As organizations accelerate the adoption of Artificial Intelligence, from deploying Large Language Models (LLMs) to integrating autonomous agents and Model Context Protocol (MCP) servers, risk management has transitioned from a theoretical exercise to a critical business imperative. The NIST AI Risk Management Framework (AI RMF 1.0) has emerged as the standard for managing these risks, offering a structured approach to designing, developing, and deploying trustworthy AI systems.

However, AI systems do not operate in isolation. They rely heavily on Application Programming Interfaces (APIs) to ingest training data, serve model inferences, and facilitate communication between agents and servers. Consequently, the API attack surface effectively becomes the AI attack surface. Securing these API pathways is fundamental to achieving the “Secure and Resilient” and “Privacy-Enhanced” characteristics mandated by the framework.

Understanding the NIST AI RMF Core

The NIST AI RMF is organized around four core functions that provide a structure for managing risk throughout the AI lifecycle:

• GOVERN: Cultivates a culture of risk management and outlines processes, documents, and organizational schemes.
• MAP: Establishes context to frame risks, identifying interdependencies and visibility gaps.
• MEASURE: Employs tools and methodologies to analyze, assess, and monitor AI risk and related impacts.
• MANAGE: Prioritizes and acts upon risks, allocating resources to respond to and recover from incidents.

The Critical Role of API Posture Governance

While the “GOVERN” function in the NIST framework focuses on organizational culture and policies, API Posture Governance serves as the technical enforcement mechanism for these policies in operational environments.

Without robust API posture governance, organizations struggle to effectively Manage or Govern their AI risks. Unvetted AI models may be deployed via shadow APIs, and sensitive training data can be exposed through misconfigurations. Automating posture governance ensures that every API connected to an AI system adheres to security standards, preventing the deployment of insecure models and ensuring your AI infrastructure remains compliant by design.

How Salt Security Safeguards AI Systems

Salt Security provides a tailored solution that aligns directly with the NIST AI RMF. By securing the API layer (Agentic AI Action Layer), Salt Security helps organizations maintain the integrity of their AI systems and safeguard sensitive data. The key features, along with their direct correlations to NIST AI RMF functions, include:

Automated API Discovery:

• Alignment: Supports the MAP function by establishing context and recognizing risk visibility gaps.
• Outcome: Guarantees a complete inventory of all APIs, including shadow APIs used for AI training or inference, ensuring no part of the AI ecosystem is unmanaged.

Posture Governance:

• Alignment: Operationalizes the GOVERN and MANAGE functions by enabling organizational risk culture and prioritizing risk treatment.
• Outcome: Preserves secure APIs throughout their lifecycle, enforcing policies that prevent the deployment of insecure models and ensuring ongoing compliance with NIST standards.

AI-Driven Threat Detection:

• Alignment: Meets the Secure & Resilient trustworthiness characteristic by defending against adversarial misuse and exfiltration attacks.
• Outcome: Actively identifies and blocks sophisticated threats like model extraction, data poisoning, and prompt injection attacks in real-time.

Sensitive Data Visibility:

• Alignment: Supports the Privacy-Enhanced characteristic by safeguarding data confidentiality and limiting observation.
• Outcome: Oversees data flow through APIs to protect PII and sensitive training data, ensuring data minimization and privacy compliance.

Vulnerability Assessment:

• Alignment: Assists in the MEASURE function by assessing system trustworthiness and testing for failure modes.
• Outcome: Identifies logic flaws and misconfigurations in AI-connected APIs before they can be exploited by adversaries.

Conclusion

Trustworthy AI requires secure APIs. By implementing API Posture Governance and comprehensive security controls, organizations can confidently adopt the NIST AI RMF and innovate safely. Salt Security provides the visibility and protection needed to secure the critical infrastructure powering your AI. For a more in-depth understanding of API security compliance across multiple regulations, please refer to our comprehensive API Compliance Whitepaper.

If you want to learn more about Salt and how we can help you, please contact us, schedule a demo, or visit our website. You can also get a free API Attack Surface Assessment from Salt Security’s research team and learn what attackers already know.

*** This is a Security Bloggers Network syndicated blog from Salt Security blog authored by Eric Schwake. Read the original post at: https://salt.security/blog/securing-the-ai-frontier-how-api-posture-governance-enables-nist-ai-rmf-compliance