SharePoint NoAccess Sites: Search Indexing and Copilot Misconceptions Guide
What is NoAccess Mode in SharePoint? NoAccess mode is a site-level setting in SharePoint Online that restricts user access to the site without permanently deleting it. Think of it as putting the site behind a locked door, the content still exists, but no one can open it. Why Do Organizations Use It? Temporary Lockdown: When a site is under review, being decommissioned, or needs to be secured quickly. Compliance & Security: Helps prevent accidental data exposure during audits or ownership changes. Preserve Data: Unlike deleting a site, NoAccess keeps the content intact for future reference or migration. How Does It Affect Search and Copilot? Search Indexing: By default, NoAccess mode does not remove the site from the search index. This means files may still appear in search results unless additional controls (like Restricted Content Discovery or NoCrawl) are applied. Copilot Behavior: Copilot uses the same index as Microsoft Search. If a site remains indexed, Copilot can surface summaries or references to its content even if users can’t open the files. This is why governance settings like Restricted Access Control or disabling indexing are critical when using Copilot. Why does this happen? NoAccess blocks site access, not indexing. The site remains in the search index unless indexing is explicitly disabled or Restricted Content Discovery (RCD) is enabled. Security trimming still applies. Users will only see items they have direct permissions to (e.g., via shared links). They cannot open anything they don’t have access to. Copilot respects permissions. It uses the same security model as Microsoft Search and Graph, so it never bypasses access controls. Low Priority. Marking a site as NoAccess is a bulk operation that goes into a low priority queue, specifically to avoid system bottlenecks and ensure real-time content changes are prioritized over less critical updates which means it can take much longer than expected for those sites to stop appearing in search results. What are the options to fully hide content? Turn off Allow this site to appear in search results: This setting removes the site from indexing. Note: change the search setting BEFORE setting NoAccess to a site. Enable Restricted Content Discovery (RCD): This hides the site from search and Copilot while keeping it accessible to those with permissions. There is a PowerShell cmdlet available: Set-SPOSite –identity <site-url> -RestrictContentOrgWideSearch $true Please note that for larger sites, both the RCD and no-crawl processes may require a minimum of a week to reflect updates. According to the RCD documentation, sites with more than 500,000 pages could experience update times exceeding one week. What are the options to get Site Crawl information? When setting up the site for NoCrawl, you can run REST to see if the items are returning in search from that site. You can use a simple REST call like: https://contoso.sharepoint.com/_api/search/query?querytext='path:"<siteurl>"'&sourceid='8413cd39-2156-4e00-b54d-11efd9abdb89'&trimduplicates=false. You have to login into the tenant first. An XML object will be generated, please look for <d:TotalRows m:type="Edm.Int32">1</d:TotalRows> you will see the count going down, at some point the count will be equals to 0, that means all items were removed from index. You can use PnP to check the site settings, here an example - Enable/Disable Search Crawling on Sites and Libraries | PnP Samples, remember PnP is open source and it is not supported by Microsoft. Get-PnPSite | Select NoCrawl Key Takeaways Setting a SharePoint site to NoAccess does not automatically remove it from search or Copilot. Copilot and Search always enforce permissions users never see or access unauthorized content. For complete removal, disable site indexing or enable RCD. Monitor index status to confirm content is truly hidden. Understanding and managing these settings ensures secure, seamless experiences with Copilot and Microsoft Search. Helpful Resources Lock and unlock sites - SharePoint in Microsoft 365 | Microsoft Learn Enable/Disable Search Crawling on Sites and Libraries | PnP Samples Restrict discovery of SharePoint sites and content - SharePoint in Microsoft 365 | Microsoft Learn Contributors: Tania Menice
Avoiding Access Errors with SharePoint App-Only Access
To avoid persistent access errors like “403 Forbidden” when using SharePoint Online REST API with app-only permissions, it is essential to authenticate using a self-signed X.509 certificate rather than a client secret, as SharePoint requires certificate-based authentication for app-only access to ensure stronger security and validation. The solution involves generating a certificate, updating the Azure AD app with it, and using it to obtain access tokens, as demonstrated in PnP PowerShell examples and Microsoft documentation.
Locked out of Azure account for 5 months! Spent hours on phone, still no resolution! PLEASE HELP!!!
As per the title, back in April I somehow managed to lock myself out of my Azure portal. Typically to sign in my browser would auto-fill in the password field - for some reason that fateful day the auto-fill function didn't work. So I typed in what I believed to be the password, it wasn't. Annoyed, I typed in a few more passwords (even checked browser password manager to ensure I was typing the correct password) and finally locked myself out. Worse still, the email address that Microsoft wanted to send its verification code as a back-up contingency is no longer active (domain wasn't renewed and has since been bought). So Microsoft is sending a verification email to a dead email address... When I try to reset the password via Microsoft's questionnaire, once submitted I then get an automated email response back stating I haven't provided enough correct/relevant information, so the password can't be reset. I have long since lost any hope or faith in Microsoft rectifying this issue. Being courteous on the phone and apologising constantly is all well and good, but is only meaningful if there is a resolution. All that's happened is I've been passed around from one department to another and back again, before eventually being ghosted back in the summer. I have since opened another support ticket which is already winding its way around to ultimately leading me down another dead end. At this stage, all I want is for Microsoft to release my SQL database (my intellectual property) back to me. I am able to provide old invoices relating to my Azure account (when I was able to log in and download invoices!), as well as proof of ID to prove I am who I say I am - enough is enough! Please advise.Securing Data with Microsoft Purview IRM + Defender: A Hands-On Lab
Hi everyone I recently explored how Microsoft Purview Insider Risk Management (IRM) integrates with Microsoft Defender to secure sensitive data. This lab demonstrates how these tools work together to identify, investigate, and mitigate insider risks. What I covered in this lab: Set up Insider Risk Management policies in Microsoft Purview Connected Microsoft Defender to monitor risky activities Walkthrough of alerts triggered → triaged → escalated into cases Key governance and compliance insights Key learnings from the lab: Purview IRM policies detect both accidental risks (like data spillage) and malicious ones (IP theft, fraud, insider trading) IRM principles include transparency (balancing privacy vs. protection), configurable policies, integrations across Microsoft 365 apps, and actionable alerts IRM workflow follows: Define policies → Trigger alerts → Triage by severity → Investigate cases (dashboards, Content Explorer, Activity Explorer) → Take action (training, legal escalation, or SIEM integration) Defender + Purview together provide unified coverage: Defender detects and responds to threats, while Purview governs compliance and insider risk This was part of my ongoing series of security labs. Curious to hear from others — how are you approaching Insider Risk Management in your organizations or labs?Building a Custom Continuous Export Pipeline for Azure Application Insights
1. Introduction MonitorLiftApp is a modular Python application designed to export telemetry data from Azure Application Insights to custom sinks such as Azure Data Lake Storage Gen2 (ADLS). This solution is ideal when Event Hub integration is not feasible, providing a flexible, maintainable, and scalable alternative for organizations needing to move telemetry data for analytics, compliance, or integration scenarios. 2. Problem Statement Exporting telemetry from Azure Application Insights is commonly achieved via Event Hub streaming. However, there are scenarios where Event Hub integration is not possible due to cost, complexity, or architectural constraints. In such cases, organizations need a reliable, incremental, and customizable way to extract telemetry data and move it to a destination of their choice, such as ADLS, SQL, or REST APIs. 3. Investigation Why Not Event Hub? Event Hub integration may not be available in all environments. Some organizations have security or cost concerns. Custom sinks (like ADLS) may be required for downstream analytics or compliance. Alternative Approach Use the Azure Monitor Query SDK to periodically export data. Build a modular, pluggable Python app for maintainability and extensibility. 4. Solution 4.1 Architecture Overview MonitorLiftApp is structured into four main components: Configuration: Centralizes all settings and credentials. Main Application: Orchestrates the export process. Query Execution: Runs KQL queries and serializes results. Sink Abstraction: Allows easy swapping of data targets (e.g., ADLS, SQL). 4.2 Configuration (app_config.py) All configuration is centralized in app_config.py, making it easy to adapt the app to different environments. CONFIG = { "APPINSIGHTS_APP_ID": "<your-app-id>", "APPINSIGHTS_WORKSPACE_ID": "<your-workspace-id>", "STORAGE_ACCOUNT_URL": "<your-adls-url>", "CONTAINER_NAME": "<your-container>", "Dependencies_KQL": "dependencies \n limit 10000", "Exceptions_KQL": "exceptions \n limit 10000", "Pages_KQL": "pageViews \n limit 10000", "Requests_KQL": "requests \n limit 10000", "Traces_KQL": "traces \n limit 10000", "START_STOP_MINUTES": 5, "TIMER_MINUTES": 5, "CLIENT_ID": "<your-client-id>", "CLIENT_SECRET": "<your-client-secret>", "TENANT_ID": "<your-tenant-id>" } Explanation: This configuration file contains all the necessary parameters for connecting to Azure resources, defining KQL queries, and scheduling the export job. By centralizing these settings, the app becomes easy to maintain and adapt. 4.3 Main Application (main.py) The main application is the entry point and can be run as a Python console app. It loads the configuration, sets up credentials, and runs the export job on a schedule. from app_config import CONFIG from azure.identity import ClientSecretCredential from monitorlift.query_runner import run_all_queries from monitorlift.target_repository import ADLSTargetRepository def build_env(): env = {} keys = [ "APPINSIGHTS_WORKSPACE_ID", "APPINSIGHTS_APP_ID", "STORAGE_ACCOUNT_URL", "CONTAINER_NAME" ] for k in keys: env[k] = CONFIG[k] for k, v in CONFIG.items(): if k.endswith("KQL"): env[k] = v return env class MonitorLiftApp: def __init__(self, client_id, client_secret, tenant_id): self.env = build_env() self.credential = ClientSecretCredential(tenant_id, client_id, client_secret) self.target_repo = ADLSTargetRepository( account_url=self.env["STORAGE_ACCOUNT_URL"], container_name=self.env["CONTAINER_NAME"], cred=self.credential ) def run(self): run_all_queries(self.target_repo, self.credential, self.env) if __name__ == "__main__": import time client_id = CONFIG["CLIENT_ID"] client_secret = CONFIG["CLIENT_SECRET"] tenant_id = CONFIG["TENANT_ID"] app = MonitorLiftApp(client_id, client_secret, tenant_id) timer_interval = app.env.get("TIMER_MINUTES", 5) print(f"Starting continuous export job. Interval: {timer_interval} minutes.") while True: print("\n[INFO] Running export job at", time.strftime('%Y-%m-%d %H:%M:%S')) try: app.run() print("[INFO] Export complete.") except Exception as e: print(f"[ERROR] Export failed: {e}") print(f"[INFO] Sleeping for {timer_interval} minutes...") time.sleep(timer_interval * 60) Explanation: The app can be run from any machine with Python and the required libraries installed—locally or in the cloud (VM, container, etc.). No compilation is needed; just run as a Python script. Optionally, you can package it as an executable using tools like PyInstaller. The main loop schedules the export job at regular intervals. 4.4 Query Execution (query_runner.py) This module orchestrates KQL queries, runs them in parallel, and serializes results. import datetime import json from concurrent.futures import ThreadPoolExecutor, as_completed from azure.monitor.query import LogsQueryClient def run_query_for_kql_var(kql_var, target_repo, credential, env): query_name = kql_var[:-4] print(f"[START] run_query_for_kql_var: {kql_var}") query_template = env[kql_var] app_id = env["APPINSIGHTS_APP_ID"] workspace_id = env["APPINSIGHTS_WORKSPACE_ID"] try: latest_ts = target_repo.get_latest_timestamp(query_name) print(f"Latest timestamp for {query_name}: {latest_ts}") except Exception as e: print(f"Error getting latest timestamp for {query_name}: {e}") return start = latest_ts time_window = env.get("START_STOP_MINUTES", 5) end = start + datetime.timedelta(minutes=time_window) query = f"app('{app_id}')." + query_template logs_client = LogsQueryClient(credential) try: response = logs_client.query_workspace(workspace_id, query, timespan=(start, end)) if response.tables and len(response.tables[0].rows) > 0: print(f"Query for {query_name} returned {len(response.tables[0].rows)} rows.") table = response.tables[0] rows = [ [v.isoformat() if isinstance(v, datetime.datetime) else v for v in row] for row in table.rows ] result_json = json.dumps({"columns": table.columns, "rows": rows}) target_repo.save_results(query_name, result_json, start, end) print(f"Saved results for {query_name}") except Exception as e: print(f"Error running query or saving results for {query_name}: {e}") def run_all_queries(target_repo, credential, env): print("[INFO] run_all_queries triggered.") kql_vars = [k for k in env if k.endswith('KQL') and not k.startswith('APPSETTING_')] print(f"Number of KQL queries to run: {len(kql_vars)}. KQL vars: {kql_vars}") with ThreadPoolExecutor(max_workers=len(kql_vars)) as executor: futures = { executor.submit(run_query_for_kql_var, kql_var, target_repo, credential, env): kql_var for kql_var in kql_vars } for future in as_completed(futures): kql_var = futures[future] try: future.result() except Exception as exc: print(f"[ERROR] Exception in query {kql_var}: {exc}") Explanation: Queries are executed in parallel for efficiency. Results are serialized and saved to the configured sink. Incremental export is achieved by tracking the latest timestamp for each query. 4.5 Sink Abstraction (target_repository.py) This module abstracts the sink implementation, allowing you to swap out ADLS for SQL, REST API, or other targets. from abc import ABC, abstractmethod import datetime from azure.storage.blob import BlobServiceClient class TargetRepository(ABC): @abstractmethod def get_latest_timestamp(self, query_name): pass @abstractmethod def save_results(self, query_name, data, start, end): pass class ADLSTargetRepository(TargetRepository): def __init__(self, account_url, container_name, cred): self.account_url = account_url self.container_name = container_name self.credential = cred self.blob_service_client = BlobServiceClient(account_url=account_url, credential=cred) def get_latest_timestamp(self, query_name, fallback_hours=3): blob_client = self.blob_service_client.get_blob_client(self.container_name, f"{query_name}/latest_timestamp.txt") try: timestamp_str = blob_client.download_blob().readall().decode() return datetime.datetime.fromisoformat(timestamp_str) except Exception as e: if hasattr(e, 'error_code') and e.error_code == 'BlobNotFound': print(f"[INFO] No timestamp blob for {query_name}, starting from {fallback_hours} hours ago.") else: print(f"[WARNING] Could not get latest timestamp for {query_name}: {type(e).__name__}: {e}") return datetime.datetime.utcnow() - datetime.timedelta(hours=fallback_hours) def save_results(self, query_name, data, start, end): filename = f"{query_name}/{start:%Y%m%d%H%M}_{end:%Y%m%d%H%M}.json" blob_client = self.blob_service_client.get_blob_client(self.container_name, filename) try: blob_client.upload_blob(data, overwrite=True) print(f"[SUCCESS] Saved results to blob for {query_name} from {start} to {end}") except Exception as e: print(f"[ERROR] Failed to save results to blob for {query_name}: {type(e).__name__}: {e}") ts_blob_client = self.blob_service_client.get_blob_client(self.container_name, f"{query_name}/latest_timestamp.txt") try: ts_blob_client.upload_blob(end.isoformat(), overwrite=True) except Exception as e: print(f"[ERROR] Failed to update latest timestamp for {query_name}: {type(e).__name__}: {e}") Explanation: The sink abstraction allows you to easily switch between different storage backends. The ADLS implementation saves both the results and the latest timestamp for incremental exports. End-to-End Setup Guide Prerequisites Python 3.8+ Azure SDKs: azure-identity, azure-monitor-query, azure-storage-blob Access to Azure Application Insights and ADLS Service principal credentials with appropriate permissions Steps Clone or Download the Repository Place all code files in a working directory. 2. **Configure **app_config.py Fill in your Azure resource IDs, credentials, and KQL queries. 3. Install Dependencies pip install azure-identity azure-monitor-query azure-storage-blob 4. Run the Application Locally: python monitorliftapp/main.py Deploy to a VM, Azure Container Instance, or as a scheduled job. (Optional) Package as Executable Use PyInstaller or similar tools if you want a standalone executable. 2. Verify Data Movement Check your ADLS container for exported JSON files. 6. Screenshots App Insights Logs:\ Exported Data in ADLS: \ 7. Final Thoughts MonitorLiftApp provides a robust, modular, and extensible solution for exporting telemetry from Azure Monitor to custom sinks. Its design supports parallel query execution, pluggable storage backends, and incremental data movement, making it suitable for a wide range of enterprise scenarios.
Service Trust Portal no longer support Microsoft Account (MSA) access
Dear all, We need to access certain documents (i.e., SOC 2 or ISO 27xxx) on the https://servicetrust.microsoft.com/DocumentPage/d013b518-c1fe-462c-8124-de901f3b68dc. To download documents you need to be signed in first. However, when I click on "sign in" (using the same email/account as for our azure account) I get the error message "Service Trust Portal no longer support Microsoft Account (MSA) access." (see screenshot below). It seems that I am not the only one since other users had similar issues but they also could not find a solution (or at least it was not mentioned in their post): https://techcommunity.microsoft.com/t5/security-compliance-and-identity/cannot-login-to-service-trust-portal/m-p/3632978 I have been trying this now since more than a week and also created a support ticket (which has not been assigned to a support agent yet). It is quite cumbersome and I hope some of you could have an idea since getting these documents is quite crucial for us.Deep Dive: Insider Risk Management in Microsoft Purview
Hi everyone I recently explored the Insider Risk Management (IRM) workflow in Microsoft Purview and how it connects across governance, compliance, and security. This end-to-end process helps organizations detect risky activities, triage alerts, investigate incidents, and take corrective action. Key Phases in the IRM Workflow: Policy: Define rules to detect both accidental (data spillage) and malicious risks (IP theft, fraud, insider trading). Alerts: Generate alerts when policies are violated. Triage: Prioritize and classify alerts by severity. Investigate: Use dashboards, Content Explorer, and Activity Explorer to dig into context. Action: Take remediation steps such as user training, legal escalation, or SIEM integration. Key takeaways from my lab: Transparency is essential (balancing privacy vs. protection). Integration across Microsoft 365 apps makes IRM policies actionable. Defender + Purview together unify detection + governance for insider risk. This was part of my ongoing security lab series. Curious to hear from the community — how are you applying Insider Risk Management in your environments or labs?Custom Windows Server Standard VM on Azure: It Works, But Is It Licensing Compliant?
Hi everyone, I wanted to share a recent technical experience where I successfully created and deployed a Windows Server Standard VM on Azure using a fully custom image. I started by downloading the official Windows Server Standard Evaluation ISO. I created a Generation 2 VM in Hyper-V and completed the OS setup using the Desktop Experience edition. Once the configuration was done, I ran sysprep to generalize the image. After that, I converted the disk from VHDX to VHD in fixed format, which turned out to be a critical step because Azure does not accept dynamic disks. The resulting file was around 127 GB, so I uploaded it to a premium storage account container to ensure performance. From there, I created a Generation 2 image in Azure and deployed a new VM from it. I then activated the Standard edition with a valid product key. Everything worked smoothly, but I’m still unsure whether this method is fully compliant with Microsoft’s licensing policies. Specifically, I’m trying to understand if going from an Evaluation ISO to sysprep, upload, deployment, and activation in Azure is a valid and compliant scenario when not using BYOL with Software Assurance or a CSP license. Has anyone gone through this process or has any insights on the compliance aspect? Thanks in advance for any guidance or clarification.👉 Securing Azure Workloads: From Identity to Monitoring
Hi everyone 👋 — following up on my journey, I want to share how I approach end-to-end security in Azure workloads. - Identity First – Microsoft Entra ID for Conditional Access, PIM, and risk-based policies. - Workload Security – Defender for Cloud to monitor compliance and surface misconfigurations. - Visibility & Monitoring – Log Analytics + Sentinel to bring everything under one pane of glass. Through my projects, I’ve been simulating enterprise scenarios where security isn’t just a checklist — it’s integrated into the architecture. Coming soon: - A lab demo showing how Defender for Cloud highlights insecure configurations. - A real-world style Conditional Access baseline for Azure workloads. Excited to hear how others in this community are securing their Azure environments! #Azure | #AzureSecurity | #MicrosoftLearn | #ZeroTrust | #PerparimLabs
Azure IAM Report – Explicit Permissions Only
Hi all, Is anyone currently working on a request to generate a report of all IAM permissions across all Azure resources? My idea is to create a script that reports only explicitly assigned permissions at the Management Group, Subscription, Resource Group, or individual Resource level. However, I’m struggling to find a way to filter only explicit permissions at the Management Group level — everything seems to include inherited roles as well. Has anyone already solved this issue or found a workaround? Thanks in advance!
