> ZERO-TRUST // zt-arch-18
Zero-Overhead WebAssembly Micro-Sandboxing for Untrusted Code
High-density, sub-millisecond execution sandboxing using WebAssembly (Wasmtime / WasmEdge) and Capability-Based Security, executing third-party plugins and untrusted customer code with zero access to filesystem, environment, or network.
Adversary Threat Model
Customer uploads malicious plugin script attempting to execute cryptominers, read memory of co-tenants, or scan local network.
Architecture Specs
NIST SP 800-207 Tenets Enforced
- ✓All data sources and computing services are considered resources.
- ✓Access to individual enterprise resources is granted on a per-session basis.
- ✓All communication is secured regardless of network location.
MITRE ATT&CK Techniques Blocked
3 Maturity Tier Configurations
Evolutionary engineering configurations from baseline Initial up to CISA Optimal zero-compromise fortress.
Node.js vm2 or Python restricted execution module.
Token validation before execution.
Standard container process.
Process stdout/stderr logging.
Wasmtime runtime executing WebAssembly modules compiled from Rust/C++.
Strict capability grant: explicit file descriptors and memory fuel limits.
No network sockets provided in WASI environment.
Execution cycle count and memory usage metrics reported per tenant.
Distributed edge WASM fabric running untrusted code with sub-millisecond cold start times.
Fine-grained Capability-Based Security (Object Capabilities) per execution invocation.
Micro-isolated linear memory bounds enforced by CPU hardware architecture.
Cryptographically signed audit logs of every input/output payload.
Infrastructure as Code: Terraform & Kubernetes
Production-ready declarative manifests for immediate automated deployment.
resource "aws_ecs_task_definition" "wasm_worker" {
family = "wasm-plugin-runner"
requires_compatibilities = ["FARGATE"]
network_mode = "awsvpc"
cpu = "256"
memory = "512"
container_definitions = jsonencode([{
name = "wasmtime"
image = "ghcr.io/tiny-cto/wasm-runner:latest"
essential = true
}])
}apiVersion: node.k8s.io/v1 kind: RuntimeClass metadata: name: wasm-runtime handler: wasmtime
High-density, sub-millisecond execution sandboxing using WebAssembly (Wasmtime / WasmEdge) and Capability-Based Security, executing third-party plugins and untrusted customer code with zero access to filesystem, environment, or network.
Architecture Blueprint FAQs
How does the Zero-Overhead WebAssembly Micro-Sandboxing for Untrusted Code blueprint mitigate adversary threats and MITRE ATT&CK techniques?
Zero-Overhead WebAssembly Micro-Sandboxing for Untrusted Code addresses the following adversary profile: Customer uploads malicious plugin script attempting to execute cryptominers, read memory of co-tenants, or scan local network. It actively eliminates lateral movement and privilege escalation by mitigating: T1203, T1059, T1496, T1055 via hardware-rooted identity, kernel-level enforcement, or continuous attestation.
Which NIST SP 800-207 Zero-Trust tenets does this architecture enforce?
This blueprint strictly operationalizes the following NIST SP 800-207 tenets: All data sources and computing services are considered resources.; Access to individual enterprise resources is granted on a per-session basis.; All communication is secured regardless of network location.. Implicit trust based on network location is replaced with per-session dynamic cryptographic verification.
What are the technical differences between the Initial and Optimal maturity tiers?
The Initial tier focuses on baseline policy and identity enforcement (Node.js vm2 or Python restricted execution module.), while the Optimal tier delivers CISA ZTMM 2.0 zero-compromise fortress defense (Distributed edge WASM fabric running untrusted code with sub-millisecond cold start times.) using: spin-wasm, wasmedge, cosign-wasm, tetragon.
What is the primary failure mode risk and how is high availability guaranteed?
The primary failure risk is identified as: WASI standard evolution requiring updates to guest module bindings.. Resilience is maintained through active-active control planes, local cached attestations, and graceful degradation playbooks.
How can engineering teams automate this architecture using Terraform and Kubernetes?
The provided declarative Terraform HCL (main.tf) and Kubernetes policy manifests (policy.yaml) can be immediately integrated into automated GitOps CI/CD pipelines (e.g., ArgoCD, Flux) for reproducible, drift-detected infrastructure provisioning.