AVEVA CONNECT: Unifying Asset Data and Real-Time Analytics for Enterprise Digital Twins

Background​

Overview: Why posture + runtime matters for SaaS agent security​

• They maintain conversational context (chat history, user intents) that can carry sensitive content.
• They often require delegated permissions to other SaaS products (email, file systems, ticketing tools), increasing the risk of lateral data exposure.
• They are dynamic at runtime: prompts, tool selections and memory manipulations change behavior on the fly.

• Enforce least-privileged access across the agent lifecycle.
• Detect prompt injection and malicious code executed via toolchains.
• Block real-time exfiltration attempts (e.g., sending sensitive emails to external recipients or relaying secrets to untrusted LLM endpoints).
• Provide auditing and traceability for compliance and incident response.

How the integration works (technical breakdown)​

• Copilot Studio calls an external threat-detection endpoint each time an agent intends to invoke a tool.
• The primary runtime endpoint is POST /analyze-tool-execution (the API expects a request that includes planner context, the user prompt, relevant chat history, metadata about the conversation, and a proposed tool invocation).
• A secondary POST /validate endpoint is used during setup to confirm the endpoint is reachable and healthy.
• Authentication for third-party threat systems is handled through Microsoft Entra (Azure AD) and can use Federated Identity Credentials (FIC) to enable secretless authentication patterns for registered apps.
• The webhook pattern is synchronous: Copilot Studio submits the tool execution request, waits for the partner decision (allow/block/modify), and proceeds accordingly. That means latency and error handling become operational factors.

• Register a new application inside Microsoft Entra (Azure AD).
• Configure Federated Identity Credentials for secretless authentication, or other supported auth flows as required.
• Configure Copilot Studio to call the external threat detection endpoint and use the vendor’s validation flow to confirm setup.
• Authorize Prisma AIRS (or another vendor) to receive runtime execution context.

What Prisma AIRS adds: posture controls, runtime checks, and red-team testing​

• Posture mapping: It inventories and maps agent permissions, highlighting overly permissive scopes and enforcing least-privileged patterns.
• Configuration validation: It checks agent configurations for misconfigurations that commonly lead to data leakage or excessive trust relationships.
• Model integrity checks: It scans models and configurations for tampering or injected threats.
• Sensitive-data exposure detection: It runs static and dynamic checks to find where secrets or regulated data might be exposed within agent memory, chats or tool calls.
• Runtime blocking: During tool execution, the Prisma AIRS runtime integration inspects the planned action and can block or modify it to prevent unauthorized data transmission or unsafe external calls.
• Specific agent protections: Prisma AIRS claims tailored defenses for agent-specific risks such as identity impersonation, memory manipulation and tool misuse.
• Automated red-teaming: It can stress-test agent deployments by simulating real-world attack scenarios.

Key technical details to verify before deployment​

• API compatibility: Confirm the analyze-tool-execution schema and the api-version used by Copilot Studio match the vendor’s integration. The webhook includes planner context, chat history, tool metadata and user messages; ensure the vendor’s parser handles all expected fields.
• Latency SLAs: Because the webhook is synchronous, define acceptable response-time SLAs for the external threat detection service. Plan for timeouts and fail-open vs. fail-closed behaviors.
• Authentication model: If using Federated Identity Credentials (FIC), validate the identity provider trust chain and rotate or audit credentials where applicable.
• Data residency and telemetry scope: Understand what conversation data, prompts or metadata are transmitted to the external vendor. Confirm retention windows, encryption-at-rest/in-transit, and whether any PII will be stored outside the tenant.
• Failure modes: Decide whether a vendor unavailability should default to blocking tool executions (safer) or allow them (higher availability). Document the business and security tradeoffs.

Threat scenarios the integration addresses​

• Prompt injection: Malicious user inputs or manipulated prompts that coerce an agent to disclose secrets or execute dangerous commands.
• Data exfiltration via tool misuse: Agents with email, file sharing or external request capabilities could be used to send sensitive files or tokens to unapproved endpoints.
• Identity impersonation: Agents can pose as users or services; runtime checks can detect improbable sender/recipient relationships or unauthorized impersonation attempts.
• Memory manipulation and poisoning: Agents that persist conversational memory could be targeted to store malicious instructions or hidden data that later surface in tool calls.
• Relay to untrusted LLMs: Agents could forward internal content to external LLM services; runtime enforcement can block outbound calls or redact sensitive content.

Operational considerations: performance, logging, and auditability​

• Performance impact: Each tool invocation will incur the latency cost of an external API call. Measure the typical execution frequency and ensure the threat detection endpoint can scale. Implement caching where safe (e.g., repeated identical evaluations) but validate cache expiry semantics.
• Consistent auditing: Ensure every decision returned by the external webhook—allowed, blocked, or modified—is logged with correlation IDs, tool metadata and planner context. These logs must be integrated into SIEM and retention policies for compliance.
• Correlation and tracing: Use x-ms-correlation-id or similar request tracing headers to correlate Copilot Studio events with vendor verdicts. This is vital for incident investigation and for reconstructing an agent’s actions.
• Incident response playbooks: Define actions for blocked executions (user notifications, automated rollback of side effects, alerts to security teams), and integrate those responses into existing incident handling procedures.
• Governance and approval: Expand IAM approvals to include the vendor integration. The registered application in Microsoft Entra should have clearly defined owners and access reviews scheduled.

Limitations, vendor claims and areas that require validation​

• Efficacy of advanced detections: Claims that a product “actively defends against prompt injection, malicious code, and data leaks” must be validated through testing using your own agents, data, and adversary simulations.
• Identity impersonation and memory-manipulation protections: These are complex problems that require careful evaluation. Proof of effectiveness should include red-team results, sample blocked scenarios and telemetry demonstrating the solution’s detection fidelity.
• Coverage of tool types: Verify which tool invocations the webhook covers (email sends, HTTP calls, file stores, etc.. Some custom or third-party tooling might behave differently.
• Data handling practices: Vendors receiving planner context and chat history need explicit contractual protections: data minimization, encryption, access control, and clear deletion policies. Confirm whether telemetry is used to train models and if so, whether your data is excluded.
• Fail-open vs fail-closed default behavior: Understand the default behavior for webhook failures—this affects both security posture and availability.

Recommended validation and deployment checklist​

• Run a focused pilot with a small set of agents that represent different permission profiles (email, file access, external API calls).
• Execute red-team scenarios: prompt injection attempts, simulated data exfiltration, and identity impersonation tests to measure detection and false-positive rates.
• Measure end-to-end latency for common tool invocations and define acceptable thresholds. Test at expected load peaks.
• Confirm log integration into the central SIEM and verify correlation IDs and context are present for forensic use.
• Review the vendor’s data handling, retention and incident response SLAs; ensure contractual protections cover telemetry use and model training.
• Conduct an access review for the registered Microsoft Entra application; enable monitoring and periodic revalidation of Federated Identity Credentials.
• Decide fail-open vs fail-closed behavior and document risk acceptance for each agent class.
• Train service owners and support teams on expected user-facing errors and the process for escalating blocked actions.

Practical examples: what a blocked execution looks like​

• Example 1 — Misaddressed email: An agent attempts to send a report to an external address containing PII. The webhook inspects the planned email, detects an external domain mismatch relative to policy, and returns a block decision. The agent notifies the user with a remediation message and logs the event.
• Example 2 — Outbound LLM relay: An agent prepares to forward a confidential brief to an unapproved external LLM for summarization. Runtime checks identify sensitive content and an untrusted destination, blocking the call and retaining an audit trail of the attempted execution.
• Example 3 — Prompt injection: A chat history includes a user-supplied snippet that attempts to override the agent’s instructions to output credentials. The webhook recognizes the injection pattern and either sanitizes the prompt or rejects the tool invocation.

Broader context: why vendors and platform owners are adding runtime webhooks now​

• The rise of agentic AI in enterprise workflows means fixed, static security models are insufficient. Agents change behavior in-flight, and the security decision must likewise occur at runtime.
• Platform owners (like Microsoft) need to enable a marketplace of security integrations while keeping control of the execution path. A standard webhook interface balances extensibility (allowing vendors to provide specialized checks) with platform governance.

Risks and potential misuse: what defenders should watch for​

• Centralized chokepoints: An attacker targeting the webhook endpoint (through DDoS or supply-chain attacks) could disrupt agent operations. Assign hardened endpoints, rate-limiting and multi-region redundancy to mitigate this.
• Over-reliance on vendor controls: Organizations may be tempted to outsource policy enforcement entirely to a vendor. Maintain internal policy as the source of truth and treat vendors as enforcement helpers, not replacements for governance.
• Telemetry confidentiality exposure: Transmitting chat histories and planner contexts outside the tenant creates potential privacy and compliance concerns. Enforce data minimization and contractual protections.
• False positives and business impact: Aggressive blocking rules can break legitimate automations. Establish exception processes and quick remediation channels.
• Shared responsibility ambiguity: Clear operational and security responsibilities must be defined between the tenant, platform (Copilot Studio), and the security vendor.

Recommendations for Windows and Microsoft-centric environments​

• Inventory agent capabilities and map each to a risk tier (high privilege, medium privilege, low privilege).
• Apply the runtime webhook first to high-risk agents (email automation, tenant-level toolchains).
• Use Federated Identity Credentials (FIC) for secretless authentication to reduce credential sprawl, but monitor and review trust relationships frequently.
• Integrate webhook logs with existing monitoring (Azure Monitor, Microsoft Sentinel or third-party SIEM) so agent events are visible alongside other tenant telemetry.
• Maintain an allowlist of trusted LLM endpoints and blacklists of known malicious domains at the webhook enforcement layer.
• Implement automated rollback or quarantine actions when an agent is blocked mid-execution to avoid partial side effects.

The bottom line​