"Wrong Answer" with hidden tests is one of the most frustrating moments in competitive programming, coding interviews and programming classes. LLMs can read code, but their verdicts are opinions. Counterproof makes bugs reproducible. How it works: paste a problem statement and your solution (Python or C++). An agent on Vultr Serverless Inference (qwen3.8-27b) writes a brute-force oracle and a seeded random input generator. The oracle must first pass the statement's sample cases; crashing tooling is fed back to the LLM for repair. The agent stress-tests your code, smaller inputs first, and stops at the first mismatch. That input is replayed in a fresh second sandbox, and only a reproduced mismatch is reported, with expected vs. actual output, an LLM explanation and fix, and a downloadable Proof Pack (SHA-256 of every program, generator seed, both runs). Blast Radius Zero: all untrusted code, user-submitted and LLM-generated, runs in a fresh Docker container on the gVisor (runsc) runtime with no network, a read-only root filesystem, RAM-only scratch space, memory caps, a 64-process limit, CPU and wall-clock limits, all capabilities dropped and no secrets inside. The Detonate tab runs a fork bomb, HTTP exfiltration, rm -rf / with writes to /etc, a memory bomb and an infinite loop, then shows a Blast Log of the restriction triggered and host checks. Vultr stack: Serverless Inference for planning, repair, explanation and the demo's TTS voice-over; Cloud Compute (Tokyo) hosts the FastAPI backend, Docker and gVisor. The API key never enters git or a sandbox. Business value: coding-education and assessment platforms could turn a red X into a reproducible failing case, priced per submission or by licence; the sandbox layer is reusable for any product running LLM-generated code. Limits: no counterexample does not prove correctness (the UI says so); the oracle is LLM-written, validated on samples, and every mismatch is replayed.
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