Exposure management is becoming the cyber security backbone for India’s AI economy: Ben Mudie, Tenable

In conversation with Express Computer, Ben Mudie, Principal Security Engineer at Tenable, explains why exposure management is emerging as a foundational pillar of modern, preventive cyber security. He further outlines how a unified, contextual view of risk helps AI platforms remain secure, enables organisations to move from incident-driven firefighting to proactive resilience, and positions Indian AI exporters as trusted partners in a highly regulated global market.

What are the various aspects in which preventive security, like exposure management, acts as a competitive moat for Indian AI exporters?

Exposure management unifies siloed security data and shows how vulnerabilities, misconfigurations, identities and external threats intersect, replacing fragmented assessments with a continuously updated, contextual view of the attack surface. By mapping how attackers could realistically move through an environment, security teams can prioritise the issues that genuinely matter and communicate risk clearly to leadership.

For AI exporters operating MaaS, PaaS and other data-intensive services, this proactive visibility builds stronger trust with international customers, demonstrating robust alignment with requirements such as GDPR, HIPAA and partner due-diligence checks. It also strengthens operational resilience by anticipating threats and reducing downtime, improving service reliability and minimising the financial and reputational impact of breaches in a landscape where cloud exposures and third-party compromises are on the rise.

By shifting organisations from incident-driven firefighting to preventing disruptions before they occur, exposure management transforms cyber security from a cost of doing business into a strategic differentiator. This positions Indian AI companies as dependable, resilient and enterprise-ready partners in an increasingly competitive global market.

How can exposure management ensure AI platforms remain secure?

Exposure management leverages AI for prioritisation, passive network monitoring, dynamic application security testing and distributed scan engines to detect AI software, libraries and browser plugins. It continuously monitors the entire attack surface to discover and identify all sanctioned and unsanctioned AI usage across the enterprise environment. This provides a better understanding of user interactions, data flows, and activities that may introduce risk.

When exposure management solutions include an AI security Posture Management component, it helps organisations identify, prioritise, and manage the risk of AI exposure, including sensitive data leakage, misconfigurations, and unsafe integrations with external tools. It puts in place security guardrails and organisational policies to control how AI is used, preventing risky user behaviours and mitigating novel threats such as prompt injections, jailbreaks, and malicious output manipulation.

How does exposure management make organisations cyber resilient?

Exposure management supports a risk-informed approach to cyber security, continuously assessing the accessibility, exploitability and criticality of digital assets. By implementing this preventive approach, organisations will be better equipped to secure their environments in the face of constant cyber threats. It improves operational efficiency, reduces costs, protects against emerging threats and ensures that business-critical systems remain secure and uninterrupted.

An exposure management strategy relies on a technology platform that enables the discovery and aggregation of asset data across the entire external and internal attack surface. Seemingly elusive assets, including AI, cloud, IT, OT, IoT, identities, and applications, will become visible in a holistic view of the attack surface.

An exposure management platform detects the three preventable forms of risk attackers use to gain initial access and move laterally such as vulnerabilities, misconfigurations and excessive privileges. It moves beyond vulnerability management, aggregating findings by asset to calculate an overall risk score that enables security teams to quickly identify exposures that pose the greatest potential risk. It identifies asset, identity and risk relationships so teams can see high-risk assets and, more importantly, be able to see all related attack paths that lead to that asset. Such an approach mitigates the financial and operational consequences of data breaches, system outages and compliance violations, building resilience.

How has Tenable taken a lead in the exposure management domain and gained competitive advantage?

Tenable has taken a clear lead in exposure management by evolving its capabilities in lockstep with the expanding attack surface. While the company’s roots are in identifying vulnerabilities across traditional IT, its mission has always centred on helping organisations understand and reduce cyber risk. As environments became more complex, Tenable broadened its focus beyond vulnerabilities to provide unified, contextual insight across cloud, identity, AI workloads, web apps, OT, and even third-party ecosystems.

This vision comes together in the Tenable One Exposure Management Platform, which delivers a comprehensive, continuously updated view of where an organisation is exposed and how attackers could realistically move through its environment. By correlating risks across domains, Tenable enables teams to prioritise what matters most and close gaps before they are exploited.

As a global leader, it is our commitment to delivering a unified, proactive model for managing cyber risk.

Can you suggest a playbook for Indian AI companies looking to implement proactive or preventive security measures?

Effective exposure management begins with identifying every asset across cloud, IT, OT, IoT, hybrid and shadow environments and understanding what each asset does, its criticality and who can access it. Automated discovery and continuous monitoring establish the baseline for meaningful risk assessment.

The next step is identifying the risks that truly matter. Instead of treating every CVE as equal, exposure management focuses on vulnerabilities, misconfigurations, identity exposures, excessive permissions and attack paths that could realistically impact the business. By correlating asset relationships, threat intelligence and exploitability, organisations avoid analysing risks in isolation and see where exposures converge.

With this context, teams can prioritise remediation based on business impact, focusing first on exposures that lead directly to critical systems, sensitive data or regulatory obligations. Clear links to uptime, customer trust and financial operations help secure leadership engagement and support.

Remediation should also be risk-based and verifiable. Rather than handing IT long patch lists, security teams provide targeted guidance, validate that fixes are effective and maintain audit-ready reporting.

Finally, because the attack surface changes every day, exposure management must be continuous and adaptive. Ongoing monitoring, control validation and posture benchmarking help organisations keep pace with new assets, shifting permissions and evolving attacker techniques. This approach aligns security and IT, reduces noise, and enables cyber risk to be communicated in business terms that drive preventive action.