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Notes on cybersecurity research
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From Threat Intelligence to Detection: Knowledge-driven Enrichment and Template-based Rule Grounding for Automated Sigma Rule Generation
The paper presents AUTOSIGMA, a system that automates the transformation of unstructured cyber threat intelligence (CTI) reports into relevant Sigma rules for threat detection. Instead of solely relying on language…
Beyond Success Rate: Cost-Aware Evaluation of Offensive and Defensive Security Agents
The research focuses on evaluating the efficiency and practicality of language model security agents in both offensive and defensive tasks, rather than just their peak offensive capability. The study uses cost-aware…
Beyond Attack-Success Rate: Action-Graded Severity Scale for Tool-Using AI Agents
The paper introduces an action-graded harm rubric for evaluating AI agents in a red-teaming scenario. This new method rates the severity of an agent's actions on a seven-level scale, considering factors such as…
Words Speak Louder Than Code: Investigating Cognitive Heuristics in LLM-Based Code Vulnerability Detection
In this research, the authors investigate how Large Language Models (LLMs) used for automated vulnerability detection in code are influenced by cognitive biases similar to those that affect human judgment. They present…
ShareLock: A Stealthy Multi-Tool Threshold Poisoning Attack Against MCP
The paper introduces a new method called ShareLock, which is a multi-tool threshold poisoning framework that can exploit the interactions between Language Model servers and external tools. This method is designed to…
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