This survey analyzed 132 web application security tutorials, finding that most lack concrete implementation details and recommending that the presence of runnable code and links to official resources…

The paper argues that agent security must be treated as a systems problem, requiring the enforcement of security invariants at the system level rather than solely relying on improving the underlying A…

This paper provides the first comprehensive security analysis of the Agent Skills framework, identifying severe structural vulnerabilities that require fundamental architectural changes rather than si…

This paper proposes a Security Decision Support System that recommends security control sub-families using a curated dataset and multi-agent model.

SMSI is a novel neuro-symbolic pipeline that automates threat modeling for cyber-physical systems by generating a prioritized list of NIST 800-53 security controls directly from a SysML architecture m…

This paper systematically reviews airport cybersecurity threats, mapping them to the MITRE ATT&CK Matrix to provide actionable recommendations for modern defense models like Zero Trust.

The paper systematically maps LLM agent vulnerabilities by testing 10,000 prompt variations, finding that 'goal reframing' language is the primary trigger for exploitation, rather than broad adversari…

The paper introduces False Security Confidence (FSC), a new metric to measure the inherent prevalence of security vulnerabilities in code generated by LLMs that are otherwise functionally correct, eve…

This paper provides the first systematic threat analysis of State-Space Models (SSMs) in safety-critical applications, introducing novel attack classes and formal metrics to quantify their security an…

The paper proposes ConGISATA, a continuous, gamified framework using embedded mobile sensors to enhance individual information security awareness by transforming passive risks into active learning opp…

The paper presents an approach to automatically generate a large number of diverse and complex cybersecurity scenarios that model enterprise IT systems for training purposes.

The paper argues that LLM agent security is fundamentally an agent-human interaction (AHI) problem, demonstrating that industry practices rely on human-centric mechanisms while academic research focus…

The paper investigates how AI coding assistants shift developers' security focus from proactive prevention to reactive review, finding that this structural change is reinforced by current tool interac…

The paper introduces a validated, consensus-labeled prompt bank that separates requests for executable malicious code (weapons) from requests for general harmful security knowledge, providing a more g…

The paper argues that current Software Bills of Materials (SBOMs) are fundamentally flawed due to a lack of shared understanding regarding what constitutes a 'component,' demonstrating that existing t…

The paper introduces STRIKE, a multi-dimensional structured taxonomy designed to provide a comprehensive and unified framework for classifying the rapidly evolving complexity of modern cybercrimes.

The paper proposes AlertStar, a hyper-relational knowledge graph completion framework, to improve cyber-attack prediction by incorporating rich flow-level metadata (qualifiers) into path reasoning ove…

The paper introduces TorchSight, an open-source local system using a fine-tuned Qwen 3.5 27B model that achieves high accuracy (95.0%) in classifying sensitive security documents without relying on ex…

The paper introduces the Mitigation-Aware Chain-of-Thought (MA-CoT) framework, which significantly enhances the security reliability of code generated by LLMs across multiple languages and models.