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

# awesome-llm-security vs langkit

*GraphCanon updated Oct 11, 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 langkit if langKit is an open-source toolkit for monitoring Large Language Models (LLMs), offering features such as text quality, relevance metrics, and sentiment analysis.

[awesome-llm-security](https://github.com/corca-ai/awesome-llm-security) reports 1.7k GitHub stars, 398 forks, and 248 open issues, last pushed Aug 20, 2025. [langkit](https://whylabs.ai) has 997 stars, 74 forks, and 37 open issues, last pushed Nov 22, 2024. Figures are from public GitHub metadata via [awesome-llm-security's repository](https://github.com/corca-ai/awesome-llm-security) and [langkit's repository](https://github.com/whylabs/langkit).

| | [awesome-llm-security](/tools/corca-ai-awesome-llm-security.md) | [langkit](/tools/whylabs-langkit.md) |
| --- | --- | --- |
| Tagline | A curation of tools, documents and projects about LLM Security | An open-source toolkit for monitoring Large Language Models (LLMs) |
| Stars | 1,710 | 997 |
| Forks | 398 | 74 |
| Open issues | 248 | 37 |
| Language | - | Jupyter Notebook |
| 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 | LangKit is an open-source toolkit for monitoring Large Language Models (LLMs), offering features such as text quality, relevance metrics, and sentiment analysis to ensure safety and security. |
| Persona | - | - |
| Runtime | - | - |
| License | - | Apache-2.0 |
| 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) | [langkit](/tools/whylabs-langkit.md) |
| --- | --- | --- |
| Days since push | 417d | 664d |
| Open issues (now) | 248 | 37 |
| Stars delta | +18 (30d) | +3 (30d) |
| Open issues delta | +41 (30d) | 0 (30d) |
| Full report | [trust report](/tools/corca-ai-awesome-llm-security/trust.md) | [trust report](/tools/whylabs-langkit/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: langkit

- **Adopt for:** LangKit is an open-source toolkit for monitoring Large Language Models (LLMs), offering features such as text quality, relevance metrics, and sentiment analysis to ensure safety and security.

## 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 langkit if…

- Tags unique to langkit: large-language-models, machine-learning, nlg, nlp.
- Use LangKit when you need a comprehensive toolkit for monitoring LLMs that includes text quality and relevance metrics, as well as sentiment analysis.
- Leaner open-issue backlog (37).

## 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 langkit

- Avoid LangKit if you are looking for a tool that supports languages other than Python, as it is specifically designed for use with Jupyter Notebooks.
- Do not use LangKit if your project requires proprietary licensing, as it is released under the open-source Apache-2.0 license.

## Common questions

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

awesome-llm-security: A curation of tools, documents and projects about LLM Security. langkit: An open-source toolkit for monitoring Large Language Models (LLMs). See the comparison table for live GitHub stats and shared categories.

### When should I choose awesome-llm-security over langkit?

Choose awesome-llm-security over langkit 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 langkit over awesome-llm-security?

Choose langkit over awesome-llm-security when Tags unique to langkit: large-language-models, machine-learning, nlg, nlp; Use LangKit when you need a comprehensive toolkit for monitoring LLMs that includes text quality and relevance metrics, as well as sentiment analysis; Leaner open-issue backlog (37).

### 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 langkit?

Avoid LangKit if you are looking for a tool that supports languages other than Python, as it is specifically designed for use with Jupyter Notebooks. Do not use LangKit if your project requires proprietary licensing, as it is released under the open-source Apache-2.0 license.

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

awesome-llm-security has more GitHub stars (1,710 vs 997). Stars measure visibility, not whether either tool fits your constraints.

### Are awesome-llm-security and langkit open source?

Yes - both are open-source projects on GitHub.

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

GraphCanon lists graph-backed alternatives at [awesome-llm-security alternatives](/tools/corca-ai-awesome-llm-security/alternatives) and [langkit alternatives](/tools/whylabs-langkit/alternatives) ([awesome-llm-security markdown twin](/tools/corca-ai-awesome-llm-security/alternatives.md), [langkit markdown twin](/tools/whylabs-langkit/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-whylabs-langkit.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 langkit?

awesome-llm-security: Dormant. langkit: 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 langkit?

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); [langkit trust report](/tools/whylabs-langkit/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/_