Volume 10 (2026-27)

The rapid enterprise adoption of agentic artificial intelligence (AI) has introduced a category of security risk that existing cyber security frameworks were not designed to address. With 78 per cent of Fortune 500 companies projected to deploy agentic AI by 2026 and the global market expected to reach US$89.6bn, the attack surface created by these autonomous workflows demands urgent attention from security practitioners. This paper examines the distinct threat model presented by agentic AI, drawing on recent high-profile incidents, including the weaponisation of a large language model in a state-sponsored espionage campaign affecting 30 organisations and the compromise of an open-source agent framework exposing 30,000 Internet-facing instances, to illustrate the consequences of inadequate controls. Grounded in the Open Worldwide Application Security Project’s Top 10 for Agentic Applications (2026) and the National Institute of Standards and Technology’s ongoing agentic AI security initiative, the paper proposes a five-layer defence-in-depth framework encompassing input validation, identity and least privilege, runtime sandboxing, human-in-the-loop governance, and continuous behavioural monitoring. It identifies sandboxing and least-privilege enforcement as the highest return on investment controls, provides a prioritised implementation roadmap, and discusses the emerging paradigm of cryptographic workflow authentication. The analysis concludes that organisations treating agentic AI security as an extension of traditional application security will find themselves critically exposed and that a purpose-built security architecture is now a business imperative. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: agentic AI; autonomous workflows; defence-in-depth; prompt injection; sandboxing; least privilege

Cyber threat intelligence (CTI) is considered an essential element of a robust cyber security programme. Given the relative nascency of the discipline, however, there is a degree of ambiguity among the community around what it takes to establish a credible CTI capability in support of the cyber security mission. At the same time, there is now a thriving industry offering commercial CTI products and services in support of the customer’s capability development efforts, with many instances of opportunistic vendors poised to exploit this fledgling market. This has spurred the growth of research and advisory companies that attempt to present an objective review and offer guidance around CTI vendor selection. Their perspective, however, is often heavily influenced by a small group of select vendors and the evaluation criteria is often incomplete and skewed towards the participating vendors. This paper makes the case for a first-principles approach that CTI teams can adopt as an unbiased anchor to guide their decisions around establishing an adequate CTI capability, and offers pragmatic recommendations to assist CTI teams with qualifying their prospective vendors to ensure good fit. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: threat intelligence; first principles; adversary; vendor selection; intelligence requirements; intelligence collection; intelligence analysis

Traditional security awareness programmes rely on annual training, phishing simulations, and engagement campaigns. These approaches generate activity and compliance metrics, but they do not effectively reduce human-driven security risk. This paper presents a strategic framework for shifting from campaign-based security awareness to behavioural risk mitigation, grounded in a decade of leading security awareness across one of the USA’s largest and most complex higher education systems. The framework addresses what prompted the shift, what analysis revealed about the limitations of traditional approaches, how buy-in was built to pivot toward behavioural risk mitigation, and what security leaders should consider when implementing similar transformations. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: behavioural risk mitigation; human risk management; security awareness; security culture; SebDB

In today’s evolving digital landscape, a new kind of AI has emerged: agentic artificial intelligence (AI) systems. These are not just tools but intelligent entities that act on their own, make decisions, and carry out tasks proactively. Once placed inside containerised cloud environments such as Kubernetes, however, these powerful agents open the door to a whole new category of security concerns. They often interact on the fly with application programming interfaces, data channels, and other AI agents, sometimes all at once, and not always in predictable ways. Recognising the risks, this paper introduces a formal framework designed to capture and analyse these unique vulnerabilities. Going beyond theory, the study offers a full threat taxonomy focused on agent behaviours, uses temporal logic to trace how agents and environments interact over time, and introduces a practical measure called the Agentic Vulnerability Exposure Metric (AVEM). To put this model to the test, researchers ran simulated cyberattacks on a Kubernetes-based orchestration system that was managing large language model (LLM)-powered agents. The results were eye-opening: AVEM was able to expose security holes such as weak isolation between agents, overlooked permissions, and routes for privilege escalation that had gone undetected before. To test the practicality of the model, real-world attack scenarios are simulated on a Kubernetes-managed AI platform utilising LLM agents. The findings reveal that AVEM effectively uncovers weaknesses such as poorly defined isolation boundaries, unexpected capabilities, and opportunities for privilege escalation between agents. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: generative AI; agentic AI; AI agents; cloud security; threat modelling; attack vectors; containerised environments; cyber security; vulnerability exposure; security framework; formal modelling; Kubernetes; autonomous systems

Systems are becoming increasingly interconnected, forming complex Systems of Systems (SoS) that are difficult to manage and secure. This paper addresses the challenges of governing the security status of such environments, particularly the need to preserve the richness of qualitative risk assessments while enabling scalable, standardised analysis. It proposes a graph-based approach that models risk scenarios quantitatively through the calculation of an ‘interest’ value, enabling prioritisation of countermeasures across large system perimeters. Combined with Boolean representations and event simulation, this framework provides a structured method for synthesising, monitoring and supporting decision-making in the management of large-scale system security. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: risk management; system of systems; rational analysis; operational research; graph theory

The rapid digitisation of critical infrastructure has made traditional fragmented risk assessment practices increasingly challenging to scale. For global industrial leaders managing hundreds of diverse projects, there is a real need for a unified methodology that ensures technical rigour, cross-project reproducibility, and scalability. This paper introduces the Advanced Risk Assessment Methodology for Industrial Systems (ARAMIS), an innovative framework developed through a strategic partnership between Airbus Protect and Alstom. ARAMIS merges the structured, requirement-driven security levels of ISA/IEC 62443 with the scenario-based approach of Expression des Besoins et Identification des Objectifs de Sécurité Risk Manager (EBIOS RM). The paper details the five-module structure of ARAMIS, its unique multilayered modelling of operational scenarios and its algorithmic approach to calculating security levels target (SL-T). Finally, it discusses the implementation of the methodology within the Fence risk management tool to ensure seamless reproducibility and knowledge capitalisation across global project portfolios. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: risk assessment; industrial cyber security; ISA/IEC 62443; EBIOS RM; critical infrastructure; transportation system; security levels; Fence risk assessment tool

Financial services institutions face increasing pressure from regulators, boards, and customers to demonstrate the effectiveness of their cyber security controls. Many organisations, however, operate extensive portfolios of security tools without clear evidence that these investments deliver measurable risk reduction. This paper examines the operational and governance challenges associated with tool sprawl and introduces the concept of ‘security debt’ as the accumulation of unvalidated exposures and misconfigurations. Drawing on practitioner experience and industry research, it argues that the core issue is not the absence of technology but the lack of systematic validation of control effectiveness. The paper proposes a structured four-phase model to streamline cyber security programme performance: baseline, integrate, remediate what matters, and automate and scale. The model emphasises alignment with recognised frameworks, including MITRE ATT&CK, the National Institute of Standards and Technology Cybersecurity Framework, the Center for Internet Security Critical Security Controls, and the Digital Operational Resilience Act, alongside continuous measurement of control performance. By shifting from activity-based to effectiveness-based metrics, organisations can improve visibility, prioritise remediation, and strengthen governance. The paper concludes that a disciplined focus on validation enables financial institutions to reduce exposure, improve returns on existing investments, and provide more meaningful, evidence-based reporting to senior stakeholders. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: cyber security effectiveness; tool sprawl; security debt; control validation; financial services; operational