verifierlab 0.2.0rc2

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Pitch

VerifierLab is a local-first lab for running reproducible campaigns that ask a hard question: when something is optimized against your verifier, does the verifier still do its job?

You wrap a grader or reward function, run ordinary baselines alongside optimized-tagged attack cohorts under declared budgets and access models, then rebuild reports from content-addressed artifacts after freeze → adjudicate → release-labels. Finding no exploit is evidence under those conditions — not a proof of correctness. This release candidate (0.2.0rc2) meets executable RC gates 1–6 in tests/test_acceptance_gates.py; do not claim soundness or SOTA verifier assurance. Honest gaps (default process-local trust boundary, research-grade attack depth) are listed in docs/limitations.md.

Why it exists

Modern agents and training loops lean on verifiers: graders, reward models, rubrics, policy checkers. Those components can be gamed — reward hacking, rubric gaming, eval cheating — and the failure modes only show up under pressure.

VerifierLab exists so you can:

• Separate ordinary behavior from optimized-tagged attack cohorts
• Keep runs reproducible with content-addressed artifacts and digests
• Stay local-first: the base install has no PyTorch, Ray, Kubernetes, or model SDKs
• Record budgets (queries, steps, wall time) instead of pretending attacks are free

Status

Release candidate (0.2.0rc2). Gates 1–6 are encoded and passing in tests/test_acceptance_gates.py (isolation, optimization, measurement, repair, reproduction, developer lifecycle). Core loop — workspace, process workers, typed decisions, broker metering with worker budget vouchers, vault v2, freeze→adjudicate→release, StatsPlan reports, packs A–F, and the offline tutorial — is implemented and tested. See docs/limitations.md and SECURITY.md. Optional adapters and launchers ship behind extras or explicit dry-run modes. APIs and CLI may still shift before 0.2.0.

Install

Requires Python >=3.11,<3.14. uv is recommended.

git clone https://github.com/fraware/verifierlab.git
cd verifierlab
uv sync --extra dev
# or: pip install -e ".[dev]"

uv run valab doctor
uv run valab --version

From a published package (when available on your index):

pip install verifierlab
valab doctor

Quick start

Offline refund tutorial (full lifecycle):

uv run valab init
uv run valab inspect examples.refunds.verifier:grade
uv run valab run campaigns/refund-blackbox.yaml
uv run valab campaign freeze .valab/runs/<run-id>
uv run valab campaign adjudicate .valab/runs/<run-id> --campaign campaigns/refund-blackbox.yaml
uv run valab campaign release-labels .valab/runs/<run-id>
uv run valab report builds .valab/runs/<run-id>

Faster smoke:

uv run valab campaign validate campaigns/fake-smoke.yaml
uv run valab campaign run campaigns/fake-smoke.yaml --processes

What you can do

Full CLI table: docs/cli.md.

Optional extras

Keep the base install light. Pull only what you need:

uv sync --extra gym
# or: pip install -e ".[gym]"

Details: docs/adapters.md.

Documentation

Contributing

Contributions are welcome — new attack strategies, adapters, campaigns, docs, and bug fixes all help.

• Read CONTRIBUTING.md for setup, PR expectations, and coding standards
• Browse open issues, especially ones labeled for newcomers
• Keep the base dependency graph light; heavy stacks belong behind extras
• Follow the Code of Conduct

uv sync --extra dev
uv run ruff check src tests
uv run mypy
uv run pytest
uv run python scripts/check_base_imports.py

Security

Do not open public issues for security-sensitive reports. Prefer a private GitHub Security Advisory, or see SECURITY.md.

License

Apache-2.0.

Links

• Repository: https://github.com/fraware/verifierlab
• Issues: https://github.com/fraware/verifierlab/issues
• Changelog: CHANGELOG.md