ORIGINAL CYBERSECURITY TASKS

Original cybersecurity tasks, built and verified by experts.

CYVARC creates new tasks around the security capability your model needs to learn or prove. We define the objective, environment, constraints, intended solution, and validation method as one system. Every task is reviewed by people who work in the relevant security domain.

01 · THE STANDARD

What makes a task ready for training.

Security expertise is essential, but training data also needs clear standards for fairness, difficulty, and reward integrity. We author original tasks rather than recycle CTF challenges, and deduplicate at the idea level, not just the wording.

01

Specific capability target

The task is built around a named security skill rather than a broad theme or an arbitrary puzzle mechanic.

02

Reproducible environment

The setup is packaged so reviewers and agents encounter the same conditions and the result does not depend on an accidental local state.

03

Independent reproduction

A second specialist follows the task from the supplied materials and verifies the intended solution without relying on private author context.

02 · YOUR WORKFLOW

From specification to reviewed task.

Define the objective

We agree on the target skill, expected agent access, completion boundary, difficulty range, and any restrictions before authoring begins.

Build the task and environment

The author creates the challenge materials, setup, intended path, and checks required to reproduce the result.

Review what the task actually measures

An expert checks whether the task rewards the intended capability and flags ambiguity, unintended paths, fragile dependencies, or difficulty caused by poor setup.

Package the evidence

Deliverables can include task files, environment instructions, the verified solution, agent run notes, reward checks, and structured review findings.

YOUR NEXT STEP

Start with a sample.

Tell us which cybersecurity capabilities matter to your work. We can arrange relevant tasks for private review and scope an SFT or RL dataset around your needs.