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 Azure-Samples · Agent Tool · ★ 160
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🔒 Is agent-openai-java-banking-assistant safe to install? View the security audit →
pagetype: sample languages: azdeveloper java bicep typescript html products: ai-services azure azure-openai active-directory azure-cognitive-search azure-container-apps azure-sdks github document-intelligence azure-monitor azure-pipelines urlFragment: agent-openai-java-banking-assistant name: Multi Agents Banking Assistant with Java and Langchain4j description: A Java sample app emulating a personal banking AI-powered assistant to inquire about account balances, review recent transactions, or initiate payments Multi Agent Banking Assistant with Java and [Langchain4j] [. Monthly Updates.
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agent-openai-java-banking-assistant is Multi-agent banking assistant with Java and Langchain4j. It is categorized as a Agent Tool with 160 GitHub stars.
agent-openai-java-banking-assistant is primarily written in Java. It covers topics such as agent, ai-azd-templates, azd-templates.
You can find installation instructions and usage details in the agent-openai-java-banking-assistant GitHub repository at github.com/Azure-Samples/agent-openai-java-banking-assistant. The project has 160 stars and 175 forks, indicating an active community.
agent-openai-java-banking-assistant is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to agent-openai-java-banking-assistant on Agent Skills Hub include awesome-azure-openai-llm, Agent-Skills, wcgw. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
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.
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