proofplane
An AI governance control plane where a control is satisfied
only when an executed adversarial attack failed — never because a document says it exists.
Everything linked below was produced by a pipeline run, not written by hand.
Assurance reports
Guarded configuration — 12 controls held
All twelve guardrails enabled. Includes the 12×12 independence matrix:
every probe breached when, and only when, its own guardrail was removed.
Unguarded configuration — 12 controls breached
Every guardrail disabled. This is what makes the report above mean something:
a suite that cannot go red proves nothing when it is green.
What it is worth
Loss exposure, bound to control state
FAIR Monte Carlo over eight scenarios, where a control is credited only if a
probe executed an attack against it and the attack failed. Inherent against residual, and
what each control is worth per year by counterfactual. When a guardrail stops holding, the
dollar figure moves on the next run.
Machine-readable output
OSCAL assessment results
Validated against the NIST OSCAL 1.1.2 schema. Every observation carries
method TEST, because that is what happened.
AI bill of materials
CycloneDX 1.6 ML-BOM of this repository's own AI surface, with the file and
line that produced each component.
Limitation demonstrations
The weaknesses the documentation admits to, executed against a fully guarded
target rather than asserted.
Loss exposure model output
Every figure from the exposure report, with the evidence run and head hash it
was derived from.
Read the status honestly. These runs use a deterministic model double, so a
held result is evidence that the guardrail works — not that any model is safe. Against a
live model, zero breaches in three trials is consistent with a true failure rate above 50%,
which is why every result shows its trial count.