#microsoft-graph-api

[infydeva]

[General Availability] Microsoft Graph Rich Notifications

Microsoft Graph allows apps to subscribe to and receive change notifications for resources through different delivery channels. You can set up subscriptions to include the changed resource data (such as the content of a Microsoft Teams chat message or Microsoft Teams presence information) in change notifications. Change notifications that include the resource change data are called Rich…

[cyber-sec]

Hackers Use ClickFix Trick to Deploy PowerShell-Based Havoc C2 via SharePoint Sites

Source: https://thehackernews.com/2025/03/hackers-use-clickfix-trick-to-deploy.html

More info: https://www.fortinet.com/blog/threat-research/havoc-sharepoint-with-microsoft-graph-api-turns-into-fud-c2

[uegub]

Why Tableau is Essential in Data Science: Transforming Raw Data into Insights

Data science is all about turning raw data into valuable insights. But numbers and statistics alone don’t tell the full story—they need to be visualized to make sense. That’s where Tableau comes in.

Tableau is a powerful tool that helps data scientists, analysts, and businesses see and understand data better. It simplifies complex datasets, making them interactive and easy to interpret. But with so many tools available, why is Tableau a must-have for data science? Let’s explore.

1. The Importance of Data Visualization in Data Science

Imagine you’re working with millions of data points from customer purchases, social media interactions, or financial transactions. Analyzing raw numbers manually would be overwhelming.

That’s why visualization is crucial in data science:

Identifies trends and patterns – Instead of sifting through spreadsheets, you can quickly spot trends in a visual format.

Makes complex data understandable – Graphs, heatmaps, and dashboards simplify the interpretation of large datasets.

Enhances decision-making – Stakeholders can easily grasp insights and make data-driven decisions faster.

Saves time and effort – Instead of writing lengthy reports, an interactive dashboard tells the story in seconds.

Without tools like Tableau, data science would be limited to experts who can code and run statistical models. With Tableau, insights become accessible to everyone—from data scientists to business executives.

2. Why Tableau Stands Out in Data Science

A. User-Friendly and Requires No Coding

One of the biggest advantages of Tableau is its drag-and-drop interface. Unlike Python or R, which require programming skills, Tableau allows users to create visualizations without writing a single line of code.

Even if you’re a beginner, you can:

✅ Upload data from multiple sources

✅ Create interactive dashboards in minutes

✅ Share insights with teams easily

This no-code approach makes Tableau ideal for both technical and non-technical professionals in data science.

B. Handles Large Datasets Efficiently

Data scientists often work with massive datasets—whether it’s financial transactions, customer behavior, or healthcare records. Traditional tools like Excel struggle with large volumes of data.

Tableau, on the other hand:

Can process millions of rows without slowing down

Optimizes performance using advanced data engine technology

Supports real-time data streaming for up-to-date analysis

This makes it a go-to tool for businesses that need fast, data-driven insights.

C. Connects with Multiple Data Sources

A major challenge in data science is bringing together data from different platforms. Tableau seamlessly integrates with a variety of sources, including:

Databases: MySQL, PostgreSQL, Microsoft SQL Server

Cloud platforms: AWS, Google BigQuery, Snowflake

Spreadsheets and APIs: Excel, Google Sheets, web-based data sources

This flexibility allows data scientists to combine datasets from multiple sources without needing complex SQL queries or scripts.

D. Real-Time Data Analysis

Industries like finance, healthcare, and e-commerce rely on real-time data to make quick decisions. Tableau’s live data connection allows users to:

Track stock market trends as they happen

Monitor website traffic and customer interactions in real time

Detect fraudulent transactions instantly

Instead of waiting for reports to be generated manually, Tableau delivers insights as events unfold.

E. Advanced Analytics Without Complexity

While Tableau is known for its visualizations, it also supports advanced analytics. You can:

Forecast trends based on historical data

Perform clustering and segmentation to identify patterns

Integrate with Python and R for machine learning and predictive modeling

This means data scientists can combine deep analytics with intuitive visualization, making Tableau a versatile tool.

3. How Tableau Helps Data Scientists in Real Life

Tableau has been adopted by the majority of industries to make data science more impactful and accessible. This is applied in the following real-life scenarios:

A. Analytics for Health Care

Tableau is deployed by hospitals and research institutions for the following purposes:

Monitor patient recovery rates and predict outbreaks of diseases

Analyze hospital occupancy and resource allocation

Identify trends in patient demographics and treatment results

B. Finance and Banking

Banks and investment firms rely on Tableau for the following purposes:

✅ Detect fraud by analyzing transaction patterns

✅ Track stock market fluctuations and make informed investment decisions

✅ Assess credit risk and loan performance

C. Marketing and Customer Insights

Companies use Tableau to:

✅ Track customer buying behavior and personalize recommendations

✅ Analyze social media engagement and campaign effectiveness

✅ Optimize ad spend by identifying high-performing channels

D. Retail and Supply Chain Management

Retailers leverage Tableau to:

✅ Forecast product demand and adjust inventory levels

✅ Identify regional sales trends and adjust marketing strategies

✅ Optimize supply chain logistics and reduce delivery delays

These applications show why Tableau is a must-have for data-driven decision-making.

4. Tableau vs. Other Data Visualization Tools

There are many visualization tools available, but Tableau consistently ranks as one of the best. Here’s why:

Tableau vs. Excel – Excel struggles with big data and lacks interactivity; Tableau handles large datasets effortlessly.

Tableau vs. Power BI – Power BI is great for Microsoft users, but Tableau offers more flexibility across different data sources.

Tableau vs. Python (Matplotlib, Seaborn) – Python libraries require coding skills, while Tableau simplifies visualization for all users.

This makes Tableau the go-to tool for both beginners and experienced professionals in data science.

5. Conclusion

Tableau has become an essential tool in data science because it simplifies data visualization, handles large datasets, and integrates seamlessly with various data sources. It enables professionals to analyze, interpret, and present data interactively, making insights accessible to everyone—from data scientists to business leaders.

If you’re looking to build a strong foundation in data science, learning Tableau is a smart career move. Many data science courses now include Tableau as a key skill, as companies increasingly demand professionals who can transform raw data into meaningful insights.

In a world where data is the driving force behind decision-making, Tableau ensures that the insights you uncover are not just accurate—but also clear, impactful, and easy to act upon.

[774]

POP、IMAP、および SMTP AUTH 2020 年に、POP、IMAP、および SMTP AUTH の OAuth 2.0 サポートをリリースしました。 一部のクライアント アプリへの更新は、これらの認証の種類をサポートするように更新されています (たとえば、Thunderbird は、21Vianet によって動作するOffice 365を使用しているお客様向けではありません)。そのため、最新バージョンのユーザーは OAuth を使用するように構成を変更できます。 Outlook クライアントが POP と IMAP の OAuth をサポートする予定はありませんが、Outlook は MAPI/HTTP （Windows クライアント）とEWS （Mac 版 Outlook）を使用して接続することができます。 これらのプロトコルを使用して電子メールを送信、読み取り、またはその他の方法で処理するアプリを構築したアプリケーション開発者は、同じプロトコルを維持できますが、ユーザーに対してセキュリティで保護された先進認証エクスペリエンスを実装する必要があります。 この機能は、Microsoft ID プラットフォーム v2.0 の上に構築され、Microsoft 365 メール アカウントへのアクセスをサポートします。 社内アプリケーションがExchange Onlineで IMAP、POP、SMTP AUTH プロトコルにアクセスする必要がある場合は、OAuth 2.0 認証を実装する手順に従います。OAuth を使用して IMAP、POP、または SMTP 接続を認証します。 さらに、PowerShell スクリプト Get-IMAPAccesstoken.ps1 を使用して、共有メールボックスのユース ケースを含む簡単な方法で、OAuth を有効にした後に IMAP アクセスをテストします。 基本認証が 2022 年 10 月 1 日に完全に無効になった場合でも、SMTP AUTH は引き続き使用できます。 SMTP が引き続き利用可能になる理��は、プリンターやスキャナーなどの多くの多機能デバイスを先進認証を使用するように更新できないためです。 ただし、可能な場合は、SMTP AUTH で基本認証を使用しないようにすることを強くお勧めします。 認証されたメールを送信するためのその他のオプションには、Microsoft Graph API などの代替プロトコルの使用があります。

Exchange Online での基本認証の廃止 | Microsoft Learn

[xmanoel]

Tracing MS Graph SDK

Well, sometimes with the Microsoft Graph SDK I I feel like getting a glipse of the requests and responses send from/to the API.

And it is possible to add debugging by adding a HTTP interceptor.

Here is just a recipe on how I added it in case it helps you: https://gist.github.com/xmanoel/84828c86d03d3d4c2ff892a6e0ca69ba

[ascentinnovationsllc]

https://www.ascent365.com/blogs/migrate-ews-apps-to-microsoft-graph-for-exchange-online-in-d365-finance-and-operations/

Migrate EWS Apps to Microsoft Graph for Exchange Online in D365 Finance and Operations Table of Contents Share Migrate EWS Apps to Microsoft Graph for Exchange Online in D365 Finance and Operations Exchange Web Services (EWS) is a legacy protocol that has been in use since Exchange Server 2007. In August 2018, Microsoft announced that there won’t be any active investment in EWS APIs for Exchange Online. We recommend that you migrate your EWS apps that access Exchange Online to Microsoft Graph.

[theazure365hub]

Configure and Manage pronouns settings for an organization using the Microsoft Graph API

[mlmgigsoftware]

Why Do MLM Companies Need Software?

1. Complex Commission Structures

MLM businesses operate using various commission and bonus models. Manual calculation is time-consuming and error-prone. Software automates the process, ensuring accuracy and timely payouts.

2. User Management

With potentially thousands of users in a growing network, it’s critical to have an organized system for user data, genealogy trees, and performance tracking.

3. Compliance & Security

Regulatory compliance and data security are crucial in MLM. Custom software ensures these aspects are covered with audit logs, secure payment gateways, and privacy protection.

4. Real-Time Analytics

MLM software provides dashboards for real-time tracking of sales, recruitment, income, and overall network performance.

Key Features of MLM Software

1. Customizable Compensation Plans

MLM software supports various plans like:

Binary Plan

Unilevel Plan

Matrix Plan

Board Plan

Hybrid Plan

Australian and Monoline Plans

Flexibility to customize or combine these plans is essential.

2. E-Wallet Integration

Users and admins benefit from integrated e-wallets that support deposits, withdrawals, transfers, and transaction histories.

3. Genealogy Tree View

A graphical representation of the downline structure helps users understand their network and strategize better.

4. Automated Commission Calculations

Daily, weekly, or monthly commissions can be automatically calculated and disbursed according to company policies.

5. User and Admin Dashboards

Separate dashboards offer relevant insights and functionalities, such as new sign-ups, top performers, sales graphs, and activity logs.

6. Replicated Websites

For branding and recruitment, each distributor can have a personal website linked to the central system.

7. Multi-Currency and Multi-Language Support

To support international expansion, MLM software often includes multi-language interfaces and currency converters.

8. Mobile App Integration

Having mobile-friendly access or dedicated mobile apps enhances user engagement and accessibility.

Steps in MLM Software Development

1. Requirement Gathering

Understand the business model, compensation structure, and specific operational needs of the MLM company.

2. Plan Selection and Customization

Choose the appropriate MLM plan or a hybrid model based on business goals.

3. Software Architecture Design

Decide on the tech stack (e.g., Laravel, Node.js, React, MySQL) and software architecture—cloud-based or on-premises.

4. Development and Testing

Build the application with modular code, integrate third-party services, and conduct rigorous testing (unit, integration, user acceptance).

5. Deployment and Maintenance

After launching the software, continuous support and updates ensure scalability and bug resolution.

Challenges in MLM Software Development

1. Scalability

Handling thousands or millions of users requires a highly scalable backend system.

2. Data Security

With sensitive financial and personal data, encryption, role-based access control, and secure APIs are mandatory.

3. Regulatory Compliance

MLM is often scrutinized for unethical practices. The software must be developed in accordance with the legal frameworks of various countries.

4. Customization vs. Standardization

Balancing client-specific customization with the need to keep the core product standardized and maintainable is a common challenge.

Technologies Used in MLM Software

Frontend: React, Vue.js, Angular

Backend: Laravel, Node.js, Django

Databases: MySQL, PostgreSQL, MongoDB

Mobile: Flutter, React Native, Swift (iOS), Kotlin (Android)

Hosting: AWS, Google Cloud, Microsoft Azure

Security Tools: SSL, OAuth2, JWT, AES encryption

Benefits of Using MLM Software

Automation of repetitive tasks

Improved accuracy in calculations

Enhanced user experience with mobile/web dashboards

Better scalability with cloud integration

Transparency in transactions and reporting

Future Trends in MLM Software

1. Blockchain Integration

Ensures transparency and decentralization in transactions and commission tracking.

2. AI & Machine Learning

Can be used for lead scoring, network behavior prediction, and performance forecasting.

3. AR/VR for Training

MLM companies are beginning to use immersive technologies for onboarding and training.

4. Gamification

Increases user engagement by incorporating leaderboards, rewards, and levels.

5. Smart Contracts

Automating commissions using Ethereum-based smart contracts is being explored by progressive MLM startups.

Choosing the Right MLM Software Development Company

When selecting a developer or agency:

Check their experience with different compensation plans

Ask for live demos or case studies

Ensure post-deployment support

Verify security protocols

Consider cost versus scalability

Conclusion

MLM software development is at the heart of modern network marketing operations. It transforms the complexities of MLM into manageable, efficient systems that empower businesses to grow, engage users, and stay compliant. As technology continues to evolve, MLM software is becoming smarter, more transparent, and user-friendly—paving the way for the future of ethical and scalable network marketing.

www.mlmgig.com

[edbmails25]

Facing Compatibility Issues During Microsoft 365 Migration? Here's What You Need to Know

Microsoft 365 migration is never just a click-and-go process. Behind every successful move is a thorough compatibility check between systems, services, and user environments. If not done right, compatibility issues surface and disrupt everything from mailbox access to user authentication. These issues are more common than they should be, and they can derail your entire migration strategy.

Here’s a practical look at what causes these compatibility breakdowns and what steps you need to take to prevent them.

Legacy Systems That Don’t Meet Microsoft 365 Standards

Many organizations continue to operate with outdated infrastructure. Systems like Windows 7, older Outlook versions, or Exchange 2010 lack the protocols and security standards required by Microsoft 365. Without modernization, they create roadblocks during migration. For instance, a system that doesn’t support TLS 1.2 or Modern Authentication will fail to connect with Microsoft 365 services.

To prevent this, perform a full compatibility assessment of your OS, Exchange servers, and Outlook clients. Upgrade the environment or establish a hybrid setup that ensures continuity while you transition users.

Authentication Failures Due to Identity Conflicts

Identity and access management is a critical pillar in Microsoft 365. If your existing setup includes outdated AD FS configurations or incomplete Azure AD synchronization, users will face login failures, broken SSO, and token-related issues. Compatibility mismatches between your on-prem directory and cloud directory often go unnoticed until users can’t sign in after cutover.

Define your identity model well in advance. Whether you choose cloud-only, hybrid, or federated, validate it with pilot users. Ensure directory sync, UPN alignment, and conditional access policies are correctly applied.

Unsupported Add-ins and Custom Applications

Custom Outlook add-ins, CRM connectors, or VBA-based automations are often built around legacy environments. These integrations may fail in Microsoft 365 because they rely on outdated APIs or local server paths. Post-migration, users report missing features or broken workflows, which is not a mailbox problem but a compatibility one.

Catalog all active plugins and applications. Check vendor documentation for Microsoft 365 support. Transition to updated versions or re-develop legacy tools using supported APIs like Microsoft Graph.

PST and Archive Data That Can’t Be Imported

PST files from end-user systems or public folder archives frequently carry hidden corruption, non-compliant data formats, or unusually large attachments. These can cause import failures or lead to incomplete data availability after migration.

To avoid surprises, pre-scan PST files using tools that verify integrity. Break large PSTs into manageable sizes. Use modern utilities that support direct PST import with accurate folder mapping and duplicate prevention.

Email Clients and Mobile App Incompatibility

Not all email clients are built to support Microsoft 365. Legacy Android apps, IMAP clients, or older iOS Mail apps often lack support for OAuth or Modern Authentication. Once migrated, users might encounter repeated login prompts or full access loss.

Standardize supported apps in advance. Recommend and configure Outlook for mobile. Use device management policies to enforce security compliance. Disable access for non-compliant clients using conditional access in Microsoft 365 admin settings.

Loss of Mailbox Permissions and Calendar Access

Access issues post-migration are common when shared mailbox permissions or calendar delegation rights aren’t migrated properly. Users may suddenly lose visibility into shared mailboxes or receive errors when trying to access team calendars.

Before migrating, document all mailbox and folder-level permissions. After migration, reapply them using PowerShell scripts or a tool that automates permission preservation. Always validate shared access functionality with test users before expanding the migration to all users.

Conclusion

Compatibility issues don’t happen randomly during Microsoft 365 migrations. They are the result of incomplete planning or assumptions that legacy systems will integrate seamlessly with modern cloud environments. The only way to mitigate them is through comprehensive discovery, pre-validation, and the right migration tooling.

If you want to reduce risk and accelerate your migration with minimal disruption, consider using EdbMails Office 365 migration tool. It simplifies complex moves, retains all mailbox properties and permissions, supports hybrid and tenant-to-tenant scenarios, and ensures seamless migration across environments. It’s a trusted choice for IT teams who need control, flexibility, and reliability.

Additional links:

�� Export Microsoft 365 Mailbox to PST

👉 Move public folders to office 365

[dynamicscommunity101]

Why Is Azure App Registration Required for Your Apps?

Building scalable and secure apps in today's cloud-driven environment frequently necessitates a smooth interaction with cloud services. In order to fully utilize Microsoft Azure's robust platform for application deployment, management, and security, it is imperative to comprehend App Registration.

Your application may securely interface with Azure services like Microsoft Graph, SharePoint, Dynamics 365, and more using the app registration in Azure gateway. App registration is a crucial step in guaranteeing safe authentication and authorization, regardless of whether you're a developer creating a web application, a mobile solution, or a sophisticated enterprise-grade system.

What is Azure App Registration?

The process of registering an application with Azure Active Directory (Azure AD) is known as app registration. It enables Azure to identify your application and give it the necessary credentials and permissions, including a client ID, secret, and certificates.

By registering your app, you are effectively giving Azure permission to trust it, provide it access to APIs, and enforce identity-based security protocols like OpenID Connect or OAuth 2.0.

This comprehensive guide will teach you more about the procedure and its significance.

Why Is App Registration Necessary for Applications?

The following are the main justifications for why Azure app registration is essential:

1. Safe Identity Administration

Azure AD controls app credentials and user identities. By registering an app, you may employ industry-standard security protocols to make sure that only authorized users and apps can access your services.

2. Control of Access

Unauthorized data access can be decreased by configuring role-based access controls (RBAC), allocating permissions, and restricting access to resources and APIs.

3. Integration of APIs

Tokens can be requested by registered applications to access Azure AD-protected custom APIs or Microsoft APIs like Microsoft Graph, which simplifies development and integration.

4. Support for Single Sign-On (SSO)

Enable SSO in your application to improve security and streamline the user experience.

5. Analytics and Monitoring

Only registered apps have access to Azure's comprehensive logs and monitoring tools for tracking app performance, behavior, and access patterns.

6. Automation and Scalability

Scripts or programs like Terraform or Bicep can automate app registrations, which facilitates large-scale application deployment.

Practical Advice from Professionals

App Registration is not just a configuration task; it's a foundational security component for any intelligent or cloud-connected application, says AI specialist Lawrence Rufrano. Registration guarantees that everything takes place under a secure identity whether your AI system has to communicate with other services, store data securely, or access APIs.

Experts like Lawrence Rufrano stress the significance of appropriate identity and access management as cloud and AI technologies merge, especially for AI solutions that depend on cloud-based data and service orchestration.

In conclusion

App registration is essential if you're developing apps that will interface with Azure services. It guarantees that your application is safe, complies with regulations, and can utilize all of Azure's features.

[cybersecurityict]

Semantic Knowledge Graphing Market Size, Share, Analysis, Forecast, and Growth Trends to 2032: Transforming Data into Knowledge at Scale

The Semantic Knowledge Graphing Market was valued at USD 1.61 billion in 2023 and is expected to reach USD 5.07 billion by 2032, growing at a CAGR of 13.64% from 2024-2032.

The Semantic Knowledge Graphing Market is rapidly evolving as organizations increasingly seek intelligent data integration and real-time insights. With the growing need to link structured and unstructured data for better decision-making, semantic technologies are becoming essential tools across sectors like healthcare, finance, e-commerce, and IT. This market is seeing a surge in demand driven by the rise of AI, machine learning, and big data analytics, as enterprises aim for context-aware computing and smarter data architectures.

Semantic Knowledge Graphing Market Poised for Strategic Transformation this evolving landscape is being shaped by an urgent need to solve complex data challenges with semantic understanding. Companies are leveraging semantic graphs to build context-rich models, enhance search capabilities, and create more intuitive AI experiences. As the digital economy thrives, semantic graphing offers a foundation for scalable, intelligent data ecosystems, allowing seamless connections between disparate data sources.

Get Sample Copy of This Report: https://www.snsinsider.com/sample-request/6040 

Market Keyplayers:

Amazon.com Inc. (Amazon Neptune, AWS Graph Database)

Baidu, Inc. (Baidu Knowledge Graph, PaddlePaddle)

Facebook Inc. (Facebook Graph API, DeepText)

Google LLC (Google Knowledge Graph, Google Cloud Dataproc)

Microsoft Corporation (Azure Cosmos DB, Microsoft Graph)

Mitsubishi Electric Corporation (Maisart AI, MELFA Smart Plus)

NELL (Never-Ending Language Learner, NELL Knowledge Graph)

Semantic Web Company (PoolParty Semantic Suite, Semantic Middleware)

YAGO (YAGO Knowledge Base, YAGO Ontology)

Yandex (Yandex Knowledge Graph, Yandex Cloud ML)

IBM Corporation (IBM Watson Discovery, IBM Graph)

Oracle Corporation (Oracle Spatial and Graph, Oracle Cloud AI)

SAP SE (SAP HANA Graph, SAP Data Intelligence)

Neo4j Inc. (Neo4j Graph Database, Neo4j Bloom)

Databricks Inc. (Databricks GraphFrames, Databricks Delta Lake)

Stardog Union (Stardog Knowledge Graph, Stardog Studio)

OpenAI (GPT-based Knowledge Graphs, OpenAI Embeddings)

Franz Inc. (AllegroGraph, Allegro CL)

Ontotext AD (GraphDB, Ontotext Platform)

Glean (Glean Knowledge Graph, Glean AI Search)

Market Analysis

The Semantic Knowledge Graphing Market is transitioning from a niche segment to a critical component of enterprise IT strategy. Integration with AI/ML models has shifted semantic graphs from backend enablers to core strategic assets. With open data initiatives, industry-standard ontologies, and a push for explainable AI, enterprises are aggressively adopting semantic solutions to uncover hidden patterns, support predictive analytics, and enhance data interoperability. Vendors are focusing on APIs, graph visualization tools, and cloud-native deployments to streamline adoption and scalability.

Market Trends

AI-Powered Semantics: Use of NLP and machine learning in semantic graphing is automating knowledge extraction and relationship mapping.

Graph-Based Search Evolution: Businesses are prioritizing semantic search engines to offer context-aware, precise results.

Industry-Specific Graphs: Tailored graphs are emerging in healthcare (clinical data mapping), finance (fraud detection), and e-commerce (product recommendation).

Integration with LLMs: Semantic graphs are increasingly being used to ground large language models with factual, structured data.

Open Source Momentum: Tools like RDF4J, Neo4j, and GraphDB are gaining traction for community-led innovation.

Real-Time Applications: Event-driven semantic graphs are now enabling real-time analytics in domains like cybersecurity and logistics.

Cross-Platform Compatibility: Vendors are prioritizing seamless integration with existing data lakes, APIs, and enterprise knowledge bases.

Market Scope

Semantic knowledge graphing holds vast potential across industries:

Healthcare: Improves patient data mapping, drug discovery, and clinical decision support.

Finance: Enhances fraud detection, compliance tracking, and investment analysis.

Retail & E-Commerce: Powers hyper-personalized recommendations and dynamic customer journeys.

Manufacturing: Enables digital twins and intelligent supply chain management.

Government & Public Sector: Supports policy modeling, public data transparency, and inter-agency collaboration.

These use cases represent only the surface of a deeper transformation, where data is no longer isolated but intelligently interconnected.

Market Forecast

As AI continues to integrate deeper into enterprise functions, semantic knowledge graphs will play a central role in enabling contextual AI systems. Rather than just storing relationships, future graphing solutions will actively drive insight generation, data governance, and operational automation. Strategic investments by leading tech firms, coupled with the rise of vertical-specific graphing platforms, suggest that semantic knowledge graphing will become a staple of digital infrastructure. Market maturity is expected to rise rapidly, with early adopters gaining a significant edge in predictive capability, data agility, and innovation speed.

Access Complete Report: https://www.snsinsider.com/reports/semantic-knowledge-graphing-market-6040 

Conclusion

The Semantic Knowledge Graphing Market is no longer just a futuristic concept—it's the connective tissue of modern data ecosystems. As industries grapple with increasingly complex information landscapes, the ability to harness semantic relationships is emerging as a decisive factor in digital competitiveness.

About Us:

SNS Insider is one of the leading market research and consulting agencies that dominates the market research industry globally. Our company's aim is to give clients the knowledge they require in order to function in changing circumstances. In order to give you current, accurate market data, consumer insights, and opinions so that you can make decisions with confidence, we employ a variety of techniques, including surveys, video talks, and focus groups around the world.

Contact Us:

Jagney Dave - Vice President of Client Engagement

Phone: +1-315 636 4242 (US) | +44- 20 3290 5010 (UK)

[cyber-sec]

𝗪𝗲𝗲𝗸𝗹𝘆 𝗠𝗮𝗹𝘄𝗮𝗿𝗲 & 𝗧𝗵𝗿𝗲𝗮𝘁𝘀 𝗥𝗼𝘂𝗻𝗱𝘂𝗽 | 𝟭𝟬 𝗙𝗲𝗯 - 𝟭𝟲 𝗙𝗲𝗯 𝟮𝟬𝟮𝟱

1️⃣ 𝗙𝗜𝗡𝗔𝗟𝗗𝗥𝗔𝗙𝗧 𝗠𝗮𝗹𝘄𝗮𝗿𝗲 𝗘𝘅𝗽𝗹𝗼𝗶𝘁𝘀 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗚𝗿𝗮𝗽𝗵 𝗔𝗣𝗜 FINALDRAFT is targeting Windows and Linux systems, leveraging Microsoft Graph API for espionage. Source: https://www.elastic.co/security-labs/fragile-web-ref7707

2️⃣ 𝗦𝗸𝘆 𝗘𝗖𝗖 𝗗𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗼𝗿𝘀 𝗔𝗿𝗿𝗲𝘀𝘁𝗲𝗱 𝗶𝗻 𝗦𝗽𝗮𝗶𝗻 𝗮𝗻𝗱 𝗧𝗵𝗲 𝗡𝗲𝘁𝗵𝗲𝗿𝗹𝗮𝗻𝗱𝘀 Four distributors of the criminal-encrypted service Sky ECC were arrested in Spain and the Netherlands. Source: https://www.bleepingcomputer.com/news/legal/sky-ecc-encrypted-service-distributors-arrested-in-spain-netherlands/

3️⃣ 𝗔𝘀𝘁𝗮𝗿𝗼𝘁𝗵: 𝗡𝗲𝘄 𝟮𝗙𝗔 𝗣𝗵𝗶𝘀𝗵𝗶𝗻𝗴 𝗞𝗶𝘁 𝗧𝗮𝗿𝗴𝗲𝘁𝘀 𝗠𝗮𝗷𝗼𝗿 𝗘𝗺𝗮𝗶𝗹 𝗣𝗿𝗼𝘃𝗶𝗱𝗲𝗿𝘀 The Astaroth phishing kit is used to bypass 2FA and steal credentials from Gmail, Yahoo, AOL, O365, and third-party logins. Source: https://slashnext.com/blog/astaroth-a-new-2fa-phishing-kit-targeting-gmail-yahoo-aol-o365-and-3rd-party-logins/

4️⃣ 𝗥𝗮𝗻𝘀𝗼𝗺𝗛𝘂𝗯 𝗕𝗲𝗰𝗼𝗺𝗲𝘀 𝟮𝟬𝟮𝟰’𝘀 𝗧𝗼𝗽 𝗥𝗮𝗻𝘀𝗼𝗺𝘄𝗮𝗿𝗲 𝗚𝗿𝗼𝘂𝗽 RansomHub overtook competitors in 2024, hitting over 600 organisations worldwide. Source: https://www.group-ib.com/blog/ransomhub-never-sleeps-episode-1/

5️⃣ 𝗕𝗮𝗱𝗣𝗶𝗹𝗼𝘁 𝗖𝗮𝗺𝗽𝗮𝗶𝗴𝗻: 𝗦𝗲𝗮𝘀𝗵𝗲𝗹𝗹 𝗕𝗹𝗶𝘇𝘇𝗮𝗿𝗱 𝗧𝗮𝗿𝗴𝗲𝘁𝘀 𝗚𝗹𝗼𝗯𝗮𝗹 𝗡𝗲𝘁𝘄𝗼𝗿𝗸𝘀 The Seashell Blizzard subgroup runs a multiyear global operation for continuous access and data theft. Source: https://www.microsoft.com/en-us/security/blog/2025/02/12/the-badpilot-campaign-seashell-blizzard-subgroup-conducts-multiyear-global-access-operation/

Additional Cybersecurity News:

🟢 𝗔𝗽𝗽𝗹𝗲 𝗙𝗶𝘅𝗲𝘀 𝗔𝗰𝘁𝗶𝘃𝗲𝗹𝘆 𝗘𝘅𝗽𝗹𝗼𝗶𝘁𝗲𝗱 𝗭𝗲𝗿𝗼-𝗗𝗮𝘆 Apple patches a critical zero-day vulnerability affecting iOS devices. Source: https://www.techspot.com/news/106731-apple-fixes-another-actively-exploited-zero-day-vulnerability.html

🟠 𝗝𝗮𝗽𝗮𝗻 𝗜𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝗲𝘀 "𝗔𝗰𝘁𝗶𝘃𝗲 𝗖𝘆𝗯𝗲𝗿 𝗗𝗲𝗳𝗲𝗻𝗰𝗲" 𝗕𝗶𝗹𝗹 Japan is moving towards offensive cybersecurity tactics with a new legislative push. Source: https://www.darkreading.com/cybersecurity-operations/japan-offense-new-cyber-defense-bill

🔴 𝗖𝗿𝗶𝘁𝗶𝗰𝗮𝗹 𝗡𝗩𝗜𝗗𝗜𝗔 𝗔𝗜 𝗩𝘂𝗹𝗻𝗲𝗿𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗗𝗶𝘀𝗰𝗼𝘃𝗲𝗿𝗲𝗱 A severe flaw in NVIDIA AI software has been discovered, enabling container escapes. Source: https://www.wiz.io/blog/nvidia-ai-vulnerability-deep-dive-cve-2024-0132

[gook54-blog]

Specialist AI used in intelligence analytics by agencies

AI is extensively used by intelligence agencies for profiling and image analysis, with tools ranging from facial recognition to behavioral prediction. Here’s a breakdown of how it works and what technologies are used:

1. Facial Recognition & Biometric Matching

Tools Used: Clearview AI, Amazon Rekognition, Microsoft Azure Face API, NEC NeoFace.

Function: Identifies individuals from photos, surveillance footage, or social media; matches faces against government databases (e.g., passport, driver's license, mugshots).

Use Cases: Counterterrorism, border control, tracking persons of interest.

2. Emotion & Microexpression Analysis

AI Capability: Detects facial expressions, voice stress, body language to infer mood, truthfulness, or potential for violence.

Vendors/Tools: Affectiva, Kairos, Realeyes, HireVue (also used in HR).

Agencies may use: Custom systems built by DARPA, NSA, or military contractors.

3. Behavioral Profiling

Methods: Aggregates data from digital footprints (social media, search history, location data) to build personality and risk profiles.

Tech Stack: Natural Language Processing (NLP), sentiment analysis, psychological modeling (OCEAN model), predictive analytics.

Tools: Palantir Gotham, IBM i2 Analyst’s Notebook, custom NSA profiling systems.

4. Object & Scene Recognition in Images

Capabilities: Detects weapons, gatherings, vehicles, symbols (e.g., gang tattoos, terrorist insignia).

Tool Examples: Google Cloud Vision AI, military-grade image classifiers developed under projects like Project Maven (US DoD).

Used In: Satellite image analysis, battlefield intelligence, riot prediction.

5. Deepfake Detection & Generation

Use: Identifies manipulated content or, conversely, generates synthetic personas or decoy videos.

Agencies Concerned: FBI, CIA, GCHQ, Mossad.

Tools: Sensity AI, Deepware Scanner, internally developed neural nets.

6. Social Network Mapping

Purpose: Maps relationships and influence webs from photos, metadata, tagged content.

Example: Using AI to infer hierarchy in terror cells from group photos.

Tech: Graph analytics + image recognition (e.g., linking people seen in the same images or events).

7. Real-Time Surveillance

Cities & Public Spaces: AI used in smart cities and fusion centers for mass surveillance and automated alerts.

China's SkyNet system is the most advanced publicly known example.

Known classified projects or contractor names (e.g., Booz Allen, Raytheon) involved in these systems!

[sranalytics50]

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[y2fear]

Microsoft launches usage reporting for Microsoft Graph API