---
title: "awesome-llm-security vs Awesome-Code-LLM"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/corca-ai-awesome-llm-security-vs-huybery-awesome-code-llm"
tools: ["corca-ai-awesome-llm-security", "huybery-awesome-code-llm"]
---

# awesome-llm-security vs Awesome-Code-LLM

*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 Awesome-Code-LLM if awesome-Code-LLM is a curated repository focused on code-focused large language models (code-LLMs), providing insights into top-performing models, evaluation toolkits, and research papers.

[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. [Awesome-Code-LLM](https://github.com/huybery/Awesome-Code-LLM) has 1.3k stars, 74 forks, and 4 open issues, last pushed Dec 10, 2024. Figures are from public GitHub metadata via [awesome-llm-security's repository](https://github.com/corca-ai/awesome-llm-security) and [Awesome-Code-LLM's repository](https://github.com/huybery/Awesome-Code-LLM).

| | [awesome-llm-security](/tools/corca-ai-awesome-llm-security.md) | [Awesome-Code-LLM](/tools/huybery-awesome-code-llm.md) |
| --- | --- | --- |
| Tagline | A curation of tools, documents and projects about LLM Security | 👨💻 An awesome and curated list of best code-LLM for research. |
| Stars | 1,672 | 1,291 |
| Forks | 312 | 74 |
| Open issues | 173 | 4 |
| Language | - | - |
| 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 | Awesome-Code-LLM is a curated repository focused on code-focused large language models (code-LLMs), providing insights into top-performing models, evaluation toolkits, and research papers. |
| Persona | - | - |
| Runtime | - | - |
| License | - | MIT License: Permissive open-source license that allows usage in virtually any project with little restrictions. |
| Categories | Evaluation & Observability | Evaluation & Observability, LLM Frameworks |

## Trust and health

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

| | [awesome-llm-security](/tools/corca-ai-awesome-llm-security.md) | [Awesome-Code-LLM](/tools/huybery-awesome-code-llm.md) |
| --- | --- | --- |
| Maintenance | Slowing (36%) | Dormant (18%) |
| Days since push | 351d | 604d |
| Open issues (now) | 173 | 4 |
| Owner type | Organization | User |
| Full report | [trust report](/tools/corca-ai-awesome-llm-security/trust.md) | [trust report](/tools/huybery-awesome-code-llm/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: Awesome-Code-LLM

- **Requirements:** No specific requirements to use the repository for reference or evaluation, but contributions may involve technical knowledge and familiarity with code-LLMs.
- **Adopt for:** Awesome-Code-LLM is a curated repository focused on code-focused large language models (code-LLMs), providing insights into top-performing models, evaluation toolkits, and research papers.
- **License detail:** MIT License: Permissive open-source license that allows usage in virtually any project with little restrictions.

## 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 Awesome-Code-LLM if…

- Requirements: No specific requirements to use the repository for reference or evaluation, but contributions may involve technical knowledge and familiarity with code-LLMs..
- Tags unique to Awesome-Code-LLM: awesome, code generation, large language models.
- Also covers LLM Frameworks.
- When you need a comprehensive list of state-of-the-art code generation LLMs with performance metrics such as HumanEval.

## 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 Awesome-Code-LLM

- When looking for a tool that provides pre-trained models with built-in APIs or services, as Awesome-Code-LLM is primarily a directory/collection of information without direct service provision.
- If you require real-time interactive use-cases and need immediate API access to LLMs; this repository does not offer such functionality.
- In scenarios where you need a single end-to-end solution for training your own code generation models, as the platform is focused on aggregating third-party resources and research rather than offering

## Common questions

### What is the difference between awesome-llm-security and Awesome-Code-LLM?

awesome-llm-security: A curation of tools, documents and projects about LLM Security. Awesome-Code-LLM: 👨💻 An awesome and curated list of best code-LLM for research.. See the comparison table for live GitHub stats and shared categories.

### When should I choose awesome-llm-security over Awesome-Code-LLM?

Choose awesome-llm-security over Awesome-Code-LLM 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 Awesome-Code-LLM over awesome-llm-security?

Choose Awesome-Code-LLM over awesome-llm-security when Requirements: No specific requirements to use the repository for reference or evaluation, but contributions may involve technical knowledge and familiarity with code-LLMs.; Tags unique to Awesome-Code-LLM: awesome, code generation, large language models; Also covers LLM Frameworks; When you need a comprehensive list of state-of-the-art code generation LLMs with performance metrics such as HumanEval.

### 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 Awesome-Code-LLM?

When looking for a tool that provides pre-trained models with built-in APIs or services, as Awesome-Code-LLM is primarily a directory/collection of information without direct service provision. If you require real-time interactive use-cases and need immediate API access to LLMs; this repository does not offer such functionality. In scenarios where you need a single end-to-end solution for training your own code generation models, as the platform is focused on aggregating third-party resources and research rather than offering

### Is awesome-llm-security or Awesome-Code-LLM more popular on GitHub?

awesome-llm-security has more GitHub stars (1,672 vs 1,291). Stars measure visibility, not whether either tool fits your constraints.

### Are awesome-llm-security and Awesome-Code-LLM open source?

Yes - both are open-source projects on GitHub.

### Where can I find alternatives to awesome-llm-security or Awesome-Code-LLM?

GraphCanon lists graph-backed alternatives at [awesome-llm-security alternatives](/tools/corca-ai-awesome-llm-security/alternatives) and [Awesome-Code-LLM alternatives](/tools/huybery-awesome-code-llm/alternatives) ([awesome-llm-security markdown twin](/tools/corca-ai-awesome-llm-security/alternatives.md), [Awesome-Code-LLM markdown twin](/tools/huybery-awesome-code-llm/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-huybery-awesome-code-llm.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 Awesome-Code-LLM?

awesome-llm-security: Slowing. Awesome-Code-LLM: 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 Awesome-Code-LLM?

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); [Awesome-Code-LLM trust report](/tools/huybery-awesome-code-llm/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/_