cohere-terrarium: A simple Python sandbox for helpful LLM data agents

by cohere-ai · Agent Tool · ★ 312

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 70/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

code-interpreterllm-agentsandbox

Quick Facts

Stars312
Forks56
LanguagePython
CategoryAgent Tool
LicenseMIT
Quality Score70/100
Open Issues8
Last Updated2026-04-22
Created2024-04-24
Platformspython
Est. Tokens~20k

About cohere-terrarium

⚠️ No longer maintained: This repository is archived and no longer supported. If you wish to continue development, please fork the project. Terrarium - A Simple Python Sandbox Terrarium is a relatively low latency, easy to use, and economical Python sandbox - to be used as a docker deployed container, for example in GCP Cloud Run - for executing untrusted user or LLM generated code.

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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