OdTM

OWASP Ontology-driven threat modelling OdTM framework Ontology-driven Threat Modelling OdTM framework is a set of means for implementation of an ontological approach into automatic threat modelling of computer systems. It is an OWASP Incubator Project. The ontological approach, provided by the Od...

security-culture

OWASP Security Culture This is a documentation project that discusses the importance and benefits of establishing a security culture when building an application security program. The guide considers security at each stage of the Software Development LifeCycle SDLC, helping to create secure...

stride-gpt

STRIDE GPT è uno strumento di threat modelling basato sull'IA che sfrutta i Large Language Models LLM per generare modelli di minaccia e alberi di attacco per una determinata applicazione basandosi sulla metodologia STRIDE. Gli utenti forniscono i dettagli dell'applicazione, come il tipo di...

stride-gpt v0.19.0

STRIDE GPT is an AI-powered threat modelling tool that leverages Large Language Models LLMs to generate threat models and attack trees for a given application based on the STRIDE methodology. Users provide application details, such as the application type, authentication methods, and whether the...

Web-Binary-Exploitation-Security-Assessment

Web & Binary Exploitation — Security Assessment Coursework fr...

Designing a GDPR-Compliant Security Architecture for Remote Elderly Care Systems: A Privacy-By-Design Approach

IoMT-based remote elderly care systems generate continuous streams of sensitive health data, yet existing security architectures have not simultaneously addressed three interdependent challenges: GDPR-compliant edge-layer pseudonymisation, elderly-specific zero-interaction usability as a binding...

GDM AI Control Roadmap

AI agents are rapidly accelerating work at frontier AI companies, helping with AI R&D, cyber-defence, and advancing scientific discoveries. As these agents become more tightly integrated into our systems, unlocking their full potential requires rethinking how we do security. We should not assume...

TRACE: A Threat Modelling Methodology for Distributed, Cloud-First, and Decentralized Organisations

Established threat modelling methodologies STRIDE, PASTA, Trike, OCTAVE, LINDDUN, attack trees, and adversary-behaviour catalogues such as MITRE ATT&CK were designed for software products and enterprises with a discernible security perimeter, a single owning organisation, and a clean separation...

Backchaining Loss of Control Mitigations from Mission-Specific Benchmarks in National Security

Affordances and permissions are promising and timely safety levers for mitigating Loss of Control LoC threats in high-stakes deployment contexts, such as national security. Deployers in defense and intelligence could rely on several approaches to identify which affordances and permissions should ...

Threat Modelling Using Domain-Adapted Language Models: Empirical Evaluation and Insights

Large Language ModelsLLMs are increasingly explored for cybersecurity applications such as vulnerability detection. In the domain of threat modelling, prior work has primarily evaluated a number of general-purpose Large Language Models under limited prompting settings. In this study, we extend th...

CVE-2026-42480

A stack-based out-of-bounds read vulnerability in VrmlDataScene::ReadLine in the VRML parser in Open CASCADE Technology OCCT V800rc5 allows attackers to cause a denial of service via a crafted VRML file. The issue occurs because the quoted-string escape handler uses ptr++anOffset without proper...

ATLAS: AI-Assisted Threat-To-Assertion Learning for System-On-Chip Security Verification

This work presents ATLAS, an LLM-driven framework that bridges standardized threat modeling and property-based formal verification for System-on-Chip SoC security. Starting from vulnerability knowledge bases such as Common Weakness Enumeration CWE, ATLAS identifies SoC-specific assets, maps...

Towards a Blockchain-Based CI/CD Framework to Enhance Security in Cloud Environments

Security is becoming a pivotal point in cloud platforms. Several divisions, such as business organisations, health care, government, etc., have experienced cyber-attacks on their infrastructures. This research focuses on security issues within Continuous Integration and Deployment CI/CD pipelines...

Towards Reliable and Practical LLM Security Evaluations Via Bayesian Modelling

Before adopting a new large language model LLM architecture, it is critical to understand vulnerabilities accurately. Existing evaluations can be difficult to trust, often drawing conclusions from LLMs that are not meaningfully comparable, relying on heuristic inputs or employing metrics that fai...

EUVD-2023-50793

Malicious code in bioql PyPI...

EUVD-2024-48645

Malicious code in bioql PyPI...

EUVD-2023-57853

Malicious code in bioql PyPI...

Threat Modeling for Enhancing Security of IoT Audio Classification Devices under a Secure Protocols Framework

The rapid proliferation of IoT nodes equipped with microphones and capable of performing on-device audio classification exposes highly sensitive data while operating under tight resource constraints. To protect against this, we present a defence-in-depth architecture comprising a security protoco...

Collaborative Intelligence: Topic Modelling of Large Language Model Use in Live Cybersecurity Operations

Objective: This work describes the topic modelling of Security Operations Centre SOC use of a large language model LLM, during live security operations. The goal is to better understand how these specialists voluntarily use this tool. Background: Human-automation teams have been extensively...

The CryptoNeo Threat Modelling Framework (CNTMF): Securing Neobanks and Fintech in Integrated Blockchain Ecosystems

The rapid integration of blockchain, cryptocurrency, and Web3 technologies into digital banks and fintech operations has created an integrated environment blending traditional financial systems with decentralised elements. This paper introduces the CryptoNeo Threat Modelling Framework CNTMF, a...