Unlocking Smarter IoT Risk Mitigation Using a Maturity Model Framework

As cyber threats targeting Internet of Things (IoT) devices continue to increase, organizations struggle to mitigate risk. Most companies try to adapt traditional vulnerability management processes to their IoT fleets. However, as they scale their fleets, these processes become time-consuming and potentially error-prone. For a company that manages hundreds or thousands of IoT devices, vulnerability management without risk prioritization leads to reactive measures that come with security gaps. 

As organizations increasingly bring their IoT devices under the umbrella of larger security programs, they need to create a strategy for managing the unique risks that their fleets create. IoT devices are just as vulnerable and prevalent as IT (servers, workstations, etc.) without the computer/storage/memory to defend themselves well. Still, ample protection is required. A risk prioritization maturity model allows organizations to take a crawl, walk, run approach to integrating IoT security into their broader strategies.

By leveraging a risk prioritization maturity model, organizations can focus on the IoT devices that pose the greatest operational and security risks for more effective and efficient vulnerability management. 

What Is a Risk Prioritization Maturity Model?

A risk prioritization maturity model is a strategic vulnerability management framework that guides organizations in assessing, improving, and maturing their remediation and patch management processes. From a vulnerability risk mitigation standpoint, the key components of this model include:

• Safely gathering a rich, reliable inventory of IoT devices and their activity
• Vulnerability scanning to identify new vulnerabilities and map them to potentially risky IoT devices.
• Asset analysis that incorporates context around IoT devices and the existing network controls that mitigate risk
• Patch management that uses automation to address the riskiest vulnerabilities
• Remediation steps that include applying security patches and any compensating controls, like limiting device functionalities or services
• Metrics that show trends over time to support the vulnerability management program’s success

At a high level, the maturity model stages typically look like this:

• Level 1: Reactive processes that incorporate basic vulnerability scanning and patching practices. 
• Level 2: Formal risk-informed policies and procedures that move toward a targeted approach to applying security updates. 
•  Level 3: Risk-based, quantitatively managed programs that incorporate threat intelligence and automation. 

Level 1: Vulnerability Scanning and Publicly Available Risk Information

In the early stages of risk management maturity, most organizations engage in ad hoc vulnerability scanning characterized by disconnected processes and minimal data analysis. Security, vulnerability management, patch management, and IT teams often struggle to collaborate effectively, resulting in inefficiencies and communication issues. 

Identification of Known Vulnerabilities

At this stage, organizations likely use the same technologies for their IoT fleets as their enterprise IT devices, like laptops. Unfortunately, these active scanners can take IoT devices offline, leading to outages that generate additional operational issues. 

Taking the Next Step

When seeking to mature their risk management processes, organizations should consider implementing solutions that:

• Identify all IoT devices connected to networks (public or private) for visibility into the fleet.
• Identify IoT vulnerabilities without disrupting availability, like passive scanning solutions.
• Incorporate IoT manufacturer data to improve identification of known firmware vulnerabilities. 

Using General Risk Data

At this stage, many organizations still rely on publicly available information, like the Common Vulnerability Scoring System (CVSS) or Exploit Prediction Scoring System (EPSS). However, these both fail to respond to IoT device security issues in different ways:

• CVSS: vulnerability severity without insight into real-world attacks leveraging the vulnerability. 
• EPSS: current trends around attackers using the vulnerability without insight into configurations or other environment-specific context.

Taking the Next Step

When seeking to mature their risk management processes, organizations should consider implementing solutions that incorporate current risk mitigations like:

• Device hardening
• Exploit nullification – Via segmentation, device changes, network changes, or patches
• IoT attacks in the real world

Level 2: Risk Informed

By implementing a solution focused on the unique risks that IoT devices create, the organization has matured its risk management strategy to the next level. At this point, it can consider itself risk-informed, enabling it to prioritize vulnerabilities based on assessed risk rather than treating them all equally. However, the organization may still rely on manual processes and spreadsheets, leaving it in a reactive state. 

Static Risk Visibility

A risk-informed vulnerability management program considers point-in-time data about operational impact. At this maturity level, organizations begin assessing the risk that different vulnerabilities pose to operations and sensitive data. However, they have little insight into real-time risk monitoring. 

Taking the Next Step

When seeking to mature their risk management processes, organizations should consider implementing solutions that incorporate:

• Information about devices from different manufacturers and with different operating systems that can contain vulnerabilities. 
• Device communication protocols or standards for insight into potential weaknesses. 
• Manufacturer firmware and software updates to gain insight into whether security patches have been published. 

Manual Risk Review

Additionally, static visibility typically assesses risks informally, relying heavily on manual risk review methods. At this level, the organization may use traditional approaches, like spreadsheets, for vulnerability documentation and remediation tracking. While effective initially, these time-consuming, error-prone processes mean that the organization struggles to scale its IoT vulnerability risk mitigation strategy, especially as it adds new devices to its fleets. 

Taking the Next Step

When seeking to mature their risk management processes, organizations should consider implementing solutions that incorporate automated risk analysis with data gathered from:

• Software Bills of Materials (SBOMs).
• IoT-focused threat intelligence. 
• Current network architecture. 

Limited Prioritization

The risk-informed practices enable organizations to start prioritizing their remediation activities. However, these prioritization methods remain reactive, focusing on the individual vulnerabilities rather than the broader attack surface. Further, while prioritization is a step in the right direction, these organizations may still have inconsistent processes and struggle with cross-functional collaboration. 

Taking the Next Step

When seeking to mature their risk management processes, organizations should consider implementing solutions that:

• Automate the risk analysis process.
• Provide risk analytics for targeted remediation. 
• Suggest the remediation activities beyond applying patches. 
• Provide a single source of IoT vulnerability information to all internal stakeholders.

Level 3: Risk-Based Dynamic Assessment and Prioritization

At this level, organizations have a fully mature risk prioritization process. They have IoT device vulnerability scanning and testing integrated into their overall security program. Using a comprehensive and dynamic risk-based vulnerability prioritization process, they align their business operations with their security strategies. 

Various Risk Factors

Organizations that achieve mature risk prioritization practices have enhanced governance arising from consistent, repeatable processes and automation that enable them to prioritize vulnerability management and patch remediation activities. At this level, organizations have implemented risk analysis processes that incorporate:

• Comprehensive identification of all IoT devices.
• Manufacturer-supplied data about devices. 
• Data from open-source software repositories.
• Threat intelligence about attacker activity. 
• Insights into attacker tactics, techniques, and procedures, like those outlined in the MITRE ATT&CK Framework

Targeted Segmentation

With targeted segmentation, organizations group IoT devices based on shared exploit vectors. This network segmentation technique enables the internal teams to improve their IoT monitoring by focusing on device type and configuration risk profile. At this level, organizations streamline their IoT vulnerability and security risk management processes by:

• Accurately classifying and categorizing devices
• Enabling full customization about how to group devices, like according to department or criticality
• Using MITRE terminology for vulnerability descriptions 
• Creating Access Control Lists (ACLs) based on their environment to aid in zero-trust efforts and simplify your network security processes

Prioritization with Context

The organization’s risk prioritization includes correlation, contextualization, and comprehensive vulnerability risk assessments. The process evaluates the potential impact and likelihood of attacks, enabling the security, vulnerability, and patch management teams to prioritize their remediation activities based on potential exploitability, business risk, and the security classification. At this level, the organizations can:

• Track devices as they move across the network for visibility into physical location. 
• Accurate device classification and vulnerability identification. 
• Filter out irrelevant vulnerabilities. 
• Integrate IoT vulnerability risk into security and IT service management solutions.

Vulnerability Remediation Automation

By adopting IoT-focused automation solutions, organizations create consistent, repeatable processes for patch deployment and vulnerability life cycle tracking. These automated solutions reduce mean time to remediation, ensuring that cross-functional teams proactively manage and address threats early. At this level, organizations have implemented:

• Automated patch management processes.
• Scheduled patching to reduce service disruptions. 
• Bulk patching to reduce the time spent on patching. 

Asimily: The IoT Risk Prioritization Solution for Mature Risk Management

Asimily’s purpose-built IoT management platform provides visibility into and control over device fleets’ operations and cybersecurity. With a centralized location for managing the IoT patching process, organizations can improve their overarching security posture by identifying vulnerabilities and installing patches faster. Every patch means a potential incursion has been prevented.

With Asimily’s IoT Management module and its patching function, security and IT teams can more effectively and efficiently update IoT devices while reducing the operational risks and costs arising from the process. With a centralized location for managing these processes, organizations can monitor for new firmware fixes and then either trigger automatic updates or schedule patch deployments, depending on the risk the vulnerability poses and the impact that service downtime will have. 

To learn more about Asimily and the IoT patch management functionality, reach out now to book a demo.