Case study in progress Verified evidence, incomplete publication scope

nullstate

An autonomous purple-team IaC sandbox built for the AMD x lablab.ai hackathon, then expanded into an open-source DevSecOps alpha with reproducible attack, remediation, and evidence workflows.

48h original hackathon build AMD x lablab.ai submission window.
104.45 tok/s AWS red-agent output Gemma 4 26B final run telemetry.
160.94 tok/s AWS blue-agent output Gemma 4 26B final run telemetry.
Blocked post-fix AWS replay Public S3 path after deterministic remediation.

The core AWS path is proven. The full case study is not finished.

nullstate tests whether infrastructure security validation can move beyond a static finding. It reads Terraform, targets controlled cloud emulators, asks self-hosted models to reason about red and blue paths, applies deterministic remediation, repeats the attack, and writes evidence a reviewer can inspect.

The acting models ran through ROCm and vLLM on an AMD Instinct MI300X. The endpoint was reached through a secure SSH tunnel rather than exposed publicly. The model improved reasoning and reporting, while deterministic code remained the source of truth for findings, fixes, and the final pass or fail verdict.

A constrained red and blue loop around reproducible infrastructure.

The original Terraform source is never modified. Every run operates in an isolated workspace and preserves events, findings, attack code, remediation, metrics, and the final report.

  1. 01 Terraform input

    Read an IaC project and create an isolated run workspace.

  2. 02 Deterministic detection

    Identify supported cloud-storage exposure from configuration and plan evidence.

  3. 03 Local sandbox

    Target LocalStack-backed AWS or Azure-style infrastructure rather than production accounts.

  4. 04 Private model endpoint

    Call self-hosted red and blue models through an SSH-tunneled OpenAI-compatible vLLM API.

  5. 05 Constrained attack

    Execute only the generated run-directory attack script and preserve command evidence.

  6. 06 Deterministic repair

    Apply a versioned Terraform patch rather than accepting model output as the security verdict.

  7. 07 Replay and report

    Repeat the attack, record the outcome, and write structured evidence artifacts.

AWS LocalStack replay and repository discipline

  • The public S3 path was live-validated against LocalStack.
  • The attack succeeded before remediation and was blocked after the deterministic Terraform fix.
  • Final AWS telemetry records 942 red completion tokens and 640 blue completion tokens.
  • CI, CodeQL, dependency review, security documentation, and release evidence are public.

Live Azure validation and broad production readiness

  • The Azure Blob path has deterministic finding and remediation evidence but not live emulator validation.
  • Kubernetes, Docker Compose, and on-prem targets remain scaffolded unless a page states otherwise.
  • The current benchmark does not yet execute Checkov, tfsec, Terrascan, or a human-review baseline.
  • This is an open-source alpha and should not be treated as a production security control.

The screenshots support the story, but do not replace the run artifacts.

Open any image at full size. The repository remains the canonical source for the security model, technical walkthrough, run contracts, and current readiness limits.

The model never receives an unrestricted shell.

The red model returns attack reasoning. nullstate executes only the generated run-directory attack.py through a constrained runner and records the command, stdout, stderr, return code, target, stage, and duration.

Production cloud access is out of scope by default. Model endpoints, LocalStack, cloud tokens, Terraform state, and environment files are not exposed as public services.

What still has to be assembled