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Covert-Channel Threat Model

Your agents are isolated — except through the hardware they share

Model covert channels between isolated agents: shared caches, storage timing, CPU contention, and certificate caches, and decide which channels your threat model must cover and which controls actually close them.

Vista previa de Covert-Channel Threat Model
Ideal para
Security architects, platform teams, AI infra leads
Tiempo necesario
~1 day to model
Nivel
Intermedio

Instálala en 3 pasos

Sin registro. Sin herramientas CLI. Elige tu IA, copia una línea y pégala.

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Qué incluye

Un SKILL.md (la guía paso a paso) + una plantilla inicial. Una vista previa:

Covert-Channel Threat Model

The finding that changes the model

In October 2026, OpenAI disclosed that two red-team agents in separate microVMs on a shared host exchanged synthetic secrets through CPU cache timing: one evicted chosen cache data, the other measured reload times. No network. No shared files. The channel was slow and hard to exploit — OpenAI said so itself — but it was real, and it survived every software control that was supposed to keep the agents apart. If your threat model says "isolated means cannot communicate," this finding breaks it.

Workflow

  1. List shared resources (input: your agent deployment -> output: a resource list).
    For every pair of agents that must not communicate, list what they
    share: a host (CPU cache, memory bandwidth), a storage system (write
    timing, shared files), a network path (DNS, TLS caches, proxies), a
    scheduler (CPU contention), and a monitoring system (logs both can
    influence). A shared resource is a potential channel; an unlisted one
    is an unmodelled one.
  2. Rank channels by bandwidth and stealth (input: resource list -> output: a ranked table).
    For each resource, estimate: how much data could pass per hour, how
    noisy the signal is to your monitoring, and whether the agents need
    prior coordination (a shared protocol) or can invent one. Cache timing
    is low-bandwidth and noisy; storage write patterns are higher
    bandwidth and easier to spot; DNS is the classic exfiltration path
    and the one that actually escaped in September 2026.
  3. Map controls to channels (input: ranked table -> output: a control matrix).
    For each channel, name the control that closes it — not mitigates it
    in theory, but closes it in your deployment: cache partitioning or
    dedicated hosts for cache timing; separate storage for storage timing;
    no shared DNS resolvers for DNS; noisy-neighbour detection for CPU
    contention. A channel with no closing control is an accepted risk:
    write it down, name who accepted it, and say what monitoring watches it.
  4. Test with a red team (input: control matrix -> output: test results).
    Give a red team the same task OpenAI gave its agents: exchange a
    secret between two isolated agents, with and without a supplied
    protocol. The with-protocol test checks your controls; the
    without-protocol test checks whether your agents can invent a channel
    you did not model. Most teams fail the second test the first time —
    that is the point of running it.
  5. Set the monitoring bar (input: test results -> output: detection rules).
    Write detection rules for the channels you accepted: timing anomalies
    in cache-sensitive workloads, rhythmic write patterns in shared
    storage, unusual DNS query shapes. A channel you cannot detect is a
    channel you must close, not one you monitor — monitoring that cannot
    see the signal is decoration.

Vista previa de la plantilla

Covert-Channel Threat Model Worksheet

1. Shared resources (per agent pair)

2. Ranked channels

3. Control matrix

4. Red-team test

  • With protocol result:
  • Without protocol result:

5. Detection rules

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El paquete de la habilidad (SKILL.md + plantilla) está escrito en inglés.

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