Anvilogic

Overview

Anvilogic solves a problem that every SOC team knows but few talk about openly: your SIEM detection rules are a disaster. Half are defaults you never tuned. A quarter were written by analysts who left years ago and nobody understands the logic. The rest have coverage gaps you've been meaning to map to MITRE ATT&CK since last year's planning meeting. Anvilogic sits on top of your SIEM — whichever one you run — and brings structure, AI-assisted management, and automated testing to the chaos of detection engineering.

The company was founded in 2019 by former Splunk engineers who understood that the detection content problem isn't a SIEM problem — it's a detection engineering workflow problem. Anvilogic is SIEM-agnostic by design, working across Splunk, Microsoft Sentinel, Google Chronicle, Snowflake, Amazon Security Lake, and others. This isn't a SIEM replacement; it's a detection management layer that makes whatever SIEM you already own more effective. The platform uses AI to map existing detections to MITRE ATT&CK, identify coverage gaps, recommend detection content, and validate that your rules actually fire when they should.

The competitive field for detection engineering tooling is still relatively thin. SOC Prime, Sigma, and individual SIEM vendors' built-in content management are the closest comparisons, but none of them combine the SIEM-agnostic deployment, AI-assisted coverage analysis, and automated detection validation that Anvilogic offers in a single platform. It's carving out a category that didn't really exist three years ago.

How It Works

Anvilogic connects to your SIEM via API and ingests your existing detection rules. The AI engine analyzes each rule, classifies it by the MITRE ATT&CK technique it's designed to detect, and maps your entire detection library against the ATT&CK framework. This produces a coverage heatmap that shows you — with uncomfortable clarity — which techniques you're detecting, which you're partially detecting, and which you have zero coverage for. In our experience, the gaps are always more extensive than anyone expects. Teams that believe they have solid detection coverage typically discover they're covering 30–40% of relevant ATT&CK techniques, and some of those detections haven't been tested or updated in months.

The platform maintains a curated detection content library with rules mapped to ATT&CK techniques, written in Anvilogic's abstraction format and deployable to any supported SIEM. When the coverage analysis identifies gaps, Anvilogic recommends specific detections from its library to fill them, prioritized by the threat intelligence relevant to your industry. The AI assists in translating these detection rules into the query language of your specific SIEM — SPL for Splunk, KQL for Sentinel, SQL for Snowflake — handling the syntactic differences so that the detection logic is consistent regardless of where it runs.

The detection validation feature — what Anvilogic calls purple team simulation — is where the platform goes beyond management into operational assurance. Anvilogic can trigger simulated attack behaviors that should activate specific detections and verify whether the expected alerts actually fire. If a detection rule is supposed to catch a suspicious PowerShell execution pattern and the simulation triggers that exact pattern without generating an alert, you know you have a problem — whether it's a data source gap, a parsing issue, a threshold misconfiguration, or a rule that looked good on paper but doesn't work in your environment. Most SOC teams know they should be validating their detections. Almost none have the tooling or time to do it systematically.

For organizations running multiple SIEMs — which is more common than anyone admits, often due to mergers, regional requirements, or migration projects — Anvilogic provides a single management plane for detection content across all of them. Write or modify a detection once, deploy it to Splunk in one environment and Sentinel in another, and manage both from a unified interface. This portability also provides strategic flexibility if you're considering a SIEM migration: your detection content isn't locked into one vendor's query language.

What We Liked

The ATT&CK coverage heatmap produced an immediate, uncomfortable, and extremely useful picture of our detection posture. We thought we had reasonable coverage. The heatmap showed us we were detecting initial access and execution techniques fairly well, had patchy coverage for persistence and privilege escalation, and had almost nothing for defense evasion and collection techniques. That visualization became the basis for our quarterly detection engineering roadmap — for the first time, we had a data-driven answer to "what should we build detections for next?" instead of reacting to whatever the latest threat report mentioned.

Detection validation changed our confidence level in our alert pipeline. Before Anvilogic, we had a detection rule for Kerberoasting that we assumed worked because we'd written it to match the known patterns. When Anvilogic's purple team simulation triggered a Kerberoasting attack, the alert didn't fire. The issue: a field mapping change in our SIEM data model from three months earlier had broken the rule silently. Nobody noticed because nobody was testing it. We found similar silent failures in about 15% of our detection rules. That's a terrifying number, and we wouldn't have known without systematic validation.

The SIEM portability is more than a theoretical benefit for us because we're in the middle of migrating from Splunk to Microsoft Sentinel. Writing detections in Anvilogic's abstraction layer means we don't have to rewrite hundreds of SPL queries in KQL — the platform handles the translation. The detection logic and tuning carry over, which is saving our team an estimated 3-4 months of manual migration work. Even if you're not migrating SIEMs today, having your detection content in a portable format is insurance against future platform changes.

The surprise: Anvilogic's detection content recommendations aren't just generic ATT&CK technique matching. The platform factors in your industry vertical and published threat intelligence to prioritize which gaps matter most. For our financial services environment, it prioritized detection rules for techniques commonly used by FIN7 and FIN12 threat groups over generic ATT&CK coverage, which was a smarter use of our limited detection engineering time than trying to achieve universal coverage.

What Fell Short

Adding another management layer on top of your SIEM introduces real complexity. When a detection doesn't fire during an actual incident, you now have to debug at two levels: is the issue in Anvilogic's rule logic and translation, or in the SIEM's data ingestion, field mapping, or query execution? We had a few situations where Anvilogic-deployed detections behaved differently than expected because of SIEM-specific quirks — field name differences, data type mismatches, or performance-related query limitations — that the abstraction layer didn't fully account for. The detection portability between SIEMs is real, but "write once, deploy anywhere" overstates how much tuning is still needed per environment.

Anvilogic is a younger company competing against the detection content ecosystems that SIEM vendors have built over decades. Splunk's ES content library, Sentinel's analytics rules from Microsoft Research, and Chronicle's curated detections from Google's Mandiant team are all substantial — and they're optimized for their respective platforms in ways that a SIEM-agnostic tool can't always match. Anvilogic's content library is growing but doesn't yet have the depth of the largest vendor libraries. For niche detection use cases, you may still need to supplement with SIEM-native content.

The documentation and self-service resources are still catching up with the product's capabilities. We found ourselves relying on Anvilogic's support team for questions that should have been answerable from documentation. For a platform that targets experienced detection engineers, the onboarding materials assume less technical sophistication than the actual user base has, while the advanced documentation doesn't cover edge cases thoroughly enough. This is a maturity issue that should improve over time, but it's worth noting if you're evaluating today.

Pricing and Value

Enterprise pricing is not published and is based on the size of the SOC team and the number of connected SIEM environments. From industry conversations, expect annual contracts in the range of $50K–$150K depending on scale. The value calculation depends on how you quantify detection engineering efficiency: if Anvilogic saves one detection engineer 10 hours per week on rule management, coverage mapping, and validation — which is a reasonable estimate based on our experience — that's a meaningful return on a mid-five-figure investment. The SIEM migration portability benefit is harder to quantify upfront but can represent hundreds of thousands of dollars in avoided re-engineering costs during a platform transition.

Who Should Use This

SOC teams with dedicated detection engineering resources who are already running a SIEM and want to improve the quality, coverage, and reliability of their detection content. Organizations with 5+ detection engineers will get the most operational value. Teams planning or executing a SIEM migration should evaluate Anvilogic for the portability benefit alone. Security programs that need to demonstrate detection coverage to auditors, boards, or regulators will value the ATT&CK mapping and validation reporting. Not a good fit for small SOCs without dedicated detection engineers — the tool assumes a level of detection engineering maturity that smaller teams may not have yet.

The Bottom Line

Detection engineering is the most important security discipline that most organizations still do poorly. Not for lack of talent or effort, but for lack of tooling. Anvilogic is the first product we've seen that treats detection engineering as a disciplined practice with proper management, testing, and continuous improvement — rather than a collection of ad-hoc queries maintained in a wiki page and hope. It won't replace your SIEM, it won't write all your detections for you, and it adds management overhead you need to account for. But if you're serious about knowing whether your detections actually work, nothing else on the market does what Anvilogic does.