RedShell fine-tunes LLMs on enhanced malicious PowerShell data to produce syntactically valid offensive code for pentesting, reporting over 90% validity, strong semantic match to references, and better edit-distance similarity than prior methods plus functional execution success.
arXiv preprint arXiv:2402.00891 (2024), https://arxiv.org/pdf/2402.00891
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citing papers explorer
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Towards Automated Pentesting with Large Language Models
RedShell fine-tunes LLMs on enhanced malicious PowerShell data to produce syntactically valid offensive code for pentesting, reporting over 90% validity, strong semantic match to references, and better edit-distance similarity than prior methods plus functional execution success.
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LanG -- A Governance-Aware Agentic AI Platform for Unified Security Operations
LanG presents a governance-aware agentic AI platform for unified security operations that reports strong performance on incident correlation, rule generation, attack reconstruction, and AI safety guardrails in an open-source package.
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SentinelSphere: Integrating AI-Powered Real-Time Threat Detection with Cybersecurity Awareness Training
SentinelSphere integrates an AI threat detector using an enhanced DNN on benchmark datasets with a fine-tuned quantized LLM for user training and awareness.