Declutter and Defend: Reducing promotional mail noise with Microsoft Defender
Enterprise inboxes are overwhelmed with graymail — legitimate, bulk email like newsletters, vendor promotions, and product updates that isn't malicious but buries the messages that matter. When high volumes of these mails land in the inbox, it crowds out priority communications and can dull security vigilance. Employees conditioned to ignore repetitive emails may miss signs of a real threat. It also creates recurring work for admins and security teams who must continuously tune filters, manage exception requests, and chase noise from user reports for email that isn’t malicious. Because graymail passes every spam filter check, traditional defenses don't separate it — leaving this signal-to-noise gap unaddressed. Today we’re excited to announce that Microsoft Defender now includes built-in graymail filtering. It is delivered natively through a new Promotions experience in Outlook that automatically classifies and separates bulk email, so it no longer competes with business-critical communication in the inbox. Now in Public Preview, this capability learns from how users interact with graymail to become more accurate over time. Coupled with the existing Bulk Senders Insight report, Defender brings data-driven bulk classification and control into the security workflows you already use. What Is Graymail? Graymail is legitimate bulk email that isn't malicious—product newsletters, event announcements, marketing promotions, and software update notifications from reputable, authenticated senders. It is distinct from spam and from phishing - graymail comes from real organizations with proper authentication and traditional spam filters aren't designed to handle it. Graymail handling in Microsoft Defender Microsoft Defender's approach is built on three principles: classify intelligently, deliver natively, and learn continuously. Promotions Folder — Intelligent Inbox Organization A dedicated Promotions folder, natively provisioned in Outlook, now keeps legitimate bulk mail out of the primary inbox. Promotional content is separated from priority emails without being sent to Junk, which means users can still access and browse newsletters and updates at their own pace. The folder appears at the top level of the mailbox for easy discovery and is visible across all Outlook experiences. Non-spam bulk mail below the organization's configured Bulk Complaint Level threshold is automatically routed to the Promotions folder. Messages from senders the user has explicitly allowed continue to land in the Inbox. Messages identified as spam continue to go to Junk. To enable the Promotions folder administrators need to enable the "Bulk Moves Enabled" setting in their anti-spam policy. The Promotions folder is then created for all users and used for routing only when this setting is ON. Existing mail flow is unaffected. Promotional mail tagging and Mailbox Rule Support Messages classified as graymail will automatically be labeled with a "Promotions" system tag in Outlook. The tag provides instant visual context without requiring users to open each message and is visible in Outlook on the Web and the native Outlook desktop apps for Windows and Mac. During Public Preview, the tagging component is opt-in, requiring administrators to enable it by configuring an Exchange Transport Rule. Once generally available, it will be enabled by default. Because this classification is integrated at the client level, the Promotions tag can also be used as a condition in Outlook mailbox rules. This enables custom routing logic for advanced scenarios like moving all promotions-tagged messages from a specific sender to a custom folder, flagging certain promotional emails for follow-up, or auto-forwarding or deleting promotions that meet specific criteria. This transforms the Promotions classification from a one-way filter into a flexible building block for personal and organizational workflows—particularly valuable for power users and teams with compliance or archival requirements. Adaptive Learning Microsoft Defender's graymail filtering gets smarter with every interaction. The system learns directly from how users handle their mail. When a user moves a message out of the Promotions folder and back to the Inbox, future emails from that sender will no longer be placed in the Promotions folder. When a user moves a message from the Inbox into the Promotions folder, future emails from that sender will be routed to the Promotions folder automatically. This creates a personalized, self-improving experience that becomes more accurate over time - no manual rule configuration required, no safe-sender lists to maintain, and no filtering rules for IT teams to manage on behalf of individual employees. Built into existing Security Workflows Administrators also gain visibility through the Bulk Senders Insight report, which provides data-driven guidance on what your organization actually receives and can help tune your bulk mail filtering. Graymail has long been the unsolved middle ground of email security—too legitimate to block, too noisy to ignore. Microsoft Defender now handles it where it should be handled: inside the platform, inside the mailbox, and inside the security workflows your organization already relies on. No new portals, no new vendors, no compromise between security and user experience. Get Started Configure promotions tagging and the promotions folder today - Bulk email detection documentation on Microsoft Learn. Monitor the experience using the Bulk Senders Insight report.
What happens when attackers get AI too?
Join Microsoft's live AMA on October 27, from 9:00–10:00 AM Pacific Time, to explore how AI could reshape cyberattacks—from reconnaissance and phishing to scripting and data analysis. Hear experts unpack realistic threats, practical limits, and the security controls that help keep organizations protected.I built a free, open-source M365 security assessment tool - looking for feedback
I work as an IT consultant, and a good chunk of my time is spent assessing Microsoft 365 environments for small and mid-sized businesses. Every engagement started the same way: connect to five different PowerShell modules, run dozens of commands across Entra ID, Exchange Online, Defender, SharePoint, and Teams, manually compare each setting against CIS benchmarks, then spend hours assembling everything into a report the client could actually read. The tools that automate this either cost thousands per year, require standing up Azure infrastructure just to run, or only cover one service area. I wanted something simpler: one command that connects, assesses, and produces a client-ready deliverable. So I built it. What M365 Assess does https://github.com/Daren9m/M365-Assess is a PowerShell-based security assessment tool that runs against a Microsoft 365 tenant and produces a comprehensive set of reports. Here is what you get from a single run: 57 automated security checks aligned to the CIS Microsoft 365 Foundations Benchmark v6.0.1, covering Entra ID, Exchange Online, Defender for Office 365, SharePoint Online, and Teams 12 compliance frameworks mapped simultaneously -- every finding is cross-referenced against NIST 800-53, NIST CSF 2.0, ISO 27001:2022, SOC 2, HIPAA, PCI DSS v4.0.1, CMMC 2.0, CISA SCuBA, and DISA STIG (plus CIS profiles for E3 L1/L2 and E5 L1/L2) 20+ CSV exports covering users, mailboxes, MFA status, admin roles, conditional access policies, mail flow rules, device compliance, and more A self-contained HTML report with an executive summary, severity badges, sortable tables, and a compliance overview dashboard -- no external dependencies, fully base64-encoded, just open it in any browser or email it directly The entire assessment is read-only. It never modifies tenant settings. Only Get-* cmdlets are used. A few things I'm proud of Real-time progress in the console. As the assessment runs, you see each check complete with live status indicators and timing. No staring at a blank terminal wondering if it hung. The HTML report is a single file. Logos, backgrounds, fonts -- everything is embedded. You can email the report as an attachment and it renders perfectly. It supports dark mode (auto-detects system preference), and all tables are sortable by clicking column headers. Compliance framework mapping. This was the feature that took the most work. The compliance overview shows coverage percentages across all 12 frameworks, with drill-down to individual controls. Each finding links back to its CIS control ID and maps to every applicable framework control. Pass/Fail detail tables. Each security check shows the CIS control reference, what was checked, what the expected value is, what the actual value is, and a clear Pass/Fail/Warning status. Findings include remediation descriptions to help prioritize fixes. Quick start If you want to try it out, it takes about 5 minutes to get running: # Install prerequisites (if you don't have them already) Install-Module Microsoft.Graph, ExchangeOnlineManagement -Scope CurrentUser Clone and run git clone https://github.com/Daren9m/M365-Assess.git cd M365-Assess .\Invoke-M365Assessment.ps1 The interactive wizard walks you through selecting assessment sections, entering your tenant ID, and choosing an authentication method (interactive browser login, certificate-based, or pre-existing connections). Results land in a timestamped folder with all CSVs and the HTML report. Requires PowerShell 7.x and runs on Windows (macOS and Linux are experimental -- I would love help testing those platforms). Cloud support M365 Assess works with: Commercial (global) tenants GCC, GCC High, and DoD environments If you work in government cloud, the tool handles the different endpoint URIs automatically. What is next This is actively maintained and I have a roadmap of improvements: More automated checks -- 140 CIS v6.0.1 controls are tracked in the registry, with 57 automated today. Expanding coverage is the top priority. Remediation commands -- PowerShell snippets and portal steps for each finding, so you can fix issues directly from the report. XLSX compliance matrix -- A spreadsheet export for audit teams who need to work in Excel. Standalone report regeneration -- Re-run the report from existing CSV data without re-assessing the tenant. I would love your feedback I have been building this for my own consulting work, but I think it could be useful to the broader community. If you try it, I would genuinely appreciate hearing: What checks should I prioritize next? Which security controls matter most in your environment? What compliance frameworks are most requested by your clients or auditors? How does the report land with non-technical stakeholders? Is the executive summary useful, or does it need work? macOS/Linux users -- does it run? What breaks? I have tested it on macOS, but not extensively. Bug reports, feature requests, and contributions are all welcome on GitHub. Repository: https://github.com/Daren9m/M365-Assess License: MIT (free for commercial and personal use) Runtime: PowerShell 7.x Thanks for reading. Happy to answer any questions in the comments.
Feature Request: Extend Security Copilot inclusion (M365 E5) to M365 A5 Education tenants
Background At Ignite 2025, Microsoft announced that Security Copilot is included for all Microsoft 365 E5 customers, with a phased rollout starting November 18, 2025. This is a significant step forward for security operations. The gap Microsoft 365 A5 for Education is the academic equivalent of E5 — it includes the same core security stack: Microsoft Defender, Entra, Intune, and Purview. However, the Security Copilot inclusion explicitly covers only commercial E5 customers. There is no public roadmap or timeline for extending this benefit to A5 education tenants. Why this matters Education institutions face the same cybersecurity threats as commercial organizations — often with fewer dedicated security resources. The A5 license was positioned as the premium security offering for education. Excluding it from Security Copilot inclusion creates an inequity between commercial and education customers holding functionally equivalent license tiers. Request We would like Microsoft to: Confirm whether Security Copilot inclusion will be extended to M365 A5 Education tenants If yes, provide an indicative timeline If no, clarify the rationale and what alternative paths exist for education customers Are other EDU admins in the same situation? Would appreciate any upvotes or comments to help raise visibility with the product team.
Microsoft 365 Developer E5 license lacking endpoints and device ON defender portal
Dear Support Team, I am a microsoft certified trainer (MCT). I currently have a Microsoft 365 Developer E5 license assigned to my tenant. However, I have noticed that my Microsoft Defender portal (security.microsoft.com) is missing several critical features. For example, I cannot see the Endpoints or Devices menus, which is preventing me from implementing and testing Microsoft Defender for Endpoint. Additionally, my Azure tenant and Microsoft 365 tenant are separate. This has created challenges when configuring security services such as Microsoft Sentinel (SIEM), as certain prerequisites and integrations require configuration through the Microsoft Defender portal. Due to the missing Defender features, I am unable to complete the necessary setup. I would appreciate your assistance in understanding: Why the Endpoints and Devices sections are unavailable in my Defender portal despite having a Microsoft 365 Developer E5 license. Whether additional licensing, onboarding steps, or tenant configurations are required to enable Microsoft Defender for Endpoint features. How best to integrate or align my separate Azure and Microsoft 365 tenants to support services such as Microsoft Sentinel and Defender XDR. These issues are significantly impacting my ability to evaluate and implement Microsoft's security solutions. I would appreciate any guidance or recommendations to resolve them.Authorization and Governance for AI Agents: Runtime Authorization Beyond Identity at Scale
Designing Authorization‑Aware AI Agents at Scale Enforcing Runtime RBAC + ABAC with Approval Injection (JIT) Microsoft Entra Agent Identity enables organizations to govern and manage AI agent identities in Copilot Studio, improving visibility and identity-level control. However, as enterprises deploy multiple autonomous AI agents, identity and OAuth permissions alone cannot answer a more critical question: “Should this action be executed now, by this agent, for this user, under the current business and regulatory context?” This post introduces a reusable Authorization Fabric—combining a Policy Enforcement Point (PEP) and Policy Decision Point (PDP)—implemented as a Microsoft Entra‑protected endpoint using Azure Functions/App Service authentication. Every AI agent (Copilot Studio or AI Foundry/Semantic Kernel) calls this fabric before tool execution, receiving a deterministic runtime decision: ALLOW / DENY / REQUIRE_APPROVAL / MASK Who this is for Anyone building AI agents (Copilot Studio, AI Foundry/Semantic Kernel) that call tools, workflows, or APIs Organizations scaling to multiple agents and needing consistent runtime controls Teams operating in regulated or security‑sensitive environments, where decisions must be deterministic and auditable Why a V2? Identity is necessary—runtime authorization is missing Entra Agent Identity (preview) integrates Copilot Studio agents with Microsoft Entra so that newly created agents automatically get an Entra agent identity, manageable in the Entra admin center, and identity activity is logged in Entra. That solves who the agent is and improves identity governance visibility. But multi-agent deployments introduce a new risk class: Autonomous execution sprawl — many agents, operating with delegated privileges, invoking the same backends independently. OAuth and API permissions answer “can the agent call this API?” They do not answer “should the agent execute this action under business policy, compliance constraints, data boundaries, and approval thresholds?” This is where a runtime authorization decision plane becomes essential. The pattern: Microsoft Entra‑Protected Authorization Fabric (PEP + PDP) Instead of embedding RBAC logic independently inside every agent, use a shared fabric: PEP (Policy Enforcement Point): Gatekeeper invoked before any tool/action PDP (Policy Decision Point): Evaluates RBAC + ABAC + approval policies Decision output: ALLOW / DENY / REQUIRE_APPROVAL / MASK This Authorization Fabric functions as a shared enterprise control plane, decoupling authorization logic from individual agents and enforcing policies consistently across all autonomous execution paths. Architecture (POC reference architecture) Use a single runtime decision plane that sits between agents and tools. What’s important here Every agent (Copilot Studio or AI Foundry/SK) calls the Authorization Fabric API first The fabric is a protected endpoint (Microsoft Entra‑protected endpoint required) Tools (Graph/ERP/CRM/custom APIs) are invoked only after an ALLOW decision (or approval) Trust boundaries enforced by this architecture Agents never call business tools directly without a prior authorization decision The Authorization Fabric validates caller identity via Microsoft Entra Authorization decisions are centralized, consistent, and auditable Approval workflows act as a runtime “break-glass” control for high-impact actions This ensures identity, intent, and execution are independently enforced, rather than implicitly trusted. Runtime flow (Decision → Approval → Execution) Here is the runtime sequence as a simple flow (you can keep your Mermaid diagram too). ```mermaid flowchart TD START(["START"]) --> S1["[1] User Request"] S1 --> S2["[2] Agent Extracts Intent\n(action, resource, attributes)"] S2 --> S3["[3] Call /authorize\n(Entra protected)"] S3 --> S4 subgraph S4["[4] PDP Evaluation"] ABAC["ABAC: Tenant · Region · Data Sensitivity"] RBAC["RBAC: Entitlement Check"] Threshold["Approval Threshold"] ABAC --> RBAC --> Threshold end S4 --> Decision{"[5] Decision?"} Decision -->|"ALLOW"| Exec["Execute Tool / API"] Decision -->|"MASK"| Masked["Execute with Masked Data"] Decision -->|"DENY"| Block["Block Request"] Decision -->|"REQUIRE_APPROVAL"| Approve{"[6] Approval Flow"} Approve -->|"Approved"| Exec Approve -->|"Rejected"| Block Exec --> Audit["[7] Audit & Telemetry"] Masked --> Audit Block --> Audit Audit --> ENDNODE(["END"]) style START fill:#4A90D9,stroke:#333,color:#fff style ENDNODE fill:#4A90D9,stroke:#333,color:#fff style S1 fill:#5B5FC7,stroke:#333,color:#fff style S2 fill:#5B5FC7,stroke:#333,color:#fff style S3 fill:#E8A838,stroke:#333,color:#fff style S4 fill:#FFF3E0,stroke:#E8A838,stroke-width:2px style ABAC fill:#FCE4B2,stroke:#999 style RBAC fill:#FCE4B2,stroke:#999 style Threshold fill:#FCE4B2,stroke:#999 style Decision fill:#fff,stroke:#333 style Exec fill:#2ECC71,stroke:#333,color:#fff style Masked fill:#27AE60,stroke:#333,color:#fff style Block fill:#C0392B,stroke:#333,color:#fff style Approve fill:#F39C12,stroke:#333,color:#fff style Audit fill:#3498DB,stroke:#333,color:#fff ``` Design principle: No tool execution occurs until the Authorization Fabric returns ALLOW or REQUIRE_APPROVAL is satisfied via an approval workflow. Where Power Automate fits (important for readers) In most Copilot Studio implementations, Agents calls Power Automate (agent flows), is the practical integration layer that calls enterprise services and APIs. Copilot Studio supports “agent flows” as a way to extend agent capabilities with low-code workflows. For this pattern, Power Automate typically: acquires/uses the right identity context for the call (depending on your tenant setup), and calls the /authorize endpoint of the Authorization Fabric, returns the decision payload to the agent for branching. Copilot Studio also supports calling REST endpoints directly using the HTTP Request node, including passing headers such as Authorization: Bearer <token>. Protected endpoint only: Securing the Authorization Fabric with Microsoft Entra For this V2 pattern, the Authorization Fabric must be protected using Microsoft Entra‑protected endpoint on Azure Functions/App Service (built‑in auth). Microsoft Learn provides the configuration guidance for enabling Microsoft Entra as the authentication provider for Azure App Service / Azure Functions. Step 1 — Create the Authorization Fabric API (Azure Function) Expose an authorization endpoint: HTTP Step 2 — Enable Microsoft Entra‑protected endpoint on the Function App In Azure Portal: Function App → Authentication Add identity provider → Microsoft Choose Workforce configuration (enterprise tenant) Set Require authentication for all requests This ensures the Authorization Fabric is not callable without a valid Entra token. Step 3 — Optional hardening (recommended) Depending on enterprise posture, layer: IP restrictions / Private endpoints APIM in front of the Function for rate limiting, request normalization, centralized logging (For a POC, keep it minimal—add hardening incrementally.) Externalizing policy (so governance scales) To make this pattern reusable across multiple agents, policies should not be hardcoded inside each agent. Instead, store policy definitions in a central policy store such as Cosmos DB (or equivalent configuration store), and have the PDP load/evaluate policies at runtime. Why this matters: Policy changes apply across all agents instantly (no agent republish) Central governance + versioning + rollback becomes possible Audit and reporting become consistent across environments (For the POC, a single JSON document per policy pack in Cosmos DB is sufficient. For production, add versioning and staged rollout.) Store one PolicyPack JSON document per environment (dev/test/prod). Include version, effectiveFrom, priority for safe rollout/rollback. Minimal decision contract (standard request / response) To keep the fabric reusable across agents, standardize the request payload. Request payload (example) Decision response (deterministic) Example scenario (1 minute to understand) Scenario: A user asks a Finance agent to create a Purchase Order for 70,000. Even if the user has API permission and the agent can technically call the ERP API, runtime policy should return: REQUIRE_APPROVAL (threshold exceeded) trigger an approval workflow execute only after approval is granted This is the difference between API access and authorized business execution. Sample Policy Model (RBAC + ABAC + Approval) This POC policy model intentionally stays simple while demonstrating both coarse and fine-grained governance. 1) Coarse‑grained RBAC (roles → actions) FinanceAnalyst CreatePO up to 50,000 ViewVendor FinanceManager CreatePO up to 100,000 and/or approve higher spend 2) Fine‑grained ABAC (conditions at runtime) ABAC evaluates context such as region, classification, tenant boundary, and risk: 3) Approval injection (Agent‑level JIT execution) For higher-risk/high-impact actions, the fabric returns REQUIRE_APPROVAL rather than hard deny (when appropriate): How policies should be evaluated (deterministic order) To ensure predictable and auditable behavior, evaluate in a deterministic order: Tenant isolation & residency (ABAC hard deny first) Classification rules (deny or mask) RBAC entitlement validation Threshold/risk evaluation Approval injection (JIT step-up) This prevents approval workflows from bypassing foundational security boundaries such as tenant isolation or data sovereignty. Copilot Studio integration (enforcing runtime authorization) Copilot Studio can call external REST APIs using the HTTP Request node, including passing headers such as Authorization: Bearer <token> and binding response schema for branching logic. Copilot Studio also supports using flows with agents (“agent flows”) to extend capabilities and orchestrate actions. Option A (Recommended): Copilot Studio → Agent Flow (Power Automate) → Authorization Fabric Why: Flows are a practical place to handle token acquisition patterns, approval orchestration, and standardized logging. Topic flow: Extract user intent + parameters Call an agent flow that: calls /authorize returns decision payload Branch in the topic: If ALLOW → proceed to tool call If REQUIRE_APPROVAL → trigger approval flow; proceed only if approved If DENY → stop and explain policy reason Important: Tool execution must never be reachable through an alternate topic path that bypasses the authorization check. Option B: Direct HTTP Request node to Authorization Fabric Use the Send HTTP request node to call the authorization endpoint and branch using the response schema. This approach is clean, but token acquisition and secure secretless authentication are often simpler when handled via a managed integration layer (flow + connector). AI Foundry / Semantic Kernel integration (tool invocation gate) For Foundry/SK agents, the integration point is before tool execution. Semantic Kernel supports Azure AI agent patterns and tool integration, making it a natural place to enforce a pre-tool authorization check. Pseudo-pattern: Agent extracts intent + context Calls Authorization Fabric Enforces decision Executes tool only when allowed (or after approval) Telemetry & audit (what Security Architects will ask for) Even the best policy engine is incomplete without audit trails. At minimum, log: agentId, userUPN, action, resource decision + reason + policyIds approval outcome (if any) correlationId for downstream tool execution Why it matters: you now have a defensible answer to: “Why did an autonomous agent execute this action?” Security signal bonus: Denials, unusual approval rates, and repeated policy mismatches can also indicate prompt injection attempts, mis-scoped agents, or governance drift. What this enables (and why it scales) With a shared Authorization Fabric: Avoid duplicating authorization logic across agents Standardize decisions across Copilot Studio + Foundry agents Update governance once (policy change) and apply everywhere Make autonomy safer without blocking productivity Closing: Identity gets you who. Runtime authorization gets you whether/when/how. Copilot Studio can automatically create Entra agent identities (preview), improving identity governance and visibility for agents. But safe autonomy requires a runtime decision plane. Securing that plane as an Entra-protected endpoint is foundational for enterprise deployments. In enterprise environments, autonomous execution without runtime authorization is equivalent to privileged access without PIM—powerful, fast, and operationally risky.
Security Admin Center Tenant Allow/Block List Not Able to Block IPv4?
While using the Security Admin Center Tenant Allow/Block List we have been able to block specific email addresses and IPv6 IP addresses but are unable to block IPv4 IP addresses. We have tried both using the console and the CLI but have turned up unsuccessful both times when it comes to IPv4. A large majority of the phishing attempts that we encounter come from IPv4 addresses but we have been unable to block any of these. Will there ever be functionality for IPv4 within the Tenant Allow/Block list or is the only option to use conditional access policies? Also why is this enterprise tool only functional with IPv6 and without documentation stating that it does not work for IPv4?Windows defender is having a lot of problems.
So I have a Microsoft 365 Family subscription, and Dark Web Monitoring shows 0 monitored items. SSN verification fails and advises you to contact support. I was also unable to delete the monitored information. I’m receive the error "Something went wrong, try again in a bit." The issue occurs in the Microsoft Defender app, web portal, and across devices. Is there anyway that I can get help with this?Securing AI Agents at Runtime: Real-Time Protection and Threat Detection for Microsoft Agent 365
Organizations are rapidly adopting AI agents to automate workflows, access enterprise data, invoke tools, and take actions on behalf of users. This autonomy creates a fundamentally new security challenge. Unlike traditional AI applications, agents operate across dynamic execution flows, interacting with external content, calling tools, and accessing sensitive resources. These interactions create new attack paths that traditional security controls were not designed to address. Today, we're announcing two major milestones for Security for AI in Microsoft Defender for Microsoft Agent 365: Threat detection for Microsoft Agent 365 agents — now in public preview. Real-time protection for Microsoft Agent 365 tooling servers — now generally available. Together, these capabilities help security teams detect, investigate, and block attacks targeting AI agents, extending Microsoft Defender's threat protection capabilities into the agent runtime. Threat detection for Microsoft Agent 365 Agents (Public Preview) Threat detection provides SOC teams with detailed visibility into attacks and suspicious activity targeting AI agents. By analyzing runtime signals across agent interactions, tool usage, and execution patterns, Microsoft Defender identifies suspicious and malicious behavior throughout the agent execution lifecycle and surfaces actionable security alerts for SOC teams. Threat detection supports cloud agent types that emit observability logs to Microsoft Agent 365, including: Microsoft Copilot Studio Microsoft Foundry Microsoft 365 Copilot Agent Builder Agents integrated through the Microsoft Agent 365 SDK This provides consistent threat visibility across supported Microsoft Agent 365 agent experiences, regardless of how the agent was built. Fig. 1. Microsoft Security for AI alerts in Microsoft Defender XDR (Preview) Microsoft Defender identifies a broad range of AI-specific threats, including: Indirect prompt injection (XPIA) — malicious instructions embedded in external content designed to manipulate agent behavior. Evasion techniques — attempts to bypass agent instructions or security controls. Malicious content propagation — attempts to use agents to generate or distribute malicious content. Secret leakage — exposure of credentials, API keys, or other sensitive information through agent interactions. LLM reconnaissance — attempts to probe agent capabilities, instructions, or security boundaries. Suspicious IP access — agent access originating from anonymized or suspicious IP addresses. Alerts are surfaced directly in Microsoft Defender, enabling SOC analysts to investigate and respond using familiar workflows, Advanced Hunting queries, and the Defender XDR investigation experience. Real-time protection for WorkIQ and Custom MCP servers (General Availability) Real-time protection moves beyond detection by blocking threats inline when AI agents interact with WorkIQ and custom MCP servers (see Microsoft Agent 365 tooling servers). When an agent invokes a registered tool or receives a tool response, Defender evaluates the interaction against configured security policies and determines whether to allow or block it directly within the agent's execution flow. This helps prevent malicious actions and data leakage in real time, without requiring agent developers to implement custom security logic. Fig. 2. Microsoft Security for AI Real-Time Protection policy in Defender Real-time protection currently guards against high-impact threats, including: Evasion techniques — attempts to bypass agent guardrails or security controls. Malicious content propagation — preventing agents from spreading malicious content through tool actions. Secret leakage — blocking agents from inadvertently exposing credentials or sensitive data through tool calls. Communication with untrusted domains — preventing agents from sending email or data to high-risk or untrusted email domains. Better Together: Detection and Protection Threat detection and real-time protection address complementary parts of the agent security lifecycle. Real-time protection provides inline enforcement to block malicious interactions during execution, while threat detection gives SOC teams the visibility and investigation context needed to identify attack patterns, assess impact, and respond to suspicious activity. Together, they provide a defense-in-depth approach that combines runtime enforcement with SOC-driven detection and investigation, purpose-built for AI agents. Getting Started Both capabilities are available through Microsoft Defender, using a dedicated Security for AI workload experience that brings together AI threat detections, investigations, and runtime protection policies. To learn more: Enable security for AI agents using Microsoft Defender Detect and investigate threats to AI agents using Microsoft Defender (Preview) Protect AI agents in real time using Microsoft Defender As AI agents become more autonomous and gain access to enterprise data and tools, securing their runtime behavior becomes critical. With Threat Detection and Real-Time Protection, Microsoft Defender helps organizations adopt AI agents with security controls designed for how agents actually operate—detecting attacks, enabling SOC investigation, and blocking malicious interactions at runtime.
