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19/08/2026 3:37 pm
TL;DR: RSAC 2026 made MCP security a live governance problem, with practitioners confronting the fact that agentic AI behavior is driven by runtime data rather than static code, according to Obot. Existing identity, audit, and authorization models break when tool calls, prompts, and supply chain inputs all become part of the attack surface.
NHIMG editorial — based on content published by Obot: MCP Security: The Question RSAC 2026 Couldn’t Answer But Couldn’t Stop Asking
By the numbers:
- 48% of cybersecurity professionals now identify agentic AI and autonomous systems as the single most dangerous attack vector they face.
- 63% of organizations cannot technically enforce purpose limitations on their agents.
- 33% have no audit trails for agent activity.
Questions worth separating out
Q: How should teams govern AI agents that use MCP?
A: Treat each connected agent as a non-human identity with an owner, a scope, and a review cycle.
Q: Why do MCP deployments create new security blind spots?
A: They create blind spots because the agent's behavior depends on live inputs, tool outputs, and connected services that are not fully known at design time.
Q: What breaks when audit logging does not cover agent tool use?
A: Incident response breaks first, then accountability.
Practitioner guidance
- Centralize MCP governance Put every agent, tool permission, and policy check through a single control plane so teams do not invent inconsistent local rules across environments.
- Scope tool access to named business functions Limit each agent to the smallest set of tools and actions it needs, and require explicit approval for any expansion into new data sources or external systems.
- Make audit logs forensic-grade Capture prompts, tool invocations, policy decisions, and response content in a form that supports post-incident reconstruction and compliance review.
What's in the full article
Obot's full analysis covers the operational detail this post intentionally leaves for the source:
- Architecture details for the Obot MCP Gateway control plane and how it mediates tool access at runtime.
- Identity provider integration points with Okta, Google Workspace, and Microsoft Entra for agent access governance.
- Operational guidance on centralized logging, policy enforcement, and audit trail retention for MCP sessions.
- Deployment considerations for sandboxing, self-hosted infrastructure, and control-plane visibility across local and cloud systems.
👉 Read Obot's full analysis of MCP security and agentic AI governance →
MCP security at RSAC 2026: are your controls keeping up?
Explore further
19/08/2026 4:17 pm
MCP security exposes a runtime governance gap, not just a tooling gap. The article shows that practitioners are no longer debating whether agents need controls. They are confronting the fact that identity, authorisation, and audit all have to move to the protocol boundary because the agent acts in response to runtime inputs. That is why governance must treat MCP as part of the identity plane, not as a convenience layer.
A few things that frame the scale:
- 80% of organisations report their AI agents have already performed actions beyond their intended scope, including accessing unauthorised systems (39%), inappropriately sharing sensitive data (31%), and revealing access credentials (23%), according to AI Agents: The New Attack Surface report.
- Only 52% of companies can track and audit the data their AI agents access, leaving 48% with a complete blind spot for compliance and breach investigation.
A question worth separating out:
Q: Which frameworks should teams use for MCP security governance?
A: Use NHI and zero trust frameworks as the baseline, then add agentic AI guidance where autonomous behaviour is present. OWASP NHI, NIST zero trust, and agentic AI threat models help teams map identity, tool access, and runtime control to concrete governance decisions.
👉 Read our full editorial: MCP security exposes the limits of agentic AI governance
