Declarative model definition
Describe scenarios, telemetry mappings, simulation pipelines, dependencies, and output requirements in a YAML or JSON format instead of spreading assumptions across spreadsheets or slides.
CRML is an open-source declarative language for cyber risk modeling. It helps teams define, validate, and exchange quantified risk models in YAML or JSON, with support for different simulation engines.
CRML (Cyber Risk Modeling Language) is an open-source declarative language for cyber risk modeling. It is designed to represent cyber risk models in YAML or JSON, with explicit descriptions of scenarios, telemetry mappings, simulation pipelines, dependencies, and output requirements.
The project positions CRML as a way to make quantified cyber risk work more repeatable and auditable across teams. It supports a Risk as Code approach, where assumptions, mappings, and model outputs are versioned and validated instead of being trapped in spreadsheets or proprietary tools.
Describe scenarios, telemetry mappings, simulation pipelines, dependencies, and output requirements in a YAML or JSON format instead of spreading assumptions across spreadsheets or slides.
Treat risk assumptions as versioned artifacts that can be reviewed, validated, and executed consistently across teams and tools.
Model controls such as defense-in-depth and quantify how they reduce risk, rather than limiting analysis to static control lists.
Use median-based parameterization, multi-currency support with automatic conversion, and auto-calibration from loss data for building quantified models.
Validate models with JSON Schema before simulation so structural errors are caught early.
Run the same CRML documents on different compliant engines, which keeps the model separate from any one simulation implementation.
Use CRML to define cyber risk scenarios, assumptions, and outputs in a reviewable format that can live in source control alongside other operational code.
Model control effectiveness and defense-in-depth assumptions when you need to understand how security controls change expected outcomes.
Exchange the same model across FAIR-style Monte Carlo workflows, Bayesian or QBER engines, and other compliant runtimes without rewriting the source model.
Validate model structure before running simulation jobs so issues in mappings, parameters, or outputs are caught earlier in the workflow.
Keep risk, control, and threat catalogs versioned separately from model logic so framework changes can be handled by updating mappings rather than rebuilding the whole model.
CRML is a declarative language for describing cyber risk models in YAML or JSON. The repository also ships a reference runtime and CLI through `crml-engine`, plus a browser UI called CRML Studio for validation and simulation.
The source describes CRML as engine-agnostic and compatible with different quantification approaches, including FAIR-style Monte Carlo engines, Bayesian/QBER models, and other compliant simulation engines.
The repository states that `crml-lang` provides language/spec models, schema validation, and YAML I/O, while `crml-engine` provides the reference runtime and `crml` CLI. The web UI is under `web/` and is described as CRML Studio.
Installation guidance in the repository says to install `crml-engine` if you want the CLI, or `crml-lang` if you only need the language library.
The project page says the codebase is under heavy development and may change without notice, and points readers to the `crml-dev-1.3` branch for the latest work in progress.
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