Solution Guide
Detection-as-Code
Maintain Detections Like Software
Table of Content
A Modern Framework for Smarter SOCs
Detection-as-Code (DaC) is a software engineering approach to threat detection where detection logic is defined, managed, and deployed as version-controlled code. This enables security teams to deliver consistent, high-fidelity detections with repeatable workflows, automated testing, and cross-platform portability.
Built for modern, hybrid environments, Anvilogic operationalizes DaC with a platform-agnostic framework that integrates CI/CD, AI-powered agents, and modular deployment across SIEMs and data lakes.
60%
Improved ATT&CK Coverage
15K
Saved in Detection Engineering Hours
3X
More Efficient in Deploying Detections
90%
Reduction in Detection Deployment Time
Detection-as-Code Breakdown
Detection-as-Code (DaC) is a modern approach to building, managing, and scaling high-fidelity threat detections with the same rigor and agility as software development. It allows security teams to define detections as version-controlled code, automate testing and deployment, and collaborate more effectively across teams and environments.
With Anvilogic, Detection-as-Code is not just a methodology, it's implemented into its framework to powers efficient, adaptive, and AI-accelerated detection engineering across SIEMs and data lakes.
Build High-Fidelity Detections That Actually Work
Deliver more high-fidelity detections, faster.
Maintain Detections Like Software
Maintain healthier detections with version-controlled code
Maximize Atomic Detections
Correlate saved searches using a robust detection engineering framework.
Scale Coverage Without Scaling Headcount
DaC eliminates repetitive manual work and helps with analyst burnout.
Legacy Detection Lifecycle
Takes Days or Weeks...
Manual Research
Internet search
Social media
Threat intel feeds
Tracking & Feedback
Ticket MGMT
Bug trackers
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Develop, Test,
Deploy
Deploy
SIEM
Log Analytics
Manual Health & Performance Maintenance
WIKIS
DOCS
Metrics & Reporting
Dashboard Tools
BI
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Performed in Minutes
DevOps
Practices
Practices
Version Control
Treat detections as code artifacts managed in the platform.
Build, Test, Deploy
Collaboration
Enable peer reviews, documentation, and shared ownership.
AI-Powered
Automation
Integrate CI/CD to validate, test, and deploy detections reliably.
Mature & Improve
Portability
Write once and deploy to multiple platforms (SIEM, data lakes)
Key DaC Capabilities
Detection-as-Code Builder
Use Case:
Quickly author detections using familiar query languages like SPL, KQL, SQL, or Python.
Instead of:
It is a time-consuming process to build saved searches to cover detection gaps. Limited data schema skill sets make building query logic time and labor-intensive.
Now with Anvilogic, you can...
Drag-and-drop interface for building rules in SPL, KQL & SQL
Package into reusable modules and deploy across SIEMs, data lakes, and cloud-native stores
Auto-aligns to MITRE ATT&CK tactics
Supports atomic and behavioral detections
Enforce standards via schema validation, linting, and automated review
Package into reusable modules and deploy across SIEMs, data lakes, and cloud-native stores
Auto-aligns to MITRE ATT&CK tactics
Supports atomic and behavioral detections
Enforce standards via schema validation, linting, and automated review
Case Study: SAP
SAP is the biggest private cloud in the world, controlling data for 95 of the Forbes 100. For their security teams, managing the lifecycle of threat detections is a time-consuming and inefficient task, especially given that they deal with over 20,000 common vulnerabilities annually, along with zero-days, ransomware, and other threats.
SAP chose Anvilogic to incorporate automation and AI into their security incident detection to streamline this process. SAP can now:
- Centralize and unify visibility across various detection tools.
- Significantly reduce the time required for essential tasks.
- Create new detections and conduct research with incredible speed.
“Now our people can actually create new detections and research them with incredible speed. What we used to do in one year, now we can do in one or two months.”
Key DaC Capabilities
CI/CD for Detection Engineering
Use Case:
Manage detections as living artifacts, not one-off rules.
Instead of:
Iterative process that requires constant updating and tuning of logic as data formats change or if new telemetry is added makes it difficult to effectively scale and maintain high-quality detections.
Now with Anvilogic, you can...
Git-style versioning and audit trails
Change reviews and rollback support
Auto-test and deploy via CI/CD pipelines
Change reviews and rollback support
Auto-test and deploy via CI/CD pipelines
Bonus: Tuning Agents
Use AI to automate noisy rule detection and reduce alert fatigue.
Auto-suggest tuning improvements
Health scoring for deployed rules
Use AI to automate noisy rule detection and reduce alert fatigue.
Auto-suggest tuning improvements
Health scoring for deployed rules
Cross-Functional Collaboration, Codified
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Detection-as-Code isn’t just for detection engineers. It creates a shared language and operational model that empowers everyone across the security org to move faster, align better, and respond smarter. When detection logic is versioned, modular, and portable, team boundaries become bridges, not blockers.
Let’s break down the benefits by role.
Let’s break down the benefits by role.
👨💻 SOC Teams
- Ship detections faster with less manual effort
- Express logic modularly (YAML, Python) and deploy with confidence
- Collaborate via pull requests and reviews
- Reduce toil with automated testing and agentic health monitoring
- Improve signal-to-noise ratio for better response
📄 Security Architects
- Abstract detection logic from underlying platforms
- Normalize detection pipelines across hybrid infrastructure
- Enable hybrid/multi-cloud coverage without data centralization
- Standardize logic across business units and cloud tenants
- Govern logic with centralized version control and auditability
💼 CISOs & Security Leaders
- Quantify a true and more effective MITRE ATT&CK coverage report
- Quantify detection ROI and reduce reliance on vendor content
- Reduce detection debt
- Shift detection from expense center to strategic differentiator
“The ramp-up time to learn how to build a detection is greatly reduced with Anvilogic, especially for those not primarily in the security detection team.”
Key DaC Capabilities
Platform-Agnostic + Cross-Platform Deployment
Use Case:
Maintain logic once; execute it anywhere
Instead of:
Maintaining redundant rules in SPL for Splunk, KQL for Sentinel, SQL for Snowflake. Rewriting the same detection logic three different ways. Losing consistency across environments.
Now with Anvilogic, you can...
Minimize detection drift when migrating or operating across hybrid and multi-cloud environments
Deploy to Splunk, Sentinel, Databricks, Snowflake, or other queryable platforms
Leverage hundreds of out-of-the-box scenarios or easily create your own with DaC embedded framework
Ensure uniform detection quality and MITRE ATT&CK alignment across the stack
Automatically translate into native query formats (SPL, KQL, SQL, Python)
This platform-agnostic model allows teams to write once and run anywhere—keeping logic portable, maintainable, and tightly governed regardless of where your telemetry lives.
Anvilogic's low-code detection builder allows you to create advanced detections across data platforms like Splunk, Snowflake, and Azure without complexity. It can automatically translate natural language query requirements into SPL, SQL, and KQL search logic, empowering practitioners by lowering entry barriers and reducing reliance on specific logging platforms.
When higher-fidelity alerts are generated, Monte Copilot is ready to assist. Trained with Tier 3 Analyst expertise and access to common data sets and tools, Monte Copilot provides real-time answers for your triage needs. Transform slow, manual tasks into smarter, automated workflows with Monte Copilot's powerful functions, empowering your team to work more efficiently and effectively.
When higher-fidelity alerts are generated, Monte Copilot is ready to assist. Trained with Tier 3 Analyst expertise and access to common data sets and tools, Monte Copilot provides real-time answers for your triage needs. Transform slow, manual tasks into smarter, automated workflows with Monte Copilot's powerful functions, empowering your team to work more efficiently and effectively.
Why Detection-as-Code?
St. George’s University (SGU) is an international university and medical school committed to developing the intellectual capacity, creativity, and professionalism of its student body. Their SOC team faced challenges with SIEM implementation, including inadequate out-of-the-box correlation rules, difficulty adopting new detections and lack of version control for custom rules.
Traditional detection workflows are:
- Manual and error-prone: Detection logic is built ad hoc with little versioning or testing
- Difficult to scale or measure: No consistent cross-environment governance
Detection-as-Code changes that with:
- Accelerate delivery: Automates detection build, test, deploy loops
- Declarative logic: Expresses detections in structured formats (MITRE mapped, enrichment variables, etc)
- Increase precision: Tests against emulated adversary behavior; tunes with feedback loops
- Enable observability: Scores detection maturity across techniques, tools, and teams
“Anvilogic feels so natural with Splunk. We can customize detections really fast and get an alert out the door that works in our environment without a heavy lift. Because it’s not a black box, you can see the detection code and get ideas on how to build a better SPL search.”
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 Data Explorer, 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.
Triage
Triage Management
- Alert tuning, allow listing, triage observations.
- Alert triage assisted by the link analysis of the hunting graph.
- Triage across multiple hybrid cloud, cloud, and data lakes.
- Visualize alert attack pattern and timeline.
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.
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