---
title: "vigil-llm vs IB4LLMs"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/deadbits-vigil-llm-vs-zichuan-liu-ib4llms"
tools: ["deadbits-vigil-llm", "zichuan-liu-ib4llms"]
---

# vigil-llm vs IB4LLMs

*GraphCanon updated Jul 12, 2026*

## Verdict

Pick vigil-llm 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.; pick IB4LLMs when tags unique to IB4LLMs: adversarial prompts defense, information bottleneck, jailbreak defense, llms protection.

[vigil-llm](https://vigil.deadbits.ai/) reports 489 GitHub stars, 55 forks, and 16 open issues, last pushed Jan 31, 2024. [IB4LLMs](https://zichuan-liu.github.io/projects/IBProtector/index.html) has 25 stars, 2 forks, and 4 open issues, last pushed Nov 7, 2024. Figures are from public GitHub metadata via [vigil-llm's repository](https://github.com/deadbits/vigil-llm) and [IB4LLMs's repository](https://github.com/zichuan-liu/IB4LLMs).

| | [vigil-llm](/tools/deadbits-vigil-llm.md) | [IB4LLMs](/tools/zichuan-liu-ib4llms.md) |
| --- | --- | --- |
| Tagline | ⚡ Vigil ⚡ Detect prompt injections, jailbreaks, and other potentially risky Large Language Model (LLM) inputs | Protecting Your LLMs with Information Bottleneck |
| Stars | 489 | 25 |
| Forks | 55 | 2 |
| Open issues | 16 | 4 |
| Language | Python | Python |
| 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. | - |
| Persona | - | - |
| Runtime | - | - |
| License | Apache-2.0 | - |
| Categories | Evaluation & Observability, LLM Frameworks, Vector Databases | Evaluation & Observability, LLM Frameworks |

## Trust and health

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

| | [vigil-llm](/tools/deadbits-vigil-llm.md) | [IB4LLMs](/tools/zichuan-liu-ib4llms.md) |
| --- | --- | --- |
| Days since push | 891d | 611d |
| Open issues (now) | 16 | 4 |
| Security scan | No lockfile | 77 low (77 low) |
| Full report | [trust report](/tools/deadbits-vigil-llm/trust.md) | [trust report](/tools/zichuan-liu-ib4llms/trust.md) |

## 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 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 Vector Databases.
- When integrating large language models into applications that need robust protection against prompt injection attacks.

### Choose IB4LLMs if…

- Tags unique to IB4LLMs: adversarial prompts defense, information bottleneck, jailbreak defense, llms protection.
- More recently updated (last pushed Nov 7, 2024).

## 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.

## When NOT to use IB4LLMs

- Last GitHub push was 612 days ago (dormant maintenance, Nov 7, 2024). Validate activity before betting a new project on IB4LLMs.
- 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 IB4LLMs?

vigil-llm: ⚡ Vigil ⚡ Detect prompt injections, jailbreaks, and other potentially risky Large Language Model (LLM) inputs. IB4LLMs: Protecting Your LLMs with Information Bottleneck. See the comparison table for live GitHub stats and shared categories.

### When should I choose vigil-llm over IB4LLMs?

Choose vigil-llm over IB4LLMs 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 Vector Databases; When integrating large language models into applications that need robust protection against prompt injection attacks.

### When should I choose IB4LLMs over vigil-llm?

Choose IB4LLMs over vigil-llm when Tags unique to IB4LLMs: adversarial prompts defense, information bottleneck, jailbreak defense, llms protection; More recently updated (last pushed Nov 7, 2024).

### 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.

### When should I avoid IB4LLMs?

Last GitHub push was 612 days ago (dormant maintenance, Nov 7, 2024). Validate activity before betting a new project on IB4LLMs. 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 IB4LLMs more popular on GitHub?

vigil-llm has more GitHub stars (489 vs 25). Stars measure visibility, not whether either tool fits your constraints.

### Are vigil-llm and IB4LLMs open source?

Yes - both are open-source projects on GitHub.

### Where can I find alternatives to vigil-llm or IB4LLMs?

GraphCanon lists graph-backed alternatives at [vigil-llm alternatives](/tools/deadbits-vigil-llm/alternatives) and [IB4LLMs alternatives](/tools/zichuan-liu-ib4llms/alternatives) ([vigil-llm markdown twin](/tools/deadbits-vigil-llm/alternatives.md), [IB4LLMs markdown twin](/tools/zichuan-liu-ib4llms/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/deadbits-vigil-llm-vs-zichuan-liu-ib4llms.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, vigil-llm or IB4LLMs?

vigil-llm: Dormant. IB4LLMs: 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 vigil-llm and IB4LLMs?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [vigil-llm trust report](/tools/deadbits-vigil-llm/trust); [IB4LLMs trust report](/tools/zichuan-liu-ib4llms/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/_
