The three layers of a cyber risk program
It helps to separate a cyber risk program into three layers. The telemetry layer collects what is actually happening on your endpoints, servers, containers and code. The analysis layer turns that raw telemetry into meaning — deduplication, correlation, detection, exposure ranking and risk quantification. The governance layer turns meaning into accountability — evidence, control mapping, compliance status and reporting to executives.
The expensive assumption is that every layer demands premium commercial licensing. In practice, the layers can be sourced independently, and the telemetry layer — usually the most costly in a commercial stack — is where open-source has become genuinely enterprise-grade.
Wazuh as the open telemetry layer
Wazuh is a mature, open-source security platform that covers a surprising amount of the telemetry layer on its own. Its agents provide host-based intrusion detection, log data analysis, file integrity monitoring, rootkit and anomaly detection, vulnerability detection against installed packages, and security configuration assessment against benchmarks. Deployed across a fleet, it produces a steady stream of the endpoint and log telemetry that a commercial EDR would otherwise supply.
Around Wazuh you can add open scanners for the gaps: Nuclei for web and network vulnerability templates, Trivy for container and dependency scanning, Semgrep for static code analysis. Together they give a small team broad coverage — endpoint, web, container, code and configuration — without a single premium license.
A neutral layer that treats open-source as first-class
Telemetry alone is not a program — it is raw material. The value comes when it is normalised, correlated and turned into decisions, and that is the job of a vendor-neutral risk and GRC layer. The key property is neutrality: the platform is designed to connect to whatever produces the data and does not care whether a finding came from a six-figure commercial scanner or an open-source one.
GeneSecure can use Wazuh and open scanner output as a low-cost data source, normalising every finding into one shared model of assets, identities and findings, and labelling each record with its provenance so real telemetry is never confused with sample or simulated data. From that normalised model it adds the layers a lean team would otherwise go without: correlation into tracked cases, exposure ranked by reachability to critical assets and by exploitability signals like CISA KEV and EPSS, and cyber risk expressed in financial terms.
Governance without the enterprise price tag
The governance layer is where an open-only stack usually falls short, and where the neutral layer earns its place. The same normalised findings feed compliance evidence, so a control can be mapped once and evidenced from live data across frameworks like SOC 2 and ISO 27001. Vendor cyber risk, exceptions and remediation live in the same system, and board-ready reporting draws from the same source rather than a separate spreadsheet.
This is the difference between telemetry and a program. Wazuh and open scanners tell you what is happening; the neutral layer turns that into ranked exposure, financial risk, auditor-ready evidence and a board report — the accountability that a security leader is actually judged on.
Who this is for, and its trade-offs
This model suits lean security teams, cost-conscious mid-market organisations, and MSSPs standing up an affordable managed offering for smaller clients. It delivers a real program — not a toy — because the intelligence and governance are enterprise-grade even when the telemetry is open-source.
The honest trade-offs are operational. Open-source telemetry means you run and tune the agents and scanners yourself; the coverage and quality depend on that discipline, and on the depth of the connectors feeding the neutral layer. The right way to think about it is that open-source and commercial are not opposites: use open where it is strong (telemetry), consolidate the intelligence and governance in one neutral layer, and add commercial tools later exactly where they earn their cost — without re-architecting, because the model does not care which tool produced the data.