doris — security grade SAFE, quality 56/100

Security audit verdict: SAFE · quality 56/100

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 apache · Agent Tool · ★ 16.0k

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

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About doris

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Quick Facts

Stars15,969
Forks3,951
LanguageJava
CategoryAgent Tool
LicenseApache-2.0
Quality Score55.8023146955644/100
Open Issues1351
Last Updated2026-09-20
Created2017-08-10
Platformsjava
Est. Tokens~18k

Compatible Skills

These tools work well together with doris for enhanced workflows:

doris alternative? Top 6 similar tools

Looking for a doris alternative? If you're comparing doris with other agent tool tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

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Frequently Asked Questions

What is doris?

doris is Apache Doris is a real-time analytics and hybrid search database for AI agents.. It is categorized as a Agent Tool with 16.0k GitHub stars.

What programming language is doris written in?

doris is primarily written in Java. It covers topics such as agent, ai, bigquery.

How do I install or use doris?

You can find installation instructions and usage details in the doris GitHub repository at github.com/apache/doris. The project has 16.0k stars and 3951 forks, indicating an active community.

What license does doris use?

doris is released under the Apache-2.0 license, making it free to use and modify according to the license terms.

What are the best alternatives to doris?

The top alternatives to doris on Agent Skills Hub include mcp-toolbox, gpt-researcher, WrenAI. 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:

View on GitHub → Browse Agent Tool tools