ExCyTIn-Bench is the first benchmark of 7542 questions from Microsoft Sentinel threat investigation graphs, where the best LLM agent achieves a reward of 0.606.
When llms meet cybersecurity: A systematic literature review,
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VulGD is a dynamic open-access graph database that aggregates vulnerability data from multiple sources and uses LLM embeddings to enable more accurate risk assessment and threat prioritization.
A framework detects LLM anomalies including hallucinations, jailbreaks, and backdoors by forensic inspection of layer-wise hidden state patterns, reporting over 95% accuracy with minimal computational overhead.
citing papers explorer
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ExCyTIn-Bench: Evaluating LLM agents on Cyber Threat Investigation
ExCyTIn-Bench is the first benchmark of 7542 questions from Microsoft Sentinel threat investigation graphs, where the best LLM agent achieves a reward of 0.606.
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VulGD: A LLM-Powered Dynamic Open-Access Vulnerability Graph Database
VulGD is a dynamic open-access graph database that aggregates vulnerability data from multiple sources and uses LLM embeddings to enable more accurate risk assessment and threat prioritization.
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Exposing the Ghost in the Transformer: Abnormal Detection for Large Language Models via Hidden State Forensics
A framework detects LLM anomalies including hallucinations, jailbreaks, and backdoors by forensic inspection of layer-wise hidden state patterns, reporting over 95% accuracy with minimal computational overhead.