AI security certification has become a critical requirement for organizations assessing the risk posture of AI-enabled vendors, especially as AI becomes deeply embedded in sensitive and regulated business processes. For third-party risk management (TPRM) teams, the question is no longer whether vendors use AI, but whether those AI systems are secure, governed, and independently validated against recognized security standards.

As AI adoption accelerates across industries, traditional vendor risk assessments are struggling to keep pace. Questionnaires and attestations alone cannot adequately address the unique risks introduced by AI models, training data, and automated decision-making. This is where AI security certification plays a pivotal role, providing structured, testable assurance that AI systems meet defined security and risk management expectations.

Why AI security certification is critical today

The rise of AI in sensitive and regulated environments

Third-party vendors increasingly rely on AI to process protected health information (PHI), financial data, intellectual property, and other sensitive assets. From clinical decision support tools to fraud detection engines, AI systems now sit directly in the flow of regulated data.

For organizations managing third-party risk, this creates a new exposure layer. A vendor’s AI model may introduce risks that extend far beyond traditional infrastructure or application security, making AI security assessment an essential component of modern vendor due diligence.

Security challenges unique to AI systems

AI systems present distinct security challenges that are often overlooked in standard risk assessments. These include risks related to training data integrity, model drift, prompt injection, adversarial attacks, and unintended data leakage through model outputs. Vendors may also struggle to demonstrate consistent governance over how AI systems are developed, deployed, and monitored over time.

Without a recognized AI assurance framework, organizations are left to interpret vendor claims without objective validation, an approach that increases uncertainty and risk.

The cost of uncertified AI deployment

Uncertified AI deployments can expose organizations to regulatory scrutiny, operational disruptions, reputational damage, and downstream third-party failures. For TPRM leaders, the absence of AI security certification complicates vendor onboarding, slows procurement, and increases residual risk across the supply chain.

Independent assessment helps reduce these challenges by offering a standardized, repeatable way to evaluate AI security controls at scale.

What is AI security certification?

Defining AI assurance through a security lens

AI security certification is a formal, independent proof of evaluation of an AI system’s security, governance, and risk management controls. Unlike high-level ethical AI principles or self-attested compliance checklists, certification focuses on whether AI systems are implemented and operated securely in real-world environments.

For third-party risk teams, AI security certification serves as objective evidence that a vendor’s AI system has been assessed against defined security requirements.

Key components of a certifiable AI security program

A certifiable AI security program typically includes controls for data protection, secure model development, access management, monitoring, incident response, and governance oversight. It also requires documented policies, repeatable processes, and demonstrable implementation — elements that are critical for scalable vendor risk management.

HITRUST brings these components together through a structured, security-first approach to AI assurance.

How certification helps mitigate AI risks

Addressing data integrity and model vulnerabilities

AI security assessment helps organizations validate that vendors have safeguards in place to protect training data, prevent unauthorized model access, and detect tampering or degradation over time. This is particularly important when vendors rely on large datasets sourced from multiple environments.

TPRM teams gain confidence through certification that AI systems are not only functional but resilient against integrity and availability risks.

Preventing adversarial exploits and bias

Adversarial attacks, model manipulation, and unintended bias pose significant risks to organizations relying on third-party AI. Certification frameworks designed for AI security evaluate whether vendors have controls to identify, mitigate, and respond to these threats.

By requiring certified assurance, organizations can reduce the likelihood that vendor AI systems introduce compliance, ethical, or operational failures into their ecosystems.

HITRUST’s role in AI security certification

Overview of the HITRUST AI Security Assessment

The HITRUST AI Security Assessment and Certification was designed to solve a specific and increasingly urgent problem for organizations and third-party risk management teams: proving that deployed AI systems are secure.

Rather than focusing on high-level governance maturity or policy intent, HITRUST evaluates AI-specific security risks in real, operational environments. The assessment applies prescriptive, threat-mapped controls tailored to how and where AI is deployed, ensuring that security requirements align directly to practical risk scenarios.

Independent testing, centralized quality assurance, and formal HITRUST certification together deliver defensible, evidence-based AI security assurance that TPRM teams can rely on across vendor ecosystems.

How HITRUST aligns with global AI security standards

HITRUST’s AI security assessment aligns with and maps to leading global standards and guidance, including NIST publications, ISO/IEC standards, and OWASP resources. However, HITRUST differs materially from governance-first approaches such as ISO/IEC 42001. HITRUST provides prescriptive security requirements and standardized assurance outcomes.

Use cases: HITRUST in healthcare, finance, and beyond

Developed through extensive industry collaboration, HITRUST AI Security Certification enables scalable trust across regulated industries where AI risk is embedded in third-party products and services. The assessment includes 44 harmonized, AI-specific security controls with explicit mappings between threats and required safeguards, and it is regularly updated to address emerging AI risks.

In healthcare, HITRUST-certified AI systems support the protection of PHI and regulatory compliance. In financial services, they help organizations validate the security of AI-driven analytics, automation, and fraud detection. Across industries, standardized reporting supports executives, regulators, and TPRM teams alike.

By certifying systems and environments, HITRUST delivers clear proof that AI systems are protected, enabling organizations to make confident, defensible third-party risk decisions at scale.

Steps to achieve AI security certification

Conducting a readiness assessment

Vendors typically begin by evaluating their AI systems against HITRUST requirements to identify gaps. Additional insights on building trust in AI highlight how structured assurance accelerates confidence across stakeholders.

Working with HITRUST external assessors

Certification requires validation by an authorized HITRUST Assessor, ensuring independence and consistency. This third-party validation is a key differentiator for risk teams seeking defensible assurance outcomes.

Organizations exploring broader assurance options can also review HITRUST’s full portfolio of assessments and certifications to support holistic risk management strategies.

Maintaining certification through continuous monitoring

AI risk does not remain static. HITRUST emphasizes ongoing monitoring and reassessment to ensure certified AI systems continue to meet security expectations as models evolve and threats change. This approach supports efficient AI risk management across the vendor lifecycle.

Future-proofing AI with HITRUST

Building a culture of certified AI innovation

For organizations managing third-party risk, AI security assessment is foundational to maintaining trust, resilience, and compliance in an AI-driven ecosystem. By leveraging HITRUST’s structured, scalable pathways, organizations can gain defensible, repeatable AI assurance.

Secure AI systems with confidence and explore HITRUST’s proven path to AI security certification and risk reduction.

Ransomware has evolved from an opportunistic cybercrime into one of the most persistent and damaging threats facing organizations today. According to a recent report, the number of ransomware victims increased by 53%-63% over the past two years. As attacks grow in scale, sophistication, and impact, organizations need more than isolated controls or point-in-time assessments. They need defensible, measurable ransomware resilience.

To address this challenge, HITRUST has expanded its Insights Reports portfolio with a dedicated Ransomware Insights Report, aligning HITRUST assessment results to the NIST Cybersecurity Framework v2.0 and the NIST Ransomware Community Profile. This report delivers actionable insight into ransomware readiness using a trusted, validated assurance model.

What are HITRUST Insights Reports?

HITRUST Insights Reports transform existing HITRUST assessment results into mapped, audit-ready reports aligned with leading frameworks and regulatory expectations. Rather than treating compliance and risk reporting as duplicative efforts, Insights Reports allow organizations to extend the value of a single HITRUST assessment across multiple use cases.

These are reporting outcomes of the HITRUST assurance program, designed to help organizations communicate trust, maturity, and alignment more effectively.

Why focus on ransomware resilience now?

Ransomware continues to dominate the global threat landscape, cutting across industries and organizational sizes.

• According to Verizon’s 2025 Data Breach Investigations Report, ransomware was present in 44% of all analyzed data breaches, highlighting how frequently attackers rely on ransomware as a primary attack method.
• Small and mid-sized organizations (SMBs) were disproportionately impacted, with ransomware involved in 88% of breaches affecting SMBs.

The continued prevalence of ransomware across nearly half of all breaches demonstrates that it is no longer a niche or episodic threat, but a core attack technique used by threat actors across industries.

These figures underscore a critical reality: ransomware is not only increasing in frequency, but it is increasingly targeting organizations with fewer resources and lower tolerance for operational disruption, making ransomware resilience and preparedness essential components of modern cybersecurity and risk management programs.

What is the HITRUST Ransomware Insights Report?

The HITRUST Ransomware Insights Report maps validated HITRUST CSF assessment results to the subset of NIST Cybersecurity Framework v2.0 core subcategories prioritized in the Ransomware Community Profile, which outlines cybersecurity outcomes specifically designed to reduce the likelihood and impact of ransomware attacks.

The report provides

• Mapped control alignment between HITRUST CSF requirements and NIST ransomware-related subcategories
• Control maturity evaluations, offering insight into the organization’s ability to counter ransomware threats and deal with the potential consequences of events
• Certified, audit-ready reporting, validated through HITRUST’s quality and assurance processes

This enables organizations to view ransomware resilience through a NIST-aligned lens, without conducting separate assessments or duplicative analyses.

How does HITRUST align with the NIST Ransomware Community Profile?

The NIST Cybersecurity Framework complements existing risk management and cybersecurity programs by providing a consistent structure for identifying, managing, and communicating cybersecurity risk. The Ransomware Community Profile, detailed in NIST IR 8374, builds on this foundation by emphasizing ransomware-specific resilience outcomes.

HITRUST maps its CSF requirements to NIST CSF v2.0 using the NIST OLIR methodology, ensuring traceability, consistency, and rigor. These mappings undergo a multi-stage internal review process, including automated checks, peer review, management review, and quality assurance validation.

The result is a defensible, transparent mapping that organizations can confidently use to demonstrate ransomware readiness to internal and external stakeholders.

What insights does the report deliver?

The Ransomware Insights Report delivers structured, outcome-driven insight into how well an organization is positioned to prevent, withstand, and recover from ransomware events.

At the core of the report is a ransomware scorecard that presents control maturity across prioritized NIST CSF domains, including Govern, Identify, Protect, Detect, Respond, and Recover. These maturity scores reflect the results of independent validation performed during a validated assessment and show how effectively ransomware-related security objectives are implemented and operating in practice.

For example, with the Govern function, the report highlights foundational capabilities that directly influence ransomware resilience, such as

• Organizational context and risk awareness, which ensure ransomware preparedness is aligned to mission-critical services, stakeholder expectations, and regulatory obligations
• Defined roles, responsibilities, and authorities, enabling coordinated and timely action during ransomware incidents
• Risk management integration, ensuring ransomware risk is embedded into enterprise risk management and decision-making processes

The report enables organizations to quickly identify strengths, gaps, and areas for improvement. If control maturity falls below fully compliant, the report provides clear, relevant observations and corrective action considerations, supporting transparent risk discussions and remediation planning.

Ultimately, the insights delivered move beyond checkbox compliance. They provide leadership, risk owners, and security teams with a defensible view of ransomware readiness that can be used to communicate posture, prioritize investments, and demonstrate alignment with recognized ransomware resilience standards.

How can organizations use the Ransomware Insights Report?

Organizations can apply the report across multiple use cases, including

• Board and executive reporting to clearly communicate ransomware readiness
• Third-party and vendor risk management, especially where ransomware exposure is a top concern
• Regulatory and audit support, leveraging NIST-aligned evidence
• Security program improvement, identifying gaps and prioritizing ransomware-related remediation

For organizations already using HITRUST, the report provides a new way to operationalize existing assessment results without added assessment burden.

Conclusion

Ransomware is no longer an isolated risk. It is a defining cybersecurity challenge. Organizations must be able to measure, demonstrate, and improve resilience. The HITRUST Ransomware Insights Report delivers a practical, trusted mechanism to translate complex control environments into meaningful, ransomware-focused insight.

In a landscape where ransomware attacks are increasingly inevitable, measured resilience is what separates disruption from recovery.

AI security risk is escalating faster than organizations can measure it. AI governance frameworks such as ISO/IEC 42001 establish oversight and accountability, but they do not evaluate the security of AI systems. As AI becomes embedded in products, services, and vendor ecosystems, validated AI security assurance offers a stronger, more practical way to measure and reduce real AI risk, where governance alone falls short.

What is the difference between AI governance and AI security?

AI governance defines how AI is managed within an organization. It focuses on policies, decision-making structures, roles, and oversight intended to ensure responsible and compliant AI use.

AI security focuses on how AI systems are protected. It examines whether controls are implemented in deployed systems, whether they are tested, and whether they actually work.

Governance sets expectations. Security assurance validates reality.

Why AI security risk remains largely invisible in TPRM

AI is being deployed at a pace that outstrips traditional risk management models. Vendors are introducing AI capabilities continuously, often without clear visibility into how those systems are secured or monitored.

Most third-party risk programs still rely on indirect signals such as questionnaires and attestations to assess vendor security.

With AI, this approach breaks down. Risk teams are left to infer security posture from narrative evidence, while the actual AI systems remain untested. Because AI security controls are selectively tested and rarely validated, organizations often do not know what protections are actually in place until an incident occurs. This creates a false sense of control, where risk appears managed on paper but remains unmeasured in practice.

Why governance frameworks cannot reduce AI security risk

Governance frameworks are designed to manage behavior, not validate technical outcomes.

They do not

• Prescriptively define AI security controls
• Require testing of deployed AI environments
• Validate control effectiveness through independent assessment
• Provide standardized, comparable evidence of AI security

For instance, ISO/IEC 42001 is a governance framework designed to help organizations establish an AI Management System (AIMS). It provides structure around accountability, documentation, and continuous improvement for AI activities. However, ISO/IEC 42001 does not deeply assess the security of AI systems that are deployed and in use. Controls may be selectively implemented and selectively tested by accredited as well as unaccredited certification bodies, resulting in inconsistent assurance strength.

How AI security assurance delivers stronger risk reduction

AI security assurance focuses on measurable outcomes.

Rather than evaluating intent, it validates whether security controls are implemented, tested, and effective in real AI systems. This provides clear evidence that AI-related threats are being addressed.

Unlike management system audits, effective AI security assurance requires that all applicable controls be tested, using consistent methods and rigor through authorized assessors, so results can be relied upon by regulators, customers, and third-party risk teams.

The HITRUST AI Security Assessment and Certification was built specifically to deliver this level of assurance.

How HITRUST AI compares to ISO/IEC 42001

For a detailed comparison between HITRUST AI Security Assessment and Certification and ISO/IEC 42001, read our recent blog post.

Why HITRUST offers what governance frameworks cannot

HITRUST is the only reliable solution built for AI security assurance. HITRUST AI Security Certification provides organizations with something governance frameworks are not designed to deliver: trusted proof of AI system security.

It is

• Fast, enabling timely response to emerging AI threats
• Focused, targeting real AI security risks in deployed systems
• Affordable, allowing assurance to scale across vendors and internal environments

This makes AI security assurance practical, actionable, and repeatable.

HITRUST also delivers consistent assurance through vetted assessors, prescriptive, threat-driven testing requirements, and centralized quality assurance, reducing the variability and interpretation risk common in governance-based certifications.

What this means for organizations managing AI risk

AI governance establishes expectations. AI security assurance establishes trust.

As AI continues to permeate vendor ecosystems, organizations cannot rely on oversight alone. They must be able to measure security directly and act on verified results.

The organizations that move first will not just respond to AI risk — they will control it.