---
title: "vigil-llm vs llm-guard"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/deadbits-vigil-llm-vs-protectai-llm-guard"
tools: ["deadbits-vigil-llm", "protectai-llm-guard"]
---

# vigil-llm vs llm-guard

Neutral, constraint-first comparison with live GitHub stats.

| | [vigil-llm](/tools/deadbits-vigil-llm.md) | [llm-guard](/tools/protectai-llm-guard.md) |
| --- | --- | --- |
| Tagline | ⚡ Security scanner for Large Language Model prompts ⚡ | The Security Toolkit for LLM Interactions |
| Stars | 486 | 3,162 |
| Forks | 55 | 417 |
| Open issues | 16 | 40 |
| Language | Python | Python |
| Adopt for | vigil-llm is a security tool that acts as a scanner for potentially risky Large Language Model (LLM) prompts, like prompt injections and jailbreaks. Being in the alpha stage means it currently serves research purposes. | - |
| Persona | - | - |
| Runtime | - | - |
| License | vigil-llm is licensed under the Apache-2.0 license, allowing for free use in both commercial and non-commercial projects while requiring any redistribution of the software to maintain the same open-s源 | MIT |
| Categories | Evaluation & Observability | Evaluation & Observability, LLM Frameworks |

## Trust and health

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

| | [vigil-llm](/tools/deadbits-vigil-llm.md) | [llm-guard](/tools/protectai-llm-guard.md) |
| --- | --- | --- |
| Maintenance | Dormant (18%) | Archived (8%) |
| Days since push | 888d | 0d |
| Archived on GitHub | No | Yes |
| Open issues (now) | 16 | 40 |
| Owner type | User | Organization |
| Security scan | 65 low (65 low) | No lockfile |
| Full report | [trust report](/tools/deadbits-vigil-llm/trust.md) | [trust report](/tools/protectai-llm-guard/trust.md) |

**Typed relationship:** vigil-llm _(alternative)_ llm-guard

Both llm-guard and vigil-llm are security tools designed to protect against potential threats in Large Language Model interactions, such as prompt injection attacks.

## Shared compatibility

- **Python**: [vigil-llm](/tools/deadbits-vigil-llm.md) - Python runtime; [llm-guard](/tools/protectai-llm-guard.md) - Python runtime

## Decision facts: vigil-llm

- **Requirements:** - Vigil supports local embeddings via sentence-transformers and can integrate with OpenAI's models.; - It is built as a Python library but also provides a REST API for more flexible integration.
- **Adopt for:** vigil-llm is a security tool that acts as a scanner for potentially risky Large Language Model (LLM) prompts, like prompt injections and jailbreaks. Being in the alpha stage means it currently serves research purposes.
- **License detail:** vigil-llm is licensed under the Apache-2.0 license, allowing for free use in both commercial and non-commercial projects while requiring any redistribution of the software to maintain the same open-s源

## Choose when

### Choose vigil-llm if…

- License: vigil-llm is Apache-2.0, llm-guard is MIT.
- Requirements: - Vigil supports local embeddings via sentence-transformers and can integrate with OpenAI's models.; - It is built as a Python library but also provides a REST API for more flexible integration..
- Both llm-guard and vigil-llm are security tools designed to protect against potential threats in Large Language Model interactions, such as prompt injection attacks.
- Tags unique to vigil-llm: adversarial-attacks, yara-scanner, llm-security.
- vigil-llm ships Docker support for self-hosted deployment.
- - When you need to detect prompt injections or jailbreaks in the inputs of LLM applications.

### Choose llm-guard if…

- License: llm-guard is MIT, vigil-llm is Apache-2.0.
- Both llm-guard and vigil-llm are security tools designed to protect against potential threats in Large Language Model interactions, such as prompt injection attacks.
- Tags unique to llm-guard: llmops, large-language-models, adversarial-machine-learning, chatgpt.
- Also covers LLM Frameworks.

## When NOT to use vigil-llm

- - If your project requires a stable, fully vetted solution given Vigil's current alpha stage status.
- - For production use cases that demand a more comprehensive and proven AI firewall technology over experimental tools.

## When NOT to use llm-guard

- llm-guard is archived on GitHub. Prefer an active alternative unless you maintain a private fork or need a frozen dependency.
- Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.

## Common questions

### What is the difference between vigil-llm and llm-guard?

vigil-llm: ⚡ Security scanner for Large Language Model prompts ⚡. llm-guard: The Security Toolkit for LLM Interactions. See the comparison table for live GitHub stats and shared categories.

### When should I choose vigil-llm over llm-guard?

Choose vigil-llm over llm-guard when License: vigil-llm is Apache-2.0, llm-guard is MIT; Requirements: - Vigil supports local embeddings via sentence-transformers and can integrate with OpenAI's models.; - It is built as a Python library but also provides a REST API for more flexible integration.; Both llm-guard and vigil-llm are security tools designed to protect against potential threats in Large Language Model interactions, such as prompt injection attacks; Tags unique to vigil-llm: adversarial-attacks, yara-scanner, llm-security; vigil-llm ships Docker support for self-hosted deployment; - When you need to detect prompt injections or jailbreaks in the inputs of LLM applications.

### When should I choose llm-guard over vigil-llm?

Choose llm-guard over vigil-llm when License: llm-guard is MIT, vigil-llm is Apache-2.0; Both llm-guard and vigil-llm are security tools designed to protect against potential threats in Large Language Model interactions, such as prompt injection attacks; Tags unique to llm-guard: llmops, large-language-models, adversarial-machine-learning, chatgpt; Also covers LLM Frameworks.

### When should I avoid vigil-llm?

- If your project requires a stable, fully vetted solution given Vigil's current alpha stage status. - For production use cases that demand a more comprehensive and proven AI firewall technology over experimental tools.

### When should I avoid llm-guard?

llm-guard is archived on GitHub. Prefer an active alternative unless you maintain a private fork or need a frozen dependency. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.

### Is vigil-llm or llm-guard more popular on GitHub?

llm-guard has more GitHub stars (3,162 vs 486). Stars measure visibility, not whether either tool fits your constraints.

### Are vigil-llm and llm-guard open source?

Yes - both are open-source projects on GitHub (vigil-llm: Apache-2.0, llm-guard: MIT).

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

GraphCanon lists graph-backed alternatives at /tools/deadbits-vigil-llm/alternatives and /tools/protectai-llm-guard/alternatives (/tools/deadbits-vigil-llm/alternatives.md, /tools/protectai-llm-guard/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 /compare/deadbits-vigil-llm-vs-protectai-llm-guard.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, vigil-llm or llm-guard?

vigil-llm: Dormant. llm-guard: Archived. 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 vigil-llm and llm-guard?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: vigil-llm: /tools/deadbits-vigil-llm/trust; llm-guard: /tools/protectai-llm-guard/trust.

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=deadbits-vigil-llm`](/api/graphcanon/graph?tool=deadbits-vigil-llm)
- 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/_