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Docker Sandboxes (sbx) blocks ICMP egress with an authorizer applied only at network-creation time, and does not re-apply it to networks rebuilt from disk when the Docker daemon restarts, so a restart-surviving sandbox forwards ICMP to arbitrary hosts. A workload inside a sandbox, which the threat model treats as untrusted, can therefore defeat the documented ICMP egress block to perform network reconnaissance and exfiltrate data over an ICMP covert channel, regardless of the configured allowlist.
Docker Sandboxes (sbx) enforces an HTTP/S-only egress allowlist but does not apply it to DNS resolution: the per-network embedded DNS server forwards any queried name to the host resolver whenever the network is internet-connected, without consulting the policy. A workload inside a sandbox, which the threat model treats as untrusted, can therefore encode data into DNS labels for an attacker-controlled domain and exfiltrate it through a DNS covert channel, bypassing the configured allowlist.
The MLX inference backend in Docker Model Runner on macOS uses the MLX-LM library, which unconditionally imports and executes arbitrary Python files from model directories via the model_file configuration field in config.json. When a model's config.json specifies a model_file pointing to a Python file, MLX-LM uses importlib to load and execute it with no trust_remote_code gate or equivalent safety check. The MLX backend runs without sandboxing, resulting in arbitrary code execution on the Docker host as the Docker Desktop user. Any container on the Docker network can trigger this by calling the model-runner.docker.internal API to pull a malicious model from an attacker-controlled OCI registry and request inference.
The vllm-metal inference backend in Docker Model Runner on macOS unconditionally sets trust_remote_code=True when loading model tokenizers, and runs without sandboxing. This causes transformers. AutoTokenizer.from_pretrained() to import and execute arbitrary Python files included in any model pulled from an OCI registry, resulting in arbitrary code execution on the Docker host as the Docker Desktop user when inference is triggered. Any container on the Docker network can trigger this by calling the model-runner.docker.internal API to pull a malicious model and request inference.
The Docker CLI --use-api-socket flag bypasses Enhanced Container Isolation (ECI) restrictions in Docker Desktop. When ECI is enabled, Docker socket mounts from containers are denied unless explicitly allowed via the admin-settings configuration. However, the --use-api-socket flag adds the Docker socket mount via the HostConfig. Mounts field rather than the HostConfig. Binds field. The ECI enforcement in the Docker Desktop API proxy only inspected Binds, allowing the mount to pass unchecked. This grants a container full access to the Docker Engine socket and, if the host user has logged in to container registries, their authentication credentials. A local attacker with the ability to run Docker CLI commands can exploit this to escape ECI restrictions, access the Docker Engine, and potentially escalate privileges.