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

# awesome-llm-security vs vigil-llm

*GraphCanon updated Jul 12, 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 vigil-llm if vigil-LLM is specifically designed for detecting prompt injections and jailbreaks in LLM inputs, offering unique capabilities not found in all security tools.

[awesome-llm-security](https://github.com/corca-ai/awesome-llm-security) reports 1.6k GitHub stars, 294 forks, and 161 open issues, last pushed Aug 20, 2025. [vigil-llm](https://vigil.deadbits.ai/) has 489 stars, 55 forks, and 16 open issues, last pushed Jan 31, 2024. Figures are from public GitHub metadata via [awesome-llm-security's repository](https://github.com/corca-ai/awesome-llm-security) and [vigil-llm's repository](https://github.com/deadbits/vigil-llm).

| | [awesome-llm-security](/tools/corca-ai-awesome-llm-security.md) | [vigil-llm](/tools/deadbits-vigil-llm.md) |
| --- | --- | --- |
| Tagline | A curation of tools, documents and projects about LLM Security | ⚡ Vigil ⚡ Detect prompt injections, jailbreaks, and other potentially risky Large Language Model (LLM) inputs |
| Stars | 1,637 | 489 |
| Forks | 294 | 55 |
| Open issues | 161 | 16 |
| 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 | Vigil-LLM is specifically designed for detecting prompt injections and jailbreaks in LLM inputs, offering unique capabilities not found in all security tools. |
| Persona | - | - |
| Runtime | - | - |
| License | - | Apache-2.0 |
| Categories | Evaluation & Observability | Evaluation & Observability, LLM Frameworks, Vector Databases |

## Trust and health

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

| | [awesome-llm-security](/tools/corca-ai-awesome-llm-security.md) | [vigil-llm](/tools/deadbits-vigil-llm.md) |
| --- | --- | --- |
| Maintenance | Slowing (36%) | Dormant (18%) |
| Days since push | 325d | 891d |
| Open issues (now) | 161 | 16 |
| Owner type | Organization | User |
| Full report | [trust report](/tools/corca-ai-awesome-llm-security/trust.md) | [trust report](/tools/deadbits-vigil-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: vigil-llm

- **Pricing:** freemium - Vigil-LLM is open-source under the Apache License 2.0 and freely available to download. However, additional support or services may be offered on a paid basis depending on the context of usage.
- **Requirements:** Min 4 GB RAM
- **Adopt for:** Vigil-LLM is specifically designed for detecting prompt injections and jailbreaks in LLM inputs, offering unique capabilities not found in all security tools.

## 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 vigil-llm if…

- Pricing: Vigil-LLM is open-source under the Apache License 2.0 and freely available to download. However, additional support or services may be offered on a paid basis depending on the context of usage..
- Requirements: Min 4 GB RAM.
- Tags unique to vigil-llm: adversarial-attacks, adversarial-machine-learning, large-language-models, llm-security.
- Also covers LLM Frameworks, Vector Databases.
- When integrating large language models into applications that need robust protection against prompt injection attacks.

## 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 vigil-llm

- If the focus of security efforts is solely on data breaches and not specifically on securing against adversarial machine learning techniques like prompt injections or jailbreaks.
- When your environment is set up without Python or YARA v4.3.2, as these are prerequisites for using Vigil-LLM effectively.

## Common questions

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

awesome-llm-security: A curation of tools, documents and projects about LLM Security. vigil-llm: ⚡ Vigil ⚡ Detect prompt injections, jailbreaks, and other potentially risky Large Language Model (LLM) inputs. See the comparison table for live GitHub stats and shared categories.

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

Choose awesome-llm-security over vigil-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 vigil-llm over awesome-llm-security?

Choose vigil-llm over awesome-llm-security when Pricing: Vigil-LLM is open-source under the Apache License 2.0 and freely available to download. However, additional support or services may be offered on a paid basis depending on the context of usage.; Requirements: Min 4 GB RAM; Tags unique to vigil-llm: adversarial-attacks, adversarial-machine-learning, large-language-models, llm-security; Also covers LLM Frameworks, Vector Databases; When integrating large language models into applications that need robust protection against prompt injection attacks.

### 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 vigil-llm?

If the focus of security efforts is solely on data breaches and not specifically on securing against adversarial machine learning techniques like prompt injections or jailbreaks. When your environment is set up without Python or YARA v4.3.2, as these are prerequisites for using Vigil-LLM effectively.

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

awesome-llm-security has more GitHub stars (1,637 vs 489). Stars measure visibility, not whether either tool fits your constraints.

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

Yes - both are open-source projects on GitHub.

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

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

awesome-llm-security: Slowing. vigil-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 vigil-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); [vigil-llm trust report](/tools/deadbits-vigil-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/_