GraphCanon updated 4w · GitHub synced 4w
Decision brief
Vigil-llm is designed for users who need robust security measures to protect against prompt injections and jailbreak attempts in LLMs.
Good fit when
- When deploying large language models that require high levels of input security, vigil-llm can be employed to detect maliciously crafted inputs intended to manipulate model behavior.
- In environments where adversarial machine learning is a risk, vigil-llm's capability to identify prompt injections makes it an essential tool for safeguarding LLMs.
Avoid when
- If your application does not require high security against malicious inputs or if the risks of prompt injection are minimal due to controlled input sources, vigil-llm might be unnecessary.
- For projects that focus on optimizing output speed rather than input robustness, other tools might be more appropriate as vigil-llm could add significant processing overhead.
Observed Jul 15, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Dormant (901d since push)
- As of 4w
- Provenance
- Not a fork · Personal account
- As of 4w
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install vigil-llmHow it fits your stack(8)
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Evidence and technical details
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Overview
Vigil is a tool designed for detecting prompt injections and jailbreak attempts aimed at Large Language Models, falling under the category of Evaluation & Observability.
Capability facts
- Deploy
- Self-host
Source: dockerfile:Dockerfile · Jul 21, 2026
- Docker
- Dockerfile present
Source: dockerfile:Dockerfile · Jul 21, 2026
- Languages
- python
Source: github.language · Jul 21, 2026
Categories
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Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Tags
README
Install Vigil 🛠️
Follow the steps below to install Vigil
A Docker container is also available, but this is not currently recommended.
Install YARA
Follow the instructions on the YARA Getting Started documentation to download and install YARA v4.3.2.
Install Vigil library
Inside your virutal environment, install the application:
pip install -e .
For agents
This page has a .md twin and JSON over the API.