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Terminal-Wrench, a dataset of 331 realistic hackable environments

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I want to share a new dataset of 331 reward-hackable environments. These are real environments used in Terminal Bench and adjacent benchmarks. I first got interested in this because, as a reviewer of Terminal Bench, I noticed a lot of our tasks were hackable. I also noticed that many contributors to the benchmark do so because it provides credibility when selling environments to labs. Hence, TBench tasks are, in my opinion, held to a higher quality standard than those being used today for RL. No one is spending hours manually reviewing the $1B in tasks being purchased by major labs. As far as I understand, while everyone knows environments are hackable, nobody has released hundreds of "realistic" environments.

HN · launched Apr 15, 2026 · 6 upvotes (top 72%) · 0 views

Niche: ai benchmarking platforms · 145 launches, 4 in the last 7 days ▼ -56% · Explore this niche →

Category and tags

  • Security
  • Data infrastructure
  • Developer
  • AI feature
  • Hobby / open-source project

Visit website ↗ Source listing ↗

Could you build this?

No This is a specialized, curated research benchmark of 331 verified reward-hackable terminal environments requiring deep AI safety and reinforcement learning evaluation expertise.

What it would actually take: Building this requires designing, containerizing (Docker), and thoroughly testing hundreds of real-world command-line task environments, each instrumented with specific verifiers and exploit vectors for reward hacking. It requires deep research expertise in RLHF, agent alignment, and benchmark design, as each environment must balance realistic task completion with detectable reward specification flaws.

Discussion

2 comments analyzed.

Competitors mentioned: Berkeley 100% hack

Concerns raised: Exploits may still work on more secure harness, Unclear differentiation from existing Berkeley research

Competitors

Other products that read as similar to this one : 49 launches clear the similarity bar, closest 8 shown.

Attention rank: #38 of 50 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 162 days after the earliest competitor.

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