The detection
engineering platform.
ATT&CK coverage measured from the telemetry you actually have, rules validated before they ship, and every change a Git change request.
Illustrative data — the layout, labels and states are Talon Studio's own.
The work is real. The tooling for it isn't.
Coverage dashboards show guesses, not evidence.
A green ATT&CK heatmap means nothing if the telemetry behind it never arrives. Most coverage numbers are wishful mapping, not measured fact.
Rules break without telling anyone.
Nothing alerts when a detection dies, so a broken rule looks exactly like a quiet network — until the incident it should have caught.
Detections live in SIEM consoles, not version control.
No diffs, no review, no rollback. The rules protecting your environment often have worse change management than your marketing site.
of MITRE ATT&CK techniques are covered by detections in production SIEMs — while the telemetry already ingested could support more than 90%.
CardinalOps, State of SIEM Detection Risk, 2025
of production SIEM rules are broken and will never fire — about one in eight, averaged over five years.
CardinalOps, State of SIEM Detection Risk, 2025
of simulated attacks raised an alert, although 54% of them were logged.
Picus, Blue Report, 2025
Coverage measured against your evidence, not a wish list
Atlas maps your real telemetry onto MITRE ATT&CK. Every cell is honest: covered by a deployed rule, deployable right now from your evidence, or not detectable until the data exists.
You also get a number you can benchmark — the industry-standard ≥1-rule-per-technique percentage, comparable against published enterprise averages — plus layer depth: which techniques are covered at two or more defensive layers (endpoint, network, identity, cloud), coverage that survives one blind sensor.
Amber cells are wins waiting: a library rule exists and your telemetry already supports it — adopt it and ship it through the release pipeline. Purple cells have a rule sitting in the library but no evidence to run it on yet — fix the data and they turn amber.
Overlay a threat group and see what you'd actually catch
Drop a threat group or campaign onto the matrix and Atlas narrows it to the techniques they actually use — then colours them with your real coverage. “Are we ready for APT28?” stops being a guess.
The same overlay works for campaigns and for the technique set behind a CVE — so you can answer the question the board is actually asking, instead of quoting a percentage across all of ATT&CK.
9 of APT28's 37 techniques are covered today and 11 more are deployable right now from telemetry you already have — that's the gap worth closing before the next report lands.
Trace every detection back to its evidence
Vantage crawls the SIEM and draws what it finds as one left-to-right graph: the pipeline upstream of it, the hosts shipping in, every store and dataset it holds, the models that normalize them, and the detections reading the far end. Follow any rule backwards to the exact telemetry that feeds it.
- Silent sources surface in amber — a host or sourcetype whose last event is older than the staleness window carries it on the node: data you pay to ingest but stopped receiving.
- Sourcetypes with no rules are your cheapest wins — every dataset is marked covered or not by whether a detection reads it, so the gaps are the ones already paid for.
- Deployed rules carry live health — a detection that has gone at-risk flags itself on the graph, at the end of the chain that feeds it.
Grade every rule already in your SIEM — including the ones you didn't write here
Most detection estates are full of rules that silently stopped working years ago. Rule Health grades every installed rule from live evidence — and when a signal can't be measured, it reads unknown, never healthy.
Prove detections fire — before you trust them
Replay runs Atomic Red Team and Stratus Red Team techniques against your environment and checks whether the matching detection actually fired. It's an efficacy signal, not a deploy gate — readiness lives in Monitor.
- Real attack techniques — sourced from the Atomic Red Team and Stratus Red Team catalogs.
- Fired or not — every run reports whether the detection observed events and triggered.
- Drift alerts — flags detections that used to fire and have since gone quiet.
Write it once. Validate it. Ship it everywhere.
Author detections in Sigma or your SIEM's native query language, version them in Git as change requests, and validate against your SIEM's real telemetry before they ever reach production.
- Portable by default — one rule, converted with pySigma to Splunk, Sentinel, Elastic or Chronicle on deploy.
- Validated like software — environment readiness gates every release, with Atomic Red Team runs as validation evidence and an org policy to make failures blocking.
- Git-backed — change requests, review and one-click rollback on every rule.
A release pipeline, not a save button
Detections never deploy on save. Merging a change request triggers the pipeline: gates check readiness, the app is packaged, and each SIEM lane deploys — with one-click rollback.
An AI detection engineer — with guardrails
Claw watches your signals — KEV drops, coverage gaps, failing validations — grounds itself in your real telemetry, and proposes detections. It never merges or deploys anything: every proposal lands as a change request a human reviews.
Every agent reasons over the same evolving graph
Claw's agents share a living knowledge graph linking your agents, tools, ATT&CK techniques, CVEs, detections, telemetry sources and every past run — so each proposal is grounded in what came before, not a blank context window.
Deploy to the SIEM you already run
A detection is authored once — in Sigma, or in your SIEM's own query language — converted with pySigma at the moment it ships, then deployed and rolled back live on any of the four. The rule stays in your Git, not inside one vendor's platform.
The Community Edition connects 1 SIEM and deploys to 1 target.
ENTERPRISESeveral at once, and moving between them without a rewrite.
Saved searches, correlation searches and the macros they lean on.
Analytics rules in KQL, with the entity mappings Sentinel expects.
Detection rules in EQL and Lucene, against the ECS fields you index.
YARA-L 2.0 rules, against the UDM your ingest already normalizes to.
What you get on day one
Not a platform you fill yourself. The library, the targets, the agents and the deployment are all in the box the day you run it.
You don't start from an empty library
Talon clones five public detection catalogues and indexes all of them into one table, pre-translated to every SIEM you target. Where a rule came from is a column, not a separate product — and importing one lands it as a change request, ready to validate and deploy.
The open community standard, in portable Sigma YAML.
Enterprise Security Content Update, and its Analytic Stories.
Analytics rule templates, with the entity mappings intact.
Chronicle's YARA-L 2.0 rules, written against the UDM.
FalconForce's research queries, tracked as they publish.
What you would use instead, and when to stay with it
Every team that reads this far already has an answer to detection engineering. Here is when that answer is the right one, and what Studio does differently.
Detection-as-code, built yourself
sigma-cli or pySigma, Git and a CI pipeline
STAY WITH IT IF
you have the platform engineering to build and run the pipeline, and coverage counted from your rules is enough.
WHAT'S DIFFERENT HERE
Studio is built on pySigma and brings the rest of that pipeline in one box: coverage scored from the telemetry your SIEM actually has, validation before release, rule health after it, and change requests with rollback.
Content marketplaces and translators
SOC Prime, Uncoder and similar
STAY WITH IT IF
you want a large feed of ready-made rules and translation into many query languages, and your team curates what it adopts.
WHAT'S DIFFERENT HERE
Studio indexes 9,000+ rules from five public catalogues as a starting point. A rule you adopt becomes a YAML file in your own Git, checked against your telemetry — yours if you leave.
Coverage analytics platforms
CardinalOps and similar
STAY WITH IT IF
you want a vendor to run coverage and rule-health scoring for you across a large SIEM estate.
WHAT'S DIFFERENT HERE
Studio does the scoring on your own hardware, from your SIEM's metadata, and turns a gap into a proposed detection in the same place — a change request a person approves.
Your SIEM vendor's own content
Splunk ES Content Update, Microsoft Sentinel Content hub, Elastic prebuilt rules
STAY WITH IT IF
you run one SIEM and plan to stay on it; its content is written for its own data model.
WHAT'S DIFFERENT HERE
Studio keeps detections in Git rather than inside one SIEM, so a second SIEM or a migration is a new deploy target instead of a rewrite — with Enterprise, since Community deploys to one.
Every step of detection engineering, unified
Stop stitching tools together. Talon Studio takes you from SIEM evidence to a validated, deployed detection — on one connected surface.
Talon Connect
Introspect your SIEM's indexes, sourcetypes, fields and CIM compliance to know exactly what you can detect.
Talon Monitor
Validate rules against your environment's real telemetry — and Atomic Red Team tests where one matches — before they ship.
Talon Atlas
Map every detection to MITRE ATT&CK and see the gaps that are one detection away from closed.
Talon Claw
An AI detection engineer that proposes rules, closes KEV gaps and learns your environment — governed by review.
One pipeline, from telemetry to deployed detection
Connect introspects your SIEMs, Forge authors detections as code, Monitor validates them against your data — then the release pipeline converts and deploys to your SIEM.
Automate the busywork — every step still reviewable
Trigger a flow on a schedule, a webhook or a platform event — a merged change request, a failed validation, a SOC alert — then chain read, reasoning and action nodes. Any node that would change something stages a draft change request — nothing merges or deploys on its own.
- Real triggers — schedule, webhook, merged change request, validation failure, pipeline failure, SOC alert.
- Branching logic — if/switch nodes route on real conditions, not just linear steps.
- Propose-only actions — write nodes stage a change request; a human still approves it.
Know what you can detect against what's being exploited
Talon Threat ranks CISA KEV and EPSS-scored CVEs, then checks each one against your real coverage — Live (deployed and running), Ready (deployable now), Blind (a rule exists but your telemetry can't see it) or Uncovered (no rule at all). Blind is deliberately distinguished from covered, so the score can't be inflated by rules that will never fire.
- Priority, not just severity — ranked by exploitation likelihood and ransomware use, not CVSS alone.
- Environment-aware — every CVE is checked against your real coverage, not a generic mapping.
- Paste a threat report — Talon extracts the TTPs it describes, diffs them against your live coverage, and drafts the missing detection as a change request. Nothing auto-deploys.
- Feeds Claw — gaps here are exactly what the Coverage Analyst agent proposes detections for.
Close the loop on every alert
With Enterprise, the notables your detections fire come home: into an analyst queue, mapped to the exact rule that produced them, worked as a case — and a false positive becomes a tuning change request in Forge.
Dispositions become detection telemetry — false-positive rate and volume feed straight back into Forge and Atlas.
Your security data stays isolated
Self-host in your own cloud or on your own hardware — your detections live in an environment only you control, never pooled with other customers. What does leave it, and when, is below.
Yours to run
Run the one-container appliance in your own infrastructure. The AI features send prompts only to the model provider you configure, with personal-data fields in SIEM results redacted — a built-in list, plus any you add. Point them at a local OpenAI-compatible endpoint and they never leave your network.
Encrypted at rest
SIEM tokens, AI provider keys and connection credentials are encrypted before they ever touch the database.
Licensing you can audit
A Community key is checked on your own server and is never activated or checked in. An Enterprise key — in development — activates online, then checks in daily (every six hours around its renewal date) with the key, this instance's id, the app version and a hostname label — nothing about usage, users or data. If Talon Labs cannot be reached, it keeps working until its own expiry date.
Content updates — SigmaHQ rules, MITRE ATT&CK, the CISA KEV list and the other public catalogues — and the check for a new release are downloads of public files. They send nothing about your detections, your data or your users.
Fits the rest of your stack, too
Beyond the SIEMs you deploy to, Studio connects to the Git host, ticketing and threat-intel tools your team already runs on.
No charge, as the Community Edition.
The whole detection workflow for 2 people, 1 SIEM and 1 deploy target, self-hosted, on the Community key that comes with your Talon Labs account — and it never contacts us. Enterprise is in development; the pricing page says what it will add.