation with 95% success rate

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The cluster contains an academic paper detailing a new AI framework for security research.
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COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Katherine Swinea, Kshitiz Aryal, Lopamudra Praharaj, Maanak Gupta ·

    VEXAIoT: Autonomous IoT Vulnerability EXploitation using AI Agents

    arXiv:2607.09653v1 Announce Type: cross Abstract: Internet of Things (IoT) systems are inherently vulnerable due to constrained hardware, outdated firmware, and insecure default configurations, creating a need for scalable and adaptive security testing approaches. While recent ad…

  2. arXiv cs.AI TIER_1 English(EN) · Maanak Gupta ·

    VEXAIoT: Autonomous IoT Vulnerability EXploitation using AI Agents

    Internet of Things (IoT) systems are inherently vulnerable due to constrained hardware, outdated firmware, and insecure default configurations, creating a need for scalable and adaptive security testing approaches. While recent adoptions of Large Language Model (LLM) agents have …

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