--- title: "Aegis vs Awesome-LLMSecOps" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/justin0504-aegis-vs-wearetyomsmnv-awesome-llmsecops" tools: ["justin0504-aegis", "wearetyomsmnv-awesome-llmsecops"] --- # Aegis vs Awesome-LLMSecOps *GraphCanon updated Sep 20, 2026* ## Verdict Pick Aegis if aegis provides runtime policy enforcement for AI agents with cryptographic audit trails and human-in-the-loop approvals, supporting zero-code deployment switches suited for various compliance needs; pick Awesome-LLMSecOps if awesome-LLMSecOps is a curated list that emphasizes practical security implementation for the operations of large language models. [Aegis](https://github.com/Justin0504/Aegis) reports 340 GitHub stars, 37 forks, and 3 open issues, last pushed Sep 6, 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 [Aegis's repository](https://github.com/Justin0504/Aegis) and [Awesome-LLMSecOps's repository](https://github.com/wearetyomsmnv/Awesome-LLMSecOps). | | [Aegis](/tools/justin0504-aegis.md) | [Awesome-LLMSecOps](/tools/wearetyomsmnv-awesome-llmsecops.md) | | --- | --- | --- | | Tagline | Runtime policy enforcement for AI agents with cryptographic audit trail and human-in-the-loop approvals. | Curated security resources for LLM operations | | Stars | 340 | 155 | | Forks | 37 | 76 | | Open issues | 3 | 20 | | Language | TypeScript | HTML | | Adopt for | Aegis provides runtime policy enforcement for AI agents with cryptographic audit trails and human-in-the-loop approvals, supporting zero-code deployment switches suited for various compliance needs. | 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, Evaluation & Observability | AI Agents, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Aegis](/tools/justin0504-aegis.md) | [Awesome-LLMSecOps](/tools/wearetyomsmnv-awesome-llmsecops.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 4d | 19d | | Open issues (now) | 3 | 20 | | Stars delta | -27 (30d) | +5 (30d) | | Open issues delta | 0 (30d) | +9 (30d) | | Full report | [trust report](/tools/justin0504-aegis/trust.md) | [trust report](/tools/wearetyomsmnv-awesome-llmsecops/trust.md) | ## Decision facts: Aegis - **Adopt for:** Aegis provides runtime policy enforcement for AI agents with cryptographic audit trails and human-in-the-loop approvals, supporting zero-code deployment switches suited for various compliance needs. ## 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 Aegis if… - Aegis is primarily TypeScript; Awesome-LLMSecOps is HTML. - Tags unique to Aegis: ai-safety, anthropic, audit-trail, llm-observability. - Aegis ships Docker support for self-hosted deployment. - You need cryptographic assurance of the audit trail to meet high-security standards. ### Choose Awesome-LLMSecOps if… - Awesome-LLMSecOps is primarily HTML; Aegis is TypeScript. - Tags unique to Awesome-LLMSecOps: adversarial-ml-threat-modeling, ai-agents-security, llm-red-teaming, prompt-injection. - Need a specialized focus on LLM-specific security threats like recursive pollution and prompt manipulation ## When NOT to use Aegis - The project does not require a zero-code deployment switch and can manage changes directly in the codebase. - Minimal regulatory requirements mean that elaborate configurations like Aegis's strict retention policies are unnecessary. ## 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 Aegis and Awesome-LLMSecOps? Aegis: Runtime policy enforcement for AI agents with cryptographic audit trail and human-in-the-loop approvals.. Awesome-LLMSecOps: Curated security resources for LLM operations. See the comparison table for live GitHub stats and shared categories. ### When should I choose Aegis over Awesome-LLMSecOps? Choose Aegis over Awesome-LLMSecOps when Aegis is primarily TypeScript; Awesome-LLMSecOps is HTML; Tags unique to Aegis: ai-safety, anthropic, audit-trail, llm-observability; Aegis ships Docker support for self-hosted deployment; You need cryptographic assurance of the audit trail to meet high-security standards. ### When should I choose Awesome-LLMSecOps over Aegis? Choose Awesome-LLMSecOps over Aegis when Awesome-LLMSecOps is primarily HTML; Aegis is TypeScript; Tags unique to Awesome-LLMSecOps: adversarial-ml-threat-modeling, ai-agents-security, llm-red-teaming, prompt-injection; Need a specialized focus on LLM-specific security threats like recursive pollution and prompt manipulation. ### When should I avoid Aegis? The project does not require a zero-code deployment switch and can manage changes directly in the codebase. Minimal regulatory requirements mean that elaborate configurations like Aegis's strict retention policies are unnecessary. ### 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 Aegis or Awesome-LLMSecOps more popular on GitHub? Aegis has more GitHub stars (340 vs 155). Stars measure visibility, not whether either tool fits your constraints. ### Are Aegis and Awesome-LLMSecOps open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to Aegis or Awesome-LLMSecOps? GraphCanon lists graph-backed alternatives at [Aegis alternatives](/tools/justin0504-aegis/alternatives) and [Awesome-LLMSecOps alternatives](/tools/wearetyomsmnv-awesome-llmsecops/alternatives) ([Aegis markdown twin](/tools/justin0504-aegis/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/justin0504-aegis-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, Aegis or Awesome-LLMSecOps? Aegis: 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 Aegis and Awesome-LLMSecOps? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Aegis trust report](/tools/justin0504-aegis/trust); [Awesome-LLMSecOps trust report](/tools/wearetyomsmnv-awesome-llmsecops/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=justin0504-aegis`](/api/graphcanon/graph?tool=justin0504-aegis) - 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/_