---
title: "awesome-llm-security vs raga-llm-hub"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/corca-ai-awesome-llm-security-vs-raga-ai-hub-raga-llm-hub"
tools: ["corca-ai-awesome-llm-security", "raga-ai-hub-raga-llm-hub"]
---

# awesome-llm-security vs raga-llm-hub

*GraphCanon updated Aug 6, 2026*

## Verdict

Pick awesome-llm-security if awesome LLM Security is a curated list of resources related to the security aspects of large language models. It covers various attack methodologies, defenses, and platform security through papers, benchmarks, tools, and; pick raga-llm-hub if raga LLM-Hub is a Python-based framework for evaluating large language models, enforcing guardrails, and ensuring security during the operation of these models.

[awesome-llm-security](https://github.com/corca-ai/awesome-llm-security) reports 1.7k GitHub stars, 312 forks, and 173 open issues, last pushed Aug 20, 2025. [raga-llm-hub](https://www.raga.ai/llms) has 114 stars, 14 forks, and 2 open issues, last pushed Sep 9, 2024. Figures are from public GitHub metadata via [awesome-llm-security's repository](https://github.com/corca-ai/awesome-llm-security) and [raga-llm-hub's repository](https://github.com/raga-ai-hub/raga-llm-hub).

| | [awesome-llm-security](/tools/corca-ai-awesome-llm-security.md) | [raga-llm-hub](/tools/raga-ai-hub-raga-llm-hub.md) |
| --- | --- | --- |
| Tagline | A curation of tools, documents and projects about LLM Security | Framework for LLM evaluation, guardrails and security |
| Stars | 1,672 | 114 |
| Forks | 312 | 14 |
| Open issues | 173 | 2 |
| Language | - | Python |
| Adopt for | Awesome LLM Security is a curated list of resources related to the security aspects of large language models. It covers various attack methodologies, defenses, and platform security through papers, benchmarks, tools, and | Raga LLM-Hub is a Python-based framework for evaluating large language models, enforcing guardrails, and ensuring security during the operation of these models. |
| Persona | - | - |
| Runtime | - | - |
| License | - | The license for Raga LLM-Hub differs from common Open Source licenses like MIT or Apache, implying specific conditions that might affect its usability in open projects. |
| Categories | Evaluation & Observability | Evaluation & Observability |

## Trust and health

_Sourced signals - not a safety guarantee. No winner column._

| | [awesome-llm-security](/tools/corca-ai-awesome-llm-security.md) | [raga-llm-hub](/tools/raga-ai-hub-raga-llm-hub.md) |
| --- | --- | --- |
| Maintenance | Slowing (36%) | Dormant (18%) |
| Days since push | 351d | 687d |
| Open issues (now) | 173 | 2 |
| Full report | [trust report](/tools/corca-ai-awesome-llm-security/trust.md) | [trust report](/tools/raga-ai-hub-raga-llm-hub/trust.md) |

## Decision facts: awesome-llm-security

- **Hosting:** unknown
- **Pricing:** freemium - As an open-source project without defined pricing models, its use is generally free under the terms of its license (license details are not provided).
- **Adopt for:** Awesome LLM Security is a curated list of resources related to the security aspects of large language models. It covers various attack methodologies, defenses, and platform security through papers, benchmarks, tools, and

## Decision facts: raga-llm-hub

- **Pricing:** unknown - Pricing information is not specified; it operates under a unique licensing model which may or may not have restrictive terms for commercial use.
- **Requirements:** Requires Python installation and environment to set up.; Installation is straightforward through pip but the broader dependencies should be checked as per project requirements.
- **Adopt for:** Raga LLM-Hub is a Python-based framework for evaluating large language models, enforcing guardrails, and ensuring security during the operation of these models.
- **License detail:** The license for Raga LLM-Hub differs from common Open Source licenses like MIT or Apache, implying specific conditions that might affect its usability in open projects.

## Choose when

### Choose awesome-llm-security if…

- Pricing: As an open-source project without defined pricing models, its use is generally free under the terms of its license (license details are not provided)..
- Tags unique to awesome-llm-security: awesome-list, llm, security.
- When you are specifically looking for detailed information on both white-box and black-box attacks targeted at Large Language Models (LLMs), which 'awesome-llm-security' comprehensively catalogs.

### Choose raga-llm-hub if…

- Pricing: Pricing information is not specified; it operates under a unique licensing model which may or may not have restrictive terms for commercial use..
- Requirements: Requires Python installation and environment to set up.; Installation is straightforward through pip but the broader dependencies should be checked as per project requirements..
- Tags unique to raga-llm-hub: guardrails, llm security, llm-evaluation, llmops.
- When you need to conduct detailed evaluations on large language models and require specific methods to enforce guardrails and maintain security within your application or environment.

## When NOT to use awesome-llm-security

- When your primary interest is in general software security or vulnerabilities unrelated to language models, since 'awesome-llm-security' zeroes in on attack vectors specifically for LLMs.
- If you are solely interested in tools and methods that are not publicly discussed or peer-reviewed; the repository focuses on documented approaches within reputable academic publications.

## When NOT to use raga-llm-hub

- If you are working in an environment where the use of Python is not feasible or desired, as Raga LLM-Hub's functionality is deeply integrated within Python.
- Avoid using if your primary need does not include guardrails enforcement and security features for LLMs, since Raga LLM Hub emphasizes these aspects.

## Common questions

### What is the difference between awesome-llm-security and raga-llm-hub?

awesome-llm-security: A curation of tools, documents and projects about LLM Security. raga-llm-hub: Framework for LLM evaluation, guardrails and security. See the comparison table for live GitHub stats and shared categories.

### When should I choose awesome-llm-security over raga-llm-hub?

Choose awesome-llm-security over raga-llm-hub when Pricing: As an open-source project without defined pricing models, its use is generally free under the terms of its license (license details are not provided).; Tags unique to awesome-llm-security: awesome-list, llm, security; When you are specifically looking for detailed information on both white-box and black-box attacks targeted at Large Language Models (LLMs), which 'awesome-llm-security' comprehensively catalogs.

### When should I choose raga-llm-hub over awesome-llm-security?

Choose raga-llm-hub over awesome-llm-security when Pricing: Pricing information is not specified; it operates under a unique licensing model which may or may not have restrictive terms for commercial use.; Requirements: Requires Python installation and environment to set up.; Installation is straightforward through pip but the broader dependencies should be checked as per project requirements.; Tags unique to raga-llm-hub: guardrails, llm security, llm-evaluation, llmops; When you need to conduct detailed evaluations on large language models and require specific methods to enforce guardrails and maintain security within your application or environment.

### When should I avoid awesome-llm-security?

When your primary interest is in general software security or vulnerabilities unrelated to language models, since 'awesome-llm-security' zeroes in on attack vectors specifically for LLMs. If you are solely interested in tools and methods that are not publicly discussed or peer-reviewed; the repository focuses on documented approaches within reputable academic publications.

### When should I avoid raga-llm-hub?

If you are working in an environment where the use of Python is not feasible or desired, as Raga LLM-Hub's functionality is deeply integrated within Python. Avoid using if your primary need does not include guardrails enforcement and security features for LLMs, since Raga LLM Hub emphasizes these aspects.

### Is awesome-llm-security or raga-llm-hub more popular on GitHub?

awesome-llm-security has more GitHub stars (1,672 vs 114). Stars measure visibility, not whether either tool fits your constraints.

### Are awesome-llm-security and raga-llm-hub open source?

Yes - both are open-source projects on GitHub.

### Where can I find alternatives to awesome-llm-security or raga-llm-hub?

GraphCanon lists graph-backed alternatives at [awesome-llm-security alternatives](/tools/corca-ai-awesome-llm-security/alternatives) and [raga-llm-hub alternatives](/tools/raga-ai-hub-raga-llm-hub/alternatives) ([awesome-llm-security markdown twin](/tools/corca-ai-awesome-llm-security/alternatives.md), [raga-llm-hub markdown twin](/tools/raga-ai-hub-raga-llm-hub/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/corca-ai-awesome-llm-security-vs-raga-ai-hub-raga-llm-hub.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, awesome-llm-security or raga-llm-hub?

awesome-llm-security: Slowing. raga-llm-hub: Dormant. 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 awesome-llm-security and raga-llm-hub?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [awesome-llm-security trust report](/tools/corca-ai-awesome-llm-security/trust); [raga-llm-hub trust report](/tools/raga-ai-hub-raga-llm-hub/trust).

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=corca-ai-awesome-llm-security`](/api/graphcanon/graph?tool=corca-ai-awesome-llm-security)
- 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/_