--- title: "agent-framework vs Awesome-LLMSecOps" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/microsoft-agent-framework-vs-wearetyomsmnv-awesome-llmsecops" tools: ["microsoft-agent-framework", "wearetyomsmnv-awesome-llmsecops"] --- # agent-framework vs Awesome-LLMSecOps *GraphCanon updated Sep 20, 2026* ## Verdict Pick agent-framework if the agent-framework provides tools for developers to build and deploy AI agents and multi-agent workflows in Python and .NET environments; pick Awesome-LLMSecOps if awesome-LLMSecOps is a curated list that emphasizes practical security implementation for the operations of large language models. [agent-framework](https://aka.ms/agent-framework) reports 14k GitHub stars, 2.3k forks, and 605 open issues, last pushed Sep 18, 2026. [Awesome-LLMSecOps](https://github.com/wearetyomsmnv/Awesome-LLMSecOps) has 155 stars, 76 forks, and 20 open issues, last pushed Aug 23, 2026. Figures are from public GitHub metadata via [agent-framework's repository](https://github.com/microsoft/agent-framework) and [Awesome-LLMSecOps's repository](https://github.com/wearetyomsmnv/Awesome-LLMSecOps). | | [agent-framework](/tools/microsoft-agent-framework.md) | [Awesome-LLMSecOps](/tools/wearetyomsmnv-awesome-llmsecops.md) | | --- | --- | --- | | Tagline | Framework for building and deploying AI agents and multi-agent workflows | Curated security resources for LLM operations | | Stars | 13,573 | 155 | | Forks | 2,335 | 76 | | Open issues | 605 | 20 | | Language | Python | HTML | | Adopt for | The agent-framework provides tools for developers to build and deploy AI agents and multi-agent workflows in Python and .NET environments. | Awesome-LLMSecOps is a curated list that emphasizes practical security implementation for the operations of large language models. | | Persona | - | - | | Runtime | - | - | | License | MIT | - | | Categories | AI Agents, Developer Tools | AI Agents, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agent-framework](/tools/microsoft-agent-framework.md) | [Awesome-LLMSecOps](/tools/wearetyomsmnv-awesome-llmsecops.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 0d | 19d | | Open issues (now) | 605 | 20 | | Stars delta | +855 (30d) | +5 (30d) | | Open issues delta | -80 (30d) | +9 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/microsoft-agent-framework/trust.md) | [trust report](/tools/wearetyomsmnv-awesome-llmsecops/trust.md) | ## Decision facts: agent-framework - **Requirements:** Python version 3.6 or newer is required for Python installations.; The .NET Core SDK must be installed for utilizing the .NET packages. - **Adopt for:** The agent-framework provides tools for developers to build and deploy AI agents and multi-agent workflows in Python and .NET environments. ## Decision facts: Awesome-LLMSecOps - **Adopt for:** Awesome-LLMSecOps is a curated list that emphasizes practical security implementation for the operations of large language models. ## Choose when ### Choose agent-framework if… - agent-framework is primarily Python; Awesome-LLMSecOps is HTML. - Requirements: Python version 3.6 or newer is required for Python installations.; The .NET Core SDK must be installed for utilizing the .NET packages.. - Tags unique to agent-framework: agent-framework, agentic-ai, agents, multi-agent. - Also covers Developer Tools. - Choose agent-framework if your project requires support for both Python and .NET, allowing you to develop across different ecosystems. ### Choose Awesome-LLMSecOps if… - Awesome-LLMSecOps is primarily HTML; agent-framework is Python. - Tags unique to Awesome-LLMSecOps: adversarial-ml-threat-modeling, ai-agents-security, llm-red-teaming, prompt-injection. - Also covers Evaluation & Observability. - Need a specialized focus on LLM-specific security threats like recursive pollution and prompt manipulation ## When NOT to use agent-framework - Avoid using the agent-framework if your team does not have proficiency in either Python or.NET, as this may cause difficulties in leveraging its features effectively. - Do not opt for agent-framework if you only need lightweight support for AI agents without a comprehensive orchestration and deployment framework. ## When NOT to use Awesome-LLMSecOps - Looking for extensive academic references or ArXiv papers in descriptions - Require real-time interactive tools rather than curated static lists of resources ## Common questions ### What is the difference between agent-framework and Awesome-LLMSecOps? agent-framework: Framework for building and deploying AI agents and multi-agent workflows. Awesome-LLMSecOps: Curated security resources for LLM operations. See the comparison table for live GitHub stats and shared categories. ### When should I choose agent-framework over Awesome-LLMSecOps? Choose agent-framework over Awesome-LLMSecOps when agent-framework is primarily Python; Awesome-LLMSecOps is HTML; Requirements: Python version 3.6 or newer is required for Python installations.; The .NET Core SDK must be installed for utilizing the .NET packages.; Tags unique to agent-framework: agent-framework, agentic-ai, agents, multi-agent; Also covers Developer Tools; Choose agent-framework if your project requires support for both Python and .NET, allowing you to develop across different ecosystems. ### When should I choose Awesome-LLMSecOps over agent-framework? Choose Awesome-LLMSecOps over agent-framework when Awesome-LLMSecOps is primarily HTML; agent-framework is Python; Tags unique to Awesome-LLMSecOps: adversarial-ml-threat-modeling, ai-agents-security, llm-red-teaming, prompt-injection; Also covers Evaluation & Observability; Need a specialized focus on LLM-specific security threats like recursive pollution and prompt manipulation. ### When should I avoid agent-framework? Avoid using the agent-framework if your team does not have proficiency in either Python or.NET, as this may cause difficulties in leveraging its features effectively. Do not opt for agent-framework if you only need lightweight support for AI agents without a comprehensive orchestration and deployment framework. ### When should I avoid Awesome-LLMSecOps? Looking for extensive academic references or ArXiv papers in descriptions Require real-time interactive tools rather than curated static lists of resources ### Is agent-framework or Awesome-LLMSecOps more popular on GitHub? agent-framework has more GitHub stars (13,573 vs 155). Stars measure visibility, not whether either tool fits your constraints. ### Are agent-framework and Awesome-LLMSecOps open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to agent-framework or Awesome-LLMSecOps? GraphCanon lists graph-backed alternatives at [agent-framework alternatives](/tools/microsoft-agent-framework/alternatives) and [Awesome-LLMSecOps alternatives](/tools/wearetyomsmnv-awesome-llmsecops/alternatives) ([agent-framework markdown twin](/tools/microsoft-agent-framework/alternatives.md), [Awesome-LLMSecOps markdown twin](/tools/wearetyomsmnv-awesome-llmsecops/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/microsoft-agent-framework-vs-wearetyomsmnv-awesome-llmsecops.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agent-framework or Awesome-LLMSecOps? agent-framework: Very active. Awesome-LLMSecOps: Active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for agent-framework and Awesome-LLMSecOps? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agent-framework trust report](/tools/microsoft-agent-framework/trust); [Awesome-LLMSecOps trust report](/tools/wearetyomsmnv-awesome-llmsecops/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=microsoft-agent-framework`](/api/graphcanon/graph?tool=microsoft-agent-framework) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_