APAC Enterprises Adopt Agentic AI with Identity First Security and Guardrails

APAC enterprises are accelerating AI adoption while confronting a new security reality: agentic AI — autonomous software agents that act, decide, and access systems without constant human supervision — is expanding attack surfaces and exposing identity, credential, and data-exfiltration risks faster than many organizations can adapt. Microsoft, Keeper Security, Sophos and Check Point each announced product integrations and governance tools at and around Microsoft Ignite designed to treat agents as first-class identities, enforce runtime guardrails, and make threat intelligence consumable inside Copilot-driven workflows — moves that acknowledge agent sprawl, but also raise operational, governance and supply-chain questions organizations must resolve before wide-scale deployment.

Background​

What is “agentic AI” and why it matters now​

Agentic AI refers to systems that perform multi‑step tasks autonomously: they can retrieve data, call services, act on behalf of users, and make sequential decisions across applications. Analysts and vendors project rapid growth in agent deployment inside enterprises as agents are embedded into productivity suites, workflows and infrastructure orchestration. Microsoft has positioned Agent 365, Foundry Control Plane and Entra Agent ID as control-plane components intended to register, govern and observe these agents across the enterprise stack. The risk calculus is simple but stark: every agent needs access; access requires credentials; credentials are attractive targets. When compromised, an agent can be weaponized to operate at machine speed — traversing APIs, exfiltrating data, and executing actions across cloud services far faster than a human attacker could. Keeper Security and other vendors warn that credential and machine-identity compromise is the most immediate threat vector in an agentic environment, making identity-first controls a top priority.

The vendor response — a rapid productization cycle​

The last few days of announcements have focused on three overlapping defense strategies:

• Identity-as-First-Class-Entity: Assign and govern durable identities for agents (Entra Agent ID, Agent 365 registry).
• Runtime enforcement & guardrails: Inline DLP, prompt-injection filters and runtime checks that operate while agents execute (Check Point’s Copilot Studio guardrails, Foundry Control Plane integrations).
• Threat intelligence and observability: Make high-fidelity telemetry and threat context available inside Copilot experiences (Sophos Intelix for Microsoft Security Copilot and Microsoft 365 Copilot).

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Overview of the major vendor moves​

Microsoft: Agent 365, Foundry Control Plane and Security Dashboard for AI​

Microsoft’s Ignite disclosures formalize an agent control-plane concept. Agent 365 is presented as a centralized registry and governance layer — a “control plane” to manage agent identities, permissions and lifecycle across Copilot, Foundry and third-party agent frameworks. Microsoft emphasizes observability at every layer — silicon to OS to agent — and couples Agent 365 with Entra Agent ID for identity lifecycle and conditional access. The Foundry Control Plane brings developer-facing observability, policy and threat-detection primitives into a single environment. Microsoft also outlined a forthcoming Security Dashboard for AI aimed at CISOs to track posture across models, agents, data and cloud signals. These features are available via preview or Frontier programs and were documented in Microsoft’s Ignite Book of News. Why this matters: Microsoft is trying to transplant familiar enterprise controls — identity lifecycle, role-based access, centralized auditing — from human users to autonomous agents. That architectural framing is important because it reduces the blast radius of a compromised agent only when customers actually configure and enforce those controls. Independent reporting corroborates the product messaging and places the announcement in the context of broader agent proliferation predictions.

Keeper Security: secrets management, PAM and agent-aware detection​

Keeper’s recent product updates and market commentary emphasize zero‑trust, zero‑knowledge privileged access for agents, together with a new Model Context Protocol (MCP) integration for secure secrets retrieval. Keeper’s KeeperAI also brings real-time session analysis and automated termination for high-risk privileged sessions — a capability designed to treat risky agent sessions the same way SOCs treat suspicious human activity. Keeper’s customer- and survey-driven messaging stresses that identity and secrets are the proximate choke points for agent compromise. Caveat: some high-impact quotes circulating in regional press summarize Keeper’s position but cannot be located verbatim in Keeper’s public press releases; readers should treat vendor paraphrases appearing in secondary articles as interpretative when verbatim sourcing cannot be found.

Sophos: Intelix inside Copilot experiences​

Sophos launched Sophos Intelix integrations that make its telemetry and enrichment capabilities available directly in Microsoft Security Copilot and Microsoft 365 Copilot. Sophos cites large-scale telemetry (more than 223 TB of daily telemetry, ~34 million detections, and ~11 million automatic blocks) as the backbone for Intelix. The integration allows analysts and business users to query file, URL and IP reputations using natural language inside Copilot, and Sophos is placing Intelix into Microsoft’s Security Store and the Agent 365 ecosystem. These capabilities were announced at Ignite and in Sophos press materials. Why this matters: embedding threat context inside Copilot chat and Security Copilot accelerates triage and enriches automated playbooks. But it also expands the data-flow boundaries between vendors and tenant data, which requires careful contractual and telemetry-handling checks when deployed in regulated environments.

Check Point: runtime guardrails for Copilot Studio​

Check Point’s announcement positions runtime AI Guardrails, DLP and Threat Prevention as inline protections for Microsoft Copilot Studio — the authoring and runtime environment used to build and deploy agents that access corporate data, SaaS connectors and business systems. The integration promises continuous, low-latency enforcement to prevent prompt injection, data leakage and model misuse while agents execute. Check Point’s messaging also references recent acquisitions and AI-native capabilities as the rationale for expanding runtime protections into Copilot Studio. Operationally, runtime guardrails differ from post‑hoc audits: they must interpose on tool calls and agent outputs with minimal latency and high contextual accuracy. This is technically demanding and will require careful validation in each tenant to confirm false-positive rates, latency impact, and policy coverage.

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Technical analysis: what’s new, what’s proven, and what’s unresolved​

Identity-first security: Entra Agent ID and agent registries​

Treating agents like users is the single most consequential architectural decision vendors are making. Durable, managed identities for agents enable:

• Least-privilege assignment and short-lived credentials
• Conditional access policies and traffic inspection
• Audit trails and lifecycle management (creation, rotation, revocation)

Microsoft’s Entra Agent ID plus Agent 365’s registry are concrete steps in this direction, and Keeper’s secrets-management and PAM enhancements complement the identity layer by protecting API keys, service accounts and machine identities. Together, these reduce the chance that a single leaked credential leads to tenant-wide compromise — but only if tenants adopt the controls and align operational playbooks with them. Risk and verification: vendor demos often assume correct configuration and operational discipline. Independent validation should test: credential rotation cadence, just-in-time elevation workflows, and automated revocation in the event of anomalous agent behavior.

Runtime enforcement vs. detection-only postures​

Runtime guardrails (as Check Point describes) aim to prevent unsafe actions at the point an agent makes a tool call. This is meaningfully different from detection-only telemetry injected into a SIEM after the fact. Runtime enforcement must solve for three technical constraints simultaneously:

1. Contextual accuracy: detect prompt injection or sensitive-data exfiltration with high precision across variable prompt and retrieval contexts.
2. Low latency: operate inside execution paths without disrupting user experience or critical SLAs.
3. Policy expressiveness: allow fine-grained DLP and governance rules that map to business semantics, not just regex patterns.

Early claims are promising, but real-world validation is essential. Benchmarks should include false-positive rates, mean enforcement latency, and measured impact on agent throughput.

Model Context Protocol (MCP) and third‑party integrations​

MCP-style connectors are emerging as the de facto way for agents and Copilot experiences to securely fetch external context (threat intelligence, domain-specific knowledge, etc.. Sophos and Keeper both reference MCP-style integrations that surface services into agents while attempting to preserve tenant controls. This interoperability model is strong for extensibility — but it raises rights-of-data-use, provenance and retention questions. Every MCP-enabled call is a potential transfer of sensitive metadata to a third-party service; contractual and technical controls are required to ensure data residency and auditability.

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Cross-checks and verifications of major claims​

• Microsoft’s Agent 365, Foundry Control Plane and Security Dashboard for AI are documented on Microsoft’s official Ignite blog and Book of News; Reuters and The Verge reported independently on the Agent 365 announcements and the broader agent strategy.
• Sophos’ telemetry figures (223 TB/day, 34M detections, 11M blocks) are stated in Sophos’ own press release and product pages describing Sophos Intelix; these numbers come from vendor telemetry and should be validated by customers in proof-of-value trials if used for sizing or SLA expectations.
• Check Point’s Copilot Studio runtime guardrails are described in its November press release and corroborated by multiple industry write-ups discussing the integration; operational claims about low latency and accuracy are vendor statements that require tenant-side proof.
• Keeper’s claims around MCP integration and KeeperAI session handling are present in Keeper product materials and PR; direct quotes attributed to regional spokespeople in secondary press coverage are consistent with Keeper’s public posture on identity-first security, though some paraphrased regional quotes are not present in Keeper’s primary press text and should be treated cautiously.

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Practical guidance for APAC enterprise leaders​

Immediate (0–30 days)​

1. Map agent entry points and inventory service accounts, API keys, and machine identities that agents will use. Treat these as privileged assets.
2. Enable tenant-level guardrails: conditional access, short-lived credentials, and enforce MFA for critical admin pathways.
3. Start a focused pilot with one non‑critical but representative agent workflow to test Entra Agent ID issuance, secrets retrieval flows, and audit logging.

Short term (30–90 days)​

1. Run an agent in shadow mode to collect telemetry without granting write permissions. Measure false positives, policy drift, and latency impacts.
2. Integrate third‑party intelligence (Sophos Intelix or similar) in the Copilot sandbox to validate enrichment quality and data-leakage risk.
3. Validate runtime guardrails in a controlled staging environment — measure enforcement latency and agent throughput under expected load.

Longer-term (90+ days)​

1. Institutionalize agent lifecycle management: role-based creation flows, automated rotation, and emergency revocation scripts.
2. Update procurement and vendor contracts to cover MCP calls, telemetry retention, and auditability for third-party integrations.
3. Invest in human oversight roles — “agent ops,” prompt engineers, and compliance auditors — to monitor behavior trends and control drift.

Key operational KPIs to track:

• Mean time to detect/contain a compromised agent
• False-positive rate for runtime guardrails
• Number of privileged credentials mapped to agents and their rotation frequency
• Monthly MCP call volume and data exposure surface

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Strengths, limitations and open risks​

Notable strengths​

• Vendor alignment on identity-first, runtime protections and enriched threat context is good news: when platform owners (Microsoft) and security vendors (Sophos, Check Point, Keeper) converge on primitives, enterprise adoption is easier and tooling integrates more naturally.
• Embedding threat intelligence inside Copilot chat flows can materially shorten triage times for SOCs and enable faster remediation in the time-compressed environment introduced by agentic attacks.

Persistent limitations and risks​

• Operational complexity: agent registries, secrets rotation, runtime policy configuration and MCP governance create non-trivial engineering and governance overhead, especially for mid-market customers lacking mature identity programs.
• Vendor lock-in and concentration risk: deep integrations with Microsoft Graph, Entra and Copilot ecosystems make multi-cloud portability difficult. Organizations must negotiate exit and portability clauses when vendor concentration is a business concern.
• False positives and latency trade-offs: runtime guardrails must balance precision and speed — overly aggressive blocking can break critical workflows; overly permissive defaults leave data exposed. Each enterprise must empirically measure these trade-offs in representative workloads.
• Third-party data flow governance: MCP integrations that surface external intelligence into agents require contractual clarity around custody, retention and allowed uses of tenant data. These are legal and compliance issues as much as technical ones.

Unverifiable or vendor-proprietary claims​

Some statistics and capability claims are vendor telemetry-based and cannot be independently verified (for example, exact daily telemetry volumes or detection counts). These numbers are useful as directional signals but should be validated in tenant-specific trials and contractual SLAs prior to relying on them for risk modeling or compliance attestations.

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Recommended pilot checklist for Windows‑centric IT and security teams​

1. Identify a single, repeatable workflow for pilot (claims triage, HR onboarding automation, or single SaaS connector workflow).
2. Require human-in-the-loop gates for write actions during pilot; run read-only agent behavior for at least 30 days.
3. Map and rotate credentials (use Keeper or equivalent) and bind agent identities to Entra Agent IDs where possible.
4. Instrument telemetry: forward runtime events to Sentinel (or your SIEM) and enable Security Copilot to test enrichment flows.
5. Stress-test guardrails: run adversarial prompt injection simulations and measure guardrail response and false positives.
6. Produce a measurable TCO and latency report to inform broader rollout decisions.

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Conclusion​

Agentic AI moves the decision-making boundary from humans into software, and that shift requires a corresponding redesign of identity, runtime enforcement, and governance controls. The vendor announcements from Microsoft, Keeper, Sophos and Check Point mark a meaningful maturation: agents are being treated as identities, runtime guardrails are becoming mainstream, and threat intelligence is being embedded directly into Copilot-assisted workflows. Those are essential steps; they do not, however, eliminate organizational responsibilities.
Enterprises in APAC must pair vendor tools with disciplined operational programs: agent registries, just‑in‑time privileges, secrets management, human-in-loop approvals for high-risk actions and contractual clarity around third-party MCP calls. Proof-of-value pilots, measured KPIs for false positives and latency, and explicit contractual protections for telemetry and data use will be the difference between secure, productive agent deployment and painful, high‑impact incidents.
The technology is advancing rapidly — the security posture of agentic AI deployments will be defined less by product roadmaps and more by how rigorously organizations apply identity-first controls, observability, and human oversight to these newly autonomous decision-makers.

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Source: The Manila Times APAC enterprises turn to AI-driven defenses as agentic AI risks grow