What is AI TriSM?
AI Trust, Risk and Security Management (AI TRiSM) is Gartner's comprehensive framework that ensures AI model, application and agent governance, trustworthiness, reliability, and security. The framework addresses the critical need for organizations to proactively manage AI-related risks while maintaining operational effectiveness.
five Key Principles of AI TRisM for agentic ai identities:
Without AI TRiSM, organizations risk deploying AI systems that are opaque, non-compliant, and vulnerable to manipulation or misuse.
By implementing the AI TRiSM framework, organizations can build trust in their AI systems, mitigate potential risks, and ensure security and privacy for both themselves and their customers. CISOs should champion AI TRiSM adoption in parallel to enabling Agentic AI deployments.
The Foundation for Trustworthy Agentic AI
Identity security serves as the cornerstone of AI TRiSM implementation.
Without secure, properly managed identities accessing AI systems, organizations cannot achieve the trust, risk management, and security objectives that AI TRiSM framework demands.
Anetac helps organizations align with AI TRiSM by addressing core identity risks associated with AI agents. As AI becomes increasingly autonomous, understanding and controlling the access of these agents is essential to securing operations.
Key Insight: With 85% of breaches involving compromised identities, and the exponential growth of AI agents and non-human identities, traditional security approaches fail to address
the complex identity landscape in
AI-driven environments.
Anetac IdVM operationalizes governance, trust and accountability
Implementation Roadmap:
Integrating Anetac IdVM with AI TRiSM
1.
Assessment and Discovery
Deploy Anetac's discovery capabilities to catalog all existing identities across your ecosystem, with a focus on non-human identities. Establish baseline security posture and identify immediate vulnerabilities in Service Accounts and Agentic AI.
2.
AI TRiSM Framework Mapping
Map your AI systems and data flows to the four AI TRiSM layers. Identify where identity controls are needed and establish governance policies for AI system access and operations. Establish Anetac as the System of Record for Agentic AI Access Chains.
3.
Policy Development and Integration
Develop identity governance policies specific to AI systems, building on the existing non-human identities. Integrate Anetac's monitoring capabilities with your AI TRiSM governance layer and existing security tools for enforcement within control planes.
4.
Monitor, Remediate and Respond
Enable real-time monitoring and automated response capabilities for AI system identities and actively reduce your attack surface. Implement behavioral analytics and anomaly detection for Agentic AI and non-human identities (e.g., service accounts).
5.
Assessment and Discovery
Deploy Anetac's discovery capabilities to catalog all existing identities across your ecosystem, with a focus on non-human identities. Establish baseline security posture and identify immediate vulnerabilities in Service Accounts and Agentic AI.
Why Anetac IdVM is essential for AI TRiSM success
As organizations deploy more AI agents, the identity attack surface exponentially expands. Traditional IAM solutions cannot handle the scale and complexity of
AI-driven identity ecosystems.
Emerging AI regulations require demonstrable security controls. Identity vulnerability management provides auditable evidence of Agentic AI
security and compliance.
Identity-based attacks on AI systems can halt business operations. Proactive identity security ensures AI system availability
and business continuity.
Organizations with robust AI TRiSM implementations, including identity security, can deploy AI systems faster and with greater confidence than competitors.
Password Neglect - Service account passwords are often hard coded, easily discoverable, can be non-complex, and rarely changed. Changing them without understanding the internal dependency landscape risks impact on critical applications.
Dormant or Unknown Service Accounts - Service accounts without visibility, proper account management and configuration, can lead to increased attack surface risk.
NTLM - Migrating from NTLM requires visibility of the service account landscape in order to map usage and dependencies on AD accounts before remediating them.
Shared-use Service Accounts - Security hygiene is negatively impacted and opens up risk when human accounts are being used in scripts and behaving like non-human service accounts.
Service Account Sprawl - Organizations generate high volumes of service accounts which are difficult to identify, configure, and monitor creating a highly vulnerable internal attack surface.
Lateral Movement - Threat actors frequently employ lateral movement tactics during cyberattacks and compromised service accounts are a way for cyber criminals to move undetected across an organization’s environment.
High Privileges - Service accounts, especially privileged ones, often hold admin-level access to sensitive data and systems, making them tempting attack targets.
Incident Response - The effort to quickly identify affected service accounts and analyze logs after an active directory attack can take days and tie up valuable resources.
Compliance Risks - To mitigate compliance risks with regulations and standards such as HIPAA, PCI DSS, SOX, and GDPR, organizations must establish policies and procedures for managing service accounts which are often manual activity and usage reviews which are labor intensive, costly, and immediately outdated
Blast Radius - Poor visibility into service accounts creates issues identifying the actual impact radius of anomalous and suspicious human and nonhuman account behavior.
Anetac helps uncover blind spots with dynamic visualization of service account chains.
