Webinar Description
Key Takeaways
- Addresses the security challenges of deploying autonomous AI agents beyond simple LLM chat interfaces
- Covers the four pillars of AI agent security: identity, governance, authorisation, and observability
- Explores workload identity standards including SPIFFE/SPIRE and token exchange protocols
- Examines fine-grained authorisation models such as AuthZEN, ABAC, ReBAC, and IBAC
- Designed for security architects, DevSecOps practitioners, platform engineers, and IT leaders in enterprise environments
Securing AI Agents in an Era of Autonomous Systems
As organisations transition from basic large language model integrations to sophisticated multi-agent ecosystems, the security frameworks designed for traditional API architectures are proving inadequate. This webinar, hosted by Gravitee, examines the emerging discipline of AI agent security, focusing on how enterprises can establish robust identity, delegation, and access control mechanisms for autonomous AI workloads. The session is particularly relevant for security and engineering teams grappling with the operational realities of deploying AI agents at scale whilst maintaining governance and accountability.
The timing reflects a broader industry inflection point. AI agents are no longer confined to experimental deployments; they are increasingly embedded in production workflows where they interact with sensitive systems, make decisions, and chain together actions across multiple services. This autonomy introduces security considerations that static credentials and perimeter-based controls were never designed to address.
About This Event
The webinar is led by Gravitee’s Director of Product Management and takes a technical, educational approach to AI agent security. Rather than focusing on theoretical risks, the session aims to provide practical frameworks that security and engineering teams can apply to their own deployments. The format is a live virtual presentation, allowing attendees to engage with the material in real time.
Gravitee, the hosting organisation, develops API management and security solutions, and the session draws on their work in extending these capabilities to AI agent environments. The content addresses both the conceptual foundations of agent security and the specific standards and protocols that enable implementation.
The Four Pillars of AI Agent Security
Central to the webinar’s framework is the concept of four interconnected security pillars: identity, governance, authorisation, and observability. Each addresses a distinct aspect of the challenge, but their effectiveness depends on how well they work together.
Identity establishes who or what is acting within a system. For AI agents, this extends beyond user authentication to encompass workload identity—the ability to verify that a specific agent instance is what it claims to be. The session explores how standards like SPIFFE (Secure Production Identity Framework for Everyone) and its reference implementation SPIRE provide cryptographically verifiable identities for workloads, including AI agents operating across distributed environments.
Governance addresses the policies and controls that determine what agents are permitted to do. This includes establishing boundaries around agent capabilities, defining acceptable toolchains, and ensuring that organisational policies are consistently enforced regardless of where agents operate.
Authorisation translates governance policies into enforceable access decisions. The webinar examines several authorisation models, including Attribute-Based Access Control (ABAC), Relationship-Based Access Control (ReBAC), and Identity-Based Access Control (IBAC). It also covers AuthZEN, an emerging standard for engine-agnostic authorisation that allows organisations to implement fine-grained access control without being locked into specific policy engines.
Observability provides the visibility necessary to understand what agents are actually doing. Without comprehensive logging and tracing, organisations cannot audit agent behaviour, investigate incidents, or demonstrate compliance. The session discusses how OpenTelemetry GenAI schemas can provide structured observability data specifically designed for AI workloads.
Delegation and Token Exchange in Agent Chains
One of the more complex challenges in AI agent security involves delegation—the process by which an agent acts on behalf of a user or another system. When agents chain together, calling other agents or services to complete tasks, the question of authority becomes critical. Which permissions should propagate through the chain? How can downstream services verify that an agent is legitimately acting on behalf of an authorised principal?
The webinar addresses these questions through the lens of token exchange, specifically RFC 8693, which defines a protocol for exchanging one security token for another. This mechanism allows agents to obtain appropriately scoped credentials for specific tasks without requiring overly broad permissions. When combined with workload identity from SPIFFE/SPIRE, token exchange enables a model where each agent in a chain can be independently verified and granted only the permissions necessary for its specific function.
This approach contrasts sharply with legacy patterns where agents might operate with static API keys or service account credentials that grant broad access regardless of the specific task being performed. Such patterns create significant risk when agents behave unexpectedly or are compromised.
Moving Beyond Legacy API Security
Traditional API security models assume a relatively predictable pattern of requests and responses, typically initiated by human users or well-understood automated processes. AI agents disrupt this model in several ways. They may generate novel request patterns, chain together multiple API calls in unexpected sequences, and make autonomous decisions about which tools and services to invoke.
The webinar argues that securing these environments requires what it terms an “agent-native” approach—security frameworks designed from the ground up for autonomous, dynamic workloads rather than adapted from human-centric or static automation models. This includes real-time policy enforcement that can evaluate context at the moment of each action, rather than relying solely on pre-established permissions.
The concept of Policy Enforcement Points (PEP) and Policy Decision Points (PDP) features prominently in this discussion. These architectural patterns, drawn from established access control frameworks, provide a separation between where policies are enforced and where decisions are made. This separation allows organisations to centralise policy logic whilst distributing enforcement across their infrastructure.
Addressing Shadow AI and Uncontrolled Agent Proliferation
A recurring concern in enterprise AI deployments is the emergence of unsanctioned agents—AI systems deployed outside official governance structures. These shadow AI implementations may lack proper security controls, use inappropriate data, or create compliance risks that organisations only discover after incidents occur.
The webinar discusses how unified AI catalogues can provide visibility into agent deployments across an organisation. By maintaining a centralised registry of authorised agents, their capabilities, and their access patterns, security teams can identify unauthorised deployments and ensure that all agents operate within established governance frameworks.
Who Should Attend
The session is designed for technical professionals responsible for securing AI deployments in enterprise environments. Security architects will find value in the framework for thinking about agent security holistically. DevSecOps practitioners can apply the specific standards and protocols discussed to their implementation work. Platform engineers responsible for the infrastructure supporting AI agents will benefit from the discussion of workload identity and policy enforcement architecture. API managers facing the challenge of extending their governance models to AI workloads will find relevant guidance on authorisation patterns.
The content assumes familiarity with enterprise security concepts and will be most valuable to organisations that are actively deploying AI agents or planning to do so in the near term. Those in regulated industries, where auditability and access control are particularly critical, may find the observability and governance discussions especially pertinent.
The Broader Context of AI Governance
The challenges addressed in this webinar reflect a broader maturation of enterprise AI adoption. Early implementations often prioritised capability over governance, resulting in deployments that worked but lacked the controls necessary for production use at scale. As AI agents take on more consequential tasks—accessing sensitive data, making decisions that affect business operations, and interacting with external systems—the need for robust security frameworks becomes unavoidable.
The standards and protocols discussed, from SPIFFE/SPIRE to AuthZEN to OpenTelemetry, represent the industry’s efforts to establish common foundations for AI security. Organisations that invest in understanding these frameworks now will be better positioned to deploy AI agents confidently as the technology continues to evolve.