COVERT CHANNEL LAB

Research note 001 / 18 September 2026

What does it take
to close a channel?

A small, exact experiment in making an untrusted worker’s choices invisible to a defined observer.

We combine five digital controls with a thermal model, search every configuration in the catalogue, and check the winning design. The failures are part of the result.

Illustrative model · Declared physical assumptions · No hardware validation

{{configuration_count}}configurations enumerated
{{feasible_count}}feasible in this model
34 / 34Python tests passed
{{theorem_count}}Lean declarations audited

Beyond the thermal example

Air-gapped. Still observable.

Explore 21 channel families, a proposed configuration for nearby observers, and the evidence needed to establish an optimum.

Open the channel prevention field guide →

The question that started this

Air gaps still leave physical observations.

“One of them is able to run their CPU really hot, and then the other one can actually detect the temperature change.”
Noam Brown, OpenAI · Dwarkesh Podcast, September 17, 2026 ↗From the 01:08:34 chapter, before 01:14:12. This independent lab is inspired by that discussion; no endorsement is implied.

01 / The model

Control what the receiver can observe.

Different authorized answers may still differ. The goal is to remove the worker’s freedom to encode an extra signal inside the same authorized result.

UNTRUSTEDWorker’s proposalVariants, timing, withholding
TRUSTED CONTRACTVerify or fall backThe same authorized answer
PUBLICCanonical releaseFixed slot, mediated observation
01 Canonical encoding02 Fixed release slot03 Total fallback04 Resource partition05 Mediated egress

All five are necessary within this catalogue. A simulator switch is a contract to implement, not evidence of an enforced boundary. Read the assumptions ↗

02 / Configuration explorer

A whole search space.
One least-cost answer.

Choose a thermal design to inspect its exact certificate. This slice holds all five digital controls on: 11 attenuation settings × 5 regulation settings.

REGULATION r ↓ATTENUATION s →
{{configuration_grid}}
CertifiedCounterexampleMinimum cost

Numbers inside cells are modeled cost. “Certified” means the stipulated invariant and service floor hold.

Certified · minimum cost

s = 7 / r = 2

Modeled cost
57
Declared service score
90 / 100
Invariant radius
1/20
Sensor threshold
11/200

The radius stays strictly below the threshold. The all-time certificate holds under the declared envelope.

Every configuration, in JSON ↗

Why this is optimal

9J = 2(2s + r)² + (s − 4r)² ≥ 512

Feasibility requires 2s + r ≥ 16. Integer cost therefore satisfies J ≥ 57, and the witness reaches 57. Follow the derivation ↗

03 / The instructive failure

Quiet for 23 steps.
Observable at step 24.

Reduce regulation by one unit and the near-miss looks safe until it crosses the sensor threshold. A finite quiet prefix is not an all-time certificate.

Hot workloadQuiet workloadSensor threshold
{{thermal_chart}}

At step 24 the hot observation becomes 1; the quiet observation stays 0. The two runs use the same allowed disturbance.

Illustrative temperature deviation, zero initialization. Points are computed with exact fractions; their plotted positions are rounded for display. Raw temperatures also differ in the winning design.

04 / Negative knowledge

Keep the failures.
Make the next attempt better.

Nine replayable records preserve the rejected claims, decisive witnesses, and lessons. They are linked into the Research Kernel ledger.

{{negative_cards}}

Download all witnesses ↗/Continue the research ↗

05 / Evidence & scope

Check the result. Know its boundary.

Reproduced and checked

  • Exact search and independent optimality certificate
  • 34 Python tests, including 65,792 sorting cases
  • Lean 4.19.0 kernel check and 24 theorem axiom audits
  • Five digital ablations and every default thermal pair
Read the verification receipt ↗

Still open

  • Real-valued plant to integer envelope refinement
  • Concrete gate, isolation and fallback deadline
  • Measured hardware bounds and complete observer map
  • Composition with aggregate colluding-worker loads
Take over an open work packet ↗

Reproduce locally

Python 3.10+ · Lean 4.19.0 · No Mathlib

python3 scripts/verify.py
python3 scripts/replay_negative.py --check