LongCat-Flash-Prover — security grade SAFE, quality 62/100

Security audit verdict: SAFE · quality 62/100

No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

by meituan-longcat · Agent Tool · ★ 94

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

🔒 Is LongCat-Flash-Prover safe to install? View the security audit →

About LongCat-Flash-Prover

LongCat-Flash-Prover

Quick Facts

Stars94
Forks13
LanguagePython
CategoryAgent Tool
LicenseMIT
Quality Score61.5353776617537/100
Open Issues1
Last Updated2026-05-09
Created2026-03-20
Platformspython
Est. Tokens~476k

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Frequently Asked Questions

What is LongCat-Flash-Prover?

LongCat-Flash-Prover is A flagship 560-billion-parameter open-source MoE model that advances Native Formal Reasoning in Lean4 for Mathematics Formalization and Proving through agentic tool-integrated reasoning.. It is categorized as a Agent Tool with 94 GitHub stars.

What programming language is LongCat-Flash-Prover written in?

LongCat-Flash-Prover is primarily written in Python.

How do I install or use LongCat-Flash-Prover?

You can find installation instructions and usage details in the LongCat-Flash-Prover GitHub repository at github.com/meituan-longcat/LongCat-Flash-Prover. The project has 94 stars and 13 forks, indicating an active community.

What license does LongCat-Flash-Prover use?

LongCat-Flash-Prover is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to LongCat-Flash-Prover?

The top alternatives to LongCat-Flash-Prover on Agent Skills Hub include tutor-skills, repren. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. 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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