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Detection-as-Code Builder

Focus on the threat, not the syntax, with our low-code builder. It leverages Detection-as-Code (DaC) to provide a modern and flexible structure for writing and managing detections with software engineering best practices.

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Let's ask Monte Copilot!

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Monte Copilot is not only trained in expert-level triage but it's also fully versed in our platform documentation, to ensure optimal use.

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Designed by former Fortune 500 SOC practitioners, our Threat Identifier and Scenario framework enhances threat detection efficacy, reducing reliance on atomic detections that flood SOCs with noise and false positives.

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You can create Threat Identifiers to categorize and label specific activities or discrete events.

Hover over the elements for additional explanations.

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Easily track and manage them with customizable metadata tagging aligned to MITRE ATT&CK, custom definitions and risk scoring.

Test your detections in real-time as you build. ✨

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Easily input reasoning and track change history for detection logic updates.

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As versions evolve, compare changes side-by-side to monitor and manage your detections’ progression. Keep things organized and stay on top of your game!

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We take detection engineering to the next level by offering an innovative approach to crafting Threat Scenarios.

Our framework empowers you to combine Threat Identifiers together, constructing comprehensive multi-stage attack paths and enabling cross-platform data correlation.

A true differentiator that SIEMs alone struggle to achieve. ⭐

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You can build detection logic using chained Threat Identifiers mapped to MITRE TTPs and across various domains.

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Unify your SIEM and Data Lake Without Replacing Splunk

Threat detection is a growing challenge with the rapid expansion of the attack surfaces across disparate environments. It's unrealistic and expensive to send it all to a single centralized location, so it's often spread out across various locations and silos, but being able to turn your data into security insights and quickly respond to incidents and hunt threats remains critical.

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....with your existing Data Tech Stack to search, hunt, and implement detection logic for correlation across those data sets.

Are There Any Data Feeds That Are Not Going Into Splunk Today?

Do you have other security use cases that you struggle to detect because of it?

Data that was once unreachable and costly to consolidate we can help you store in Snowflake ❄️ at a fraction of the cost, offering you the chance to leverage it for detection and address MITRE gaps. 💡

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Illuminate Dark Data at 80% of the Cost

You don't need to rip and replace Splunk or Azure. We can offload your expensive logs, drop them into a Snowflake tenant, and get detection coverage by cross-correlating in hours rather than months at 80% of the cost of Sentinel and Splunk!

Check out our Splunk cost savings pricing calculator 🔗 to see for yourself!

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Our modular architecture enables multi-data platform correlations across all your data sources and vendor alerts, effectively reducing gaps, costs, and fulfilling your threat detection requirements.

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Measure Detection Progress

Continuously assess your SOC's readiness to detect trending threats and identify key improvement areas with adaptive maturity scoring.

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Once you connect your data platforms, Anvilogic maps your data feeds by type and category, assessing feed quality and coverage.

We offer AI-recommended suggestions to improve your feed score by tuning or adding missing data feeds to align with new rules.

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All our detections are enriched with MITRE ATT&CK metadata tagging so you can track your coverage against MITRE attack and pursue ongoing improvement of detection gaps.

Scroll down to explore the MITRE Coverage Map.

Our recommendation algorithm prioritizes detections by which MITRE techniques to deploy based on your active data feeds and priorities, helping you enhance coverage and close technique gaps.

Find the stars on the MITRE Coverage Map to deploy rules to drive impactful threat detection! ⭐

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AI-Powered Recommendations for Automation Workflows

Explore the Anvilogic homepage to discover daily AI-driven recommendations. Navigate across each insight to see how we can help you optimize your data feed health, automate tuning, and effectively close detection gaps.

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🚀 Let's start our journey by taking a look at ML-powered recommendations for new uses.

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Here's a curated Detection Pack we recommend deploying, along with the reasons of why you should.

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We customize recommendations tailored to the data feeds within your Splunk, Azure, and Snowflake platforms.

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We also provide tuning suggestions for all your active use cases, providing specific property values to allowlist to reduce alert volumes.

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