--- title: "vigil-llm vs virtual-prompt-injection" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/deadbits-vigil-llm-vs-wegodev2-virtual-prompt-injection" tools: ["deadbits-vigil-llm", "wegodev2-virtual-prompt-injection"] --- # vigil-llm vs virtual-prompt-injection *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 virtual-prompt-injection when tags unique to virtual-prompt-injection: backdoor attack, data poisoning, instruction-tuned large language models, model behavior manipulation. [vigil-llm](https://vigil.deadbits.ai/) reports 489 GitHub stars, 55 forks, and 16 open issues, last pushed Jan 31, 2024. [virtual-prompt-injection](https://github.com/wegodev2/virtual-prompt-injection) has 27 stars, 1 forks, and 0 open issues, last pushed Jul 6, 2024. Figures are from public GitHub metadata via [vigil-llm's repository](https://github.com/deadbits/vigil-llm) and [virtual-prompt-injection's repository](https://github.com/wegodev2/virtual-prompt-injection). | | [vigil-llm](/tools/deadbits-vigil-llm.md) | [virtual-prompt-injection](/tools/wegodev2-virtual-prompt-injection.md) | | --- | --- | --- | | Tagline | ⚡ Vigil ⚡ Detect prompt injections, jailbreaks, and other potentially risky Large Language Model (LLM) inputs | Backdooring instruction-tuned large language models using virtual prompt injection techniques. | | Stars | 489 | 27 | | Forks | 55 | 1 | | Open issues | 16 | 0 | | 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) | [virtual-prompt-injection](/tools/wegodev2-virtual-prompt-injection.md) | | --- | --- | --- | | Days since push | 891d | 735d | | Open issues (now) | 16 | 0 | | Full report | [trust report](/tools/deadbits-vigil-llm/trust.md) | [trust report](/tools/wegodev2-virtual-prompt-injection/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 virtual-prompt-injection if… - Tags unique to virtual-prompt-injection: backdoor attack, data poisoning, instruction-tuned large language models, model behavior manipulation. - More recently updated (last pushed Jul 6, 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 virtual-prompt-injection - Last GitHub push was 736 days ago (dormant maintenance, Jul 6, 2024). Validate activity before betting a new project on virtual-prompt-injection. - 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 virtual-prompt-injection? vigil-llm: ⚡ Vigil ⚡ Detect prompt injections, jailbreaks, and other potentially risky Large Language Model (LLM) inputs. virtual-prompt-injection: Backdooring instruction-tuned large language models using virtual prompt injection techniques.. See the comparison table for live GitHub stats and shared categories. ### When should I choose vigil-llm over virtual-prompt-injection? Choose vigil-llm over virtual-prompt-injection 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 virtual-prompt-injection over vigil-llm? Choose virtual-prompt-injection over vigil-llm when Tags unique to virtual-prompt-injection: backdoor attack, data poisoning, instruction-tuned large language models, model behavior manipulation; More recently updated (last pushed Jul 6, 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 virtual-prompt-injection? Last GitHub push was 736 days ago (dormant maintenance, Jul 6, 2024). Validate activity before betting a new project on virtual-prompt-injection. 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 virtual-prompt-injection more popular on GitHub? vigil-llm has more GitHub stars (489 vs 27). Stars measure visibility, not whether either tool fits your constraints. ### Are vigil-llm and virtual-prompt-injection open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to vigil-llm or virtual-prompt-injection? GraphCanon lists graph-backed alternatives at [vigil-llm alternatives](/tools/deadbits-vigil-llm/alternatives) and [virtual-prompt-injection alternatives](/tools/wegodev2-virtual-prompt-injection/alternatives) ([vigil-llm markdown twin](/tools/deadbits-vigil-llm/alternatives.md), [virtual-prompt-injection markdown twin](/tools/wegodev2-virtual-prompt-injection/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-wegodev2-virtual-prompt-injection.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, vigil-llm or virtual-prompt-injection? vigil-llm: Dormant. virtual-prompt-injection: 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 virtual-prompt-injection? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [vigil-llm trust report](/tools/deadbits-vigil-llm/trust); [virtual-prompt-injection trust report](/tools/wegodev2-virtual-prompt-injection/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/_