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[Upcoming Session]: Maturing SecOps with Detection-as-Code. Join us November 21.
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Solution Guide



ANVILOGIC FOR MICROSOFT SENTINEL

Table of Content
1
Operationalize detection engineering across Azure
2
Expert-led detection engineering
3
Orchestrate KQL easily
4
Azure threat detection toolkit
MITRE ATT&CK detection packs for Azure
Latest trending threat coverage
Azure playbook collection
5
Use Case 1: Close detection gaps while maximizing the value of Sentinel
6
Use Case 2: Reduce alert fatigue with multi-stage attack correlation
7
Use Case 3: Automate rule tuning and maintenance with AI
8
Enhance existing Microsoft investments
9
Product architecture and features
10
Anvilogic for Sentinel Product Tour
Book a Demo

Share This Guide
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Table of contents
1
Operationalize detection engineering across Azure
2
Expert-led detection engineering
3
Orchestrate KQL easily
4
Azure threat detection toolkit
MITRE ATT&CK detection packs for Azure
Latest trending threat coverage
Azure playbook collection
5
Use Case 1: Close detection gaps while maximizing the value of Sentinel
6
Use Case 2: Reduce alert fatigue with multi-stage attack correlation
7
Use Case 3: Automate rule tuning and maintenance with AI
8
Enhance existing Microsoft investments
9
Product architecture and features
10
Anvilogic for Sentinel Product Tour
Book a Demo

Download PDF


Share this guide
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OPERATIONALIZE DETECTION ENGINEERING ACROSS YOUR AZURE ECOSYSTEM



Microsoft has firmly positioned itself as a cornerstone in data storage and
productivity, and since entering the SIEM market with the release of Sentinel,
it’s also become a major player in security strategies. Microsoft shops rely on
platforms like Log Analytics and Data Explorer because they offer a solid
foundation for monitoring, logging, and correlating data—creating an
interconnected ecosystem where asset monitoring and data management across
Microsoft products are tightly integrated.

However, while Microsoft excels in data ingestion, querying, and providing a
cohesive ecosystem, many organizations face challenges in scaling detection
engineering and optimizing threat detection rules. Detection engineers often
struggle to find the attacks that matter most due to several factors:

 * Noisy networks that are poorly managed and overwhelm with incidents.
 * Inefficient budget allocation on solutions lacking visibility in terms of
   discovery.
 * Inadequate data, such as SIEM capacity consumed by firewall logs.
 * Poor defensive posture hindering skilled talent acquisition capable of
   finding important attacks.

This is where Anvilogic steps in. Rather than moving away from Microsoft—which
isn’t a realistic option for most enterprises—we build on top of your existing
investment, enhancing detection capabilities, automating engineering workflows,
and simplifying threat hunting. Anvilogic transforms Microsoft’s foundation into
a powerful detection platform that closes critical gaps and delivers
high-fidelity security outcomes.

Anvilogic is taking detection engineering challenges head on and gaining
significant traction among large enterprises with advanced SOC teams like eBay
and PayPal, helping them streamline their detection engineering efforts—the most
critical focus highlighted by 60% of security professionals in the ESG Report.

This solution guide explains how Anvilogic streamlines detection engineering in
your Azure ecosystem. Explore our detection engineering key feature sets, our
three main use cases, and more.

Use the Table of Contents to find the topics you’re interested in.


Learn More

90%
Reduction in detection engineering lifecycle management time
Learn More

60%
Increase in priority technique coverage across MITRE ATT&CK


BRIDGING THE DETECTION ENGINEERING GAP WITH FORTUNE 500 PRACTITIONER EXPERTISE

Founded by former Fortune 500 practitioners, Anvilogic was built to give
detection engineers the tools they need to craft precise detections using a
Detection-as-Code framework tailored to unique business and threat priorities.
It stands as the only solution that seamlessly integrates with multiple SIEMs
and security technologies, and tackles the most complex areas of detection
engineering—areas that challenge even the most advanced Security Operations
Centers.




COMPANY LEADERSHIP & VISION
100+ YEARS SOC PRACTITIONER DNA




>50%
Employees SOC Practitioner Background


EASILY ORCHESTRATE POWERFUL KQL THREAT DETECTION

Although Sentinel has a powerful query language, it primarily focuses on
Microsoft data sources, which limits its ability to perform complex, multi-stage
correlations when it comes to non-Microsoft logs or external data sources. This
narrow scope means it lacks robust cross-platform correlation capabilities that
are necessary for building multi-dimensional detections across diverse datasets.
With our Custom Detection Builder, you can develop and deploy high-fidelity,
behavioral-based detections for your team's custom use cases in minutes across
your chosen data platforms and security technologies. It alleviates the need for
your team to be experts in SPL, SQL, and KQL, simplifying the complexities of
building and deploying threat detections.

Easily create, schedule, and manage KQL queries and detections across Microsoft
Sentinel, Azure Log Analytics, or Azure Data Explorer. Anvilogic seamlessly
integrates with other data repositories like Splunk, Snowflake, allowing you to
correlate raw events and alerts across multiple platforms. Search and analyze
raw events from hybrid or multi-cloud repositories to build robust,
multi-layered threat scenarios. This unified framework empowers you to create
high-fidelity detections with minimal coding, supported by an OpenAI chatbot for
enhanced efficiency and ease.

Have a lot of custom KQL already built out? You can seamlessly onboard your
existing KQL rules into Anvilogic to manage them all in one centralized place.
We let you enrich your content with your custom tags and use AI algorithms to
map your pre-existing content to the MITRE ATT&CK framework so you can easily
track ongoing coverage against it for program effectiveness.




SUPPORTED INTEGRATIONS



and more...


Customizing detection rules across disparate technologies with varying query
language skill is resource-intensive and slow. With Anvilogic’s
Detection-as-Code capabilities, teams can quickly create, modify, and deploy
detections, drastically reducing the time and effort required to implement new
threat detection rules—scaling at the speed required to keep up with today’s
evolving threat landscape. The DaC experience offers a user-friendly canvas with
drag-and-drop functionality to query raw events in Azure Sentinel, Data Explorer
or Log Analytics from within the Anvilogic platform and transform them into
automated threat detection queries.


KEY FEATURES

Efficiently collect and gather what you need in the format that you need to
start building your rule from your data set while bypassing the intricacies of
data parsing and normalization. The platform normalizes elements from your Azure
workspaces in place so you can focus on building your detections efficiently.

As you select tables in Azure, additional filtering and formatting options allow
you to refine your queries on the fly:

 * Code Block: Ideal for KQL pros, this feature lets you craft precise KQL hunts
   with pikes necessary to filter on elements. You can then test, search, and
   narrow down results with intuitive right-click selections.
 * Filter: This feature provides a workbench with dropdowns to easily select
   schema elements and refine KQL queries with filters like equals, does not
   equal, contains, and more. It helps you retrieve precisely what you need.
 * Group Events: To avoid duplicate alerts and reduce noise, this feature
   consolidates multiple rows into a single entry, making it easier to build,
   tag, and enrich detections for use in multi-stage scenarios covered later in
   this solution guide.
 * Inline Enrichment: Enrich data with assets, identities, and IP context
   inline, with minimal engineering overhead or ongoing maintenance, enabling
   streamlined correlation and advanced analysis.
 * Custom Tagging: Tag your use case with custom definitions, categories like
   rule type, domain, coverage, and data platform. Align with MITRE to track
   technique coverage across your security alerts.
 * Version Control & Audit History: All use case changes are tracked with
   side-by-side code views, making it easy to see updates as your use cases
   evolve. You can revert to previous versions anytime.






SEARCHING MADE SIMPLE

When you need to quickly search for specific information—whether to answer a
CISO’s question or extract a report—our new Search feature makes it easier than
ever. With a user-friendly GUI, you can effortlessly search your Azure data
sources. Filter by macros or specific data feeds without writing complex KQL.
Customize your searches with basic and advanced filtering options, using
selectable properties, time pickers, and multiple conditions to refine your
results.

You can also quickly retrieve and query previously defined views as needed,
referencing them at any time—especially if you frequently reach for a previously
customized view you have out running in production today. Alternatively, you can
select any imported data feeds to which Anvilogic has authenticated access. Both
options will be organized by data domain (e.g., Application, Network, Endpoint).

Easily navigate your options and make complex joins with guided table selection.
Analyze your search results with visual distributions over time to identify
trends, spikes, and anomalies. Easily export your results and attach logs
directly to cases—streamlining the workflow for analysts and meeting case
documentation requirements. This comprehensive insight empowers you to dig
deeper and easily make informed decisions.

Once you have your search results, leverage an AI Copilot assistant with a
ChatGPT-style interface to ask questions about a result. Or dig even deeper by
asking for guidance on how to investigate.
Monte Copilot is extensively trained in different personas across the SOC, so
you can scale your team and accelerate triage and response—no matter who’s
asking the question.





BUILD YOUR AZURE DEFENSE: YOUR THREAT DETECTION TOOLKIT

With our custom detection builder, you can easily import, test, deploy rules,
and execute threat hunts across Azure—but if you're unsure where to start, no
worries! The Anvilogic Forge has your back with a clutch Detection Armory.




1,200+ Pre-Built Detections for Sentinel
1,200+ Pre-Built Detections for Sentinel
1,200+ Pre-Built Detections for Sentinel

The Detection Armory offers a library of 1200+ pre-built, MITRE ATT&CK-mapped
detections that are ready to deploy, making it easy for customers to implement
advanced detection strategies within their existing Microsoft infrastructure. We
release weekly detections various TTPs targeting Microsoft Applications, using
machine learning to prioritize relevance. This helps you decide which detections
to deploy first, ensuring you efficiently close gaps and enhance your MITRE
ATT&CK coverage.




MITRE ATT&CK DETECTION PACKS FOR AZURE

Our team consistently releases new detection content packs unique to emerging
threats and trending issues. Each pack delivers 50+ targeted detections—or
Threat Identifiers—for Azure data feeds designed to pinpoint specific tactics
and techniques. Increase your coverage in just a few clicks by easily deploying
content directly to your Sentinel, Log Analytics, Fabric and Data Explorer
environments.






CLOSING CORRELATION GAPS WITH THE LATEST TRENDING THREATS

The Anvilogic Forge curates the latest trending Cyber Threat Intelligence (CTI)
reports from leading sources, extracts key threat actor TTPs, and maps them to
relevant detections and multi-stage attack scenarios on a weekly basis. These
curated insights are also ready for immediate deployment to Azure-connected data
feeds, optimized for frequency and accompanied by comprehensive guidance to help
operationalize the reports and content packs effectively.






THE AZURE PLAYBOOK COLLECTION FOR REAL-WORLD THREAT SCENARIOS

Anvilogic’s Detection Armory goes beyond offering detection packs and reports
with atomic rules. It also delivers advanced, multi-domain, and multi-stage
correlations—or Threat Scenarios, as we like to call them—all powered by our
robust rule engine. Our curated, pre-built, and CI/CD-tested Threat Scenario
content is designed for rapid deployment, allowing you to operationalize in just
minutes. This content was inspired by customer requests across different
industries and modeled after the latest emerging threats.

You can leverage Threat Scenarios for Azure from our Detection Armory, tuning
and modifying them as needed. However, we understand that many organizations
will need to build their own. With our low-code use case builder, your SOC can
easily create custom threat detection scenarios without the complexity of coding
and deployment. While Sentinel’s KQL is a powerful query language, it isn’t
optimized for complex detection engineering tasks that require advanced
correlation logic, such as chaining events across multiple data sources in real
time. This often leads to gaps in detection coverage and difficulty in
identifying sophisticated attack scenarios that span cloud and on-prem
environments. Integrating non-Microsoft logs & security vendor alerts can also
be cumbersome, which prevents security teams from leveraging the full spectrum
of data necessary for effective, multi-stage attack detections.



Customer Use Cases in Production
A Fortune 500 Investment Firm cut costs and improved detection workflows by
switching from Microsoft Sentinel to Azure Data Explorer (ADX), achieving a 30%
increase in MITRE ATT&CK detection coverage.

Crypto.com reduced detection engineering time by utilizing a low-code builder
for multi-stage detections that produced high-fidelity alerts across multiple
atomic detections, vendor alerts, and data platforms.
Use Case One


CLOSE DETECTION GAPS WHILE MAXIMIZING VALUE OF SENTINEL


Use Case:

Aligning business and threat priorities and determining which detections to
pursue.
Current Way:

It is difficult to prioritize which detections will actually protect your
environment with limited headcount, a piling backlog, and manual MITRE ATT&CK
mapping.


NOW WITH ANVILOGIC, YOU CAN...

 * Receive AI-powered recommendations that notify you on which KQL detections we
   have in the Armory that are relevant based on your available data platforms
   and threat priorities.
 * Visually understand your tactics, techniques and procedures (TTP) coverage
   against MITRE ATT&CK automatically.
 * Improve Alert Quality by driving cross domain correlation detections across
   Microsoft & non-Microsoft Data Feeds.
 * Save hundreds of hours researching KQL rules that align to your environment.



Use Case Two


REDUCE ALERT FATIGUE WITH MULTI-STAGE ATTACK CORRELATION


Use Case:

Building and correlating multiple adversarial techniques and advanced detections
without being a KQL, SPL, or SQL expert.
Current Way:

Atomic detections restrict detection to atomic events, causing noisy alerts.
Advanced correlations require complex query logic and deep schema knowledge.


NOW WITH ANVILOGIC, YOU CAN...

 * Build complex detection logic using a low-code builder that can correlate
   atomic events across multiple stages in an attack sequence.
 * Easily Correlate detections across IT Infrastructure domains.
 * Leverage hundreds of threat intelligence-driven scenarios tailored to your
   specific industry.
 * Automatically map detections to MITRE ATT&CK.



Use Case Three


AUTOMATE RULE TUNING AND MAINTENANCE WITH AI


Use Case:

Tuning noisy alerts and ensuring your integrations, data feeds, and detection
rules aren’t broken.
Current Way:

Dedicate one day a week to manually tune alerts and check for broken rules,
risking missed critical alerts due to overturned logic or data feed issues.


NOW WITH ANVILOGIC, YOU CAN...

 * Received AI-powered recommendations that automate tuning and notify you about
   integrations, data feeds, and rules that need a checkup as well as the steps
   to nurse them back to health.
 * Tune noisy alerts and remove false positives with a single click, instantly
   applying the necessary allowlisting and filtering adjustments.
 * Save hundreds of hours of manual troubleshooting and parsing faulty values.




AI Insights Feature Spotlight


FORTIFY YOUR FRONTLINES WITH AI-POWERED  INSIGHTS

Boost detection accuracy, fine-tune alerts, optimize data feeds, and jumpstart
hunting with suggested queries.
Read More



COMPLEMENTING EXISTING MICROSOFT INVESTMENTS

Organizations aren’t looking to abandon their Microsoft tools; they want to get
more out of them. Anvilogic acts as an technology force-multiplier, integrating
effortlessly into Microsoft environments, whether it’s augmenting Sentinel with
more effective detections or providing correlations across data sources like Log
Analytics, Azure Fabric and Data Explorer.


RISK OF DOING NOTHING

And while Microsoft Sentinel excels at covering its own, it overlooks
non-Microsoft products, leaving critical blind spots in your defenses. That’s
where Anvilogic comes in: we fill the gaps, cut through the noise, and reduce
the risk of threats going unnoticed. Because when it comes to protecting your
crown jewels, “good enough” just doesn’t cut it.


THE RESULT

By working in tandem with Microsoft, Anvilogic ensures customers get the best of
both worlds—leveraging Microsoft’s powerful security infrastructure while
enhancing it with Anvilogic’s advanced detection engineering capabilities. This
partnership empowers organizations to not just monitor, but proactively defend,
adapt, and respond to threats with unparalleled efficiency.


In short, Anvilogic doesn’t replace Microsoft—it supercharges it. That’s why our
customers can continue to rely on their existing Microsoft infrastructure while
gaining more value, coverage, and insight, closing detection gaps and staying
ahead of threats without disrupting their established security strategy.

Architecture and Product Features



ANVILOGIC ARCHITECTURE






PRODUCT FEATURES:


Detection

Detection Content (Anvilogic Armory)
 * Forge Threat Research delivering over 1000s of ready-to-deploy detections
   (updated weekly) in SPL, KQL, SQL.
 * Daily detections updated based on trending threats.
 * Premium Threat Scenarios & Cloud Detection Content Packs.
 * Hunting detection packs to detect anomalous behavior.


Detection Creation
 * Low-Code detection builder to create behavior pattern-based detections or
   risk based detection scenarios.
 * Import your pre-existing rules to be standardized across all alert data.
 * Frameworks, machine learning recommendations and documentation to help define
   testing (TTPs) all in one place.


Detection Management
 * Automated end-to-end detection lifecycle management.
 * Easy to clone/modify/deploy detections.
 * Use case documentation.
 * Automated maintenance.
 * Versioning & audit history of changes.
 * Parsing and normalization code management.

Continuous Maturity Scoring
 * End-to-end visibility of your SOC maturity based on data quality analysis,
   detection coverage across MITRE, and productivity metrics (ex. hunting, alert
   dwell time, etc.).
 * Measurable technique coverage and gap analysis.
 * Assessment validation testing integrated into maturity scoring framework.

AI-Insights
 * Hunting, Tuning, and Health Insights that continuously monitor your unique
   environment, escalate activity that requires attention, and remind you of
   crucial maintenance actions.
 * Hunting Insights delivered to help identify high-fidelity alerts and
   suspicious patterns across raw event logs.
 * Detection recommendations based on your industry threat.
 * Landscape, infrastructure, and MITRE ATT&CK coverage/gaps.
 * Data prioritization & recommendations based on your unique environment.
 * Automated Tuning recommendations to ensure your deployment is performing
   optimally.

Deployment Architecture
 * Licensing: annual subscription model based on the user count.
 * SaaS Deployment: Meta data, analytics, insights, audit logs, alerts,
   allowlisting, and enrichment stored in Anvilogic Alert Lake.
 * Ability to search, query data, and deploy detections across multiple SIEMs
   and/or cloud data lakes.
 * Able to automatically tag, normalize, and enrich detections before storage
   for optimal correlation.
 * Highly flexible, open API platform that integrates with many existing
   security technologies.

Data & Integrations
 * Supported Data Platforms: Splunk (On-Prem & Cloud), Azure Sentinel, Azure
   Data Explorer, Microsoft Fabric,  Azure Log Analytics, Snowflake (AWS, Azure,
   GCP).
 * SOAR Integrations: Torq, Tines, XSOAR, Swimlane, more.
 * Case Management Integrations: Jira, ServiceNow.
 * Security Vendor Integrations: Crowdstrike, Proofpoint, Palo Alto Cortex,
   Tanium, VMware Carbon Black, Microsoft Defender, StackRox, DarkTrace,
   SentinelOne, ReversingLabs, Hunters, Abnormal Security, and more.

Alert Correlation
 * We supply detections across multiple data repositories, allowing you to
   easily query different sources and centralize them for seamless correlation
   in one location.

Monte Copilot
 * SecOps Companion trained across various SOC personas for investigation &
   detection building assistance.
 * Access to common tools and data sets used by analysts for triage ex)
   VirusTotal, Shodan, IPInfo, and more.




OPERATIONALIZE DETECTION
ENGINEERING FOR YOUR AZURE
ECOSYSTEM


OPERATIONALIZE DETECTION
ENGINEERING FOR YOUR AZURE
ECOSYSTEM

Book a Demo
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