Head-On Collision: The Unavoidable Merging of External Risks and Protection Strategies
In a rapidly evolving digital landscape, the traditional approach to risk management is no longer sufficient. A shared, connective 'tissue' is allowing companies to break out of isolated workflows and move towards a networked approach to risk management.
This shift in approach was underscored by a significant incident in the US healthcare system in 2024, which was dubbed the most consequential incident of its kind in history by the American Hospital Association. The incident highlighted the vulnerability of the healthcare supply chain due to a single point of failure in a third-party vendor, causing nationwide operational disruptions in hospitals and medical offices.
The modern 'software as a service' (SaaS) delivery model, as stated by Patrick Opet, Chief Information Security Officer at J.P. Morgan Chase, is creating a substantial vulnerability that is weakening the global economic system. This vulnerability is further exacerbated by the fact that 30% of breaches were linked to third-party involvement, according to the 2025 Verizon Data Breach Investigation Report.
To address this dynamic threat environment, forward-thinking CISOs and security teams are now asking: "Is this vendor exposed right now?" instead of "Is this vendor compliant with our policies?". Security teams need real-time visibility into the assets and digital footprint of every third party, including IP ranges, cloud infrastructure, web applications, misconfigurations, and vulnerabilities.
AI is playing a crucial role in this transformation. It automates vendor assessments, continuously triages exposure data, correlates risk with threat intelligence, recommends remediations, and even generates and routes workflows. AI can accelerate the journey towards real-time, intelligence-driven third-party risk and exposure management, but it cannot define the destination.
Modern threat intelligence offers insights into emerging attacker techniques, active campaigns, exploit trends, and adversary infrastructure. The combination of three intelligence engines - integrated, correlated, and contextualized - is unlocked through AI. Context is crucial in separating important data from irrelevant data, as it is the cornerstone of prioritization and prediction.
The future of third-party risk management isn't about changing what security teams do, but empowering them to do it better than ever before. Major companies involved in developing attack surface management tools and strategies between 2025 and 2030 include specialized cybersecurity firms like Palo Alto Networks, CrowdStrike, and RiskIQ, as well as large cloud providers such as Microsoft, AWS, and Google, which integrate these capabilities into their security platforms.
However, despite these advancements, a recent Ponemon Institute study revealed that only 36% of organizations are confident their TPRM programs can effectively mitigate third-party risks in real time. Bitsight's Cyber Risk Intelligence Global Survey found that only 1 in 3 enterprises continuously monitor all of their third-party relationships for risk exposure. This underscores the need for continued investment and improvement in third-party risk management strategies.
Threat intelligence provides the "so what" behind raw data, transforming a list of misconfigurations and CVEs into a prioritized set of risks aligned to actual threat activity. It is this prioritized, actionable intelligence that will drive the success of third-party risk management in the future.
In February 2024, a ransomware attack on a critical US healthcare infrastructure caused nationwide operational disruptions in hospitals and medical offices. This incident serves as a stark reminder of the importance of robust third-party risk management strategies in the face of increasingly sophisticated cyber threats.
A network and shared platform enables companies to create once and share with many, reducing friction in the assessment process and headaches for those managing it. AI, coupled with threat intelligence, is the key to unlocking this networked approach to risk management, empowering security teams to navigate the complexities of the modern threat landscape with confidence and precision.
