--- title: "multilingual-safety-for-LLMs vs JOOD" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/damo-nlp-sg-multilingual-safety-for-llms-vs-naver-ai-jood" tools: ["damo-nlp-sg-multilingual-safety-for-llms", "naver-ai-jood"] --- # multilingual-safety-for-LLMs vs JOOD *GraphCanon updated Aug 5, 2026* ## Verdict Pick multilingual-safety-for-LLMs if data for studying multilingual jailbreak safety in LLMs, including nine non-English languages categorized by resource availability; pick JOOD if jOOD is an implementation for exploring strategies to jailbreak language and multimodal models using out-of-distribution inputs. It leverages Python and is licensed under Apache-2.0. [multilingual-safety-for-LLMs](https://github.com/DAMO-NLP-SG/multilingual-safety-for-LLMs) reports 107 GitHub stars, 8 forks, and 0 open issues, last pushed Mar 7, 2024. [JOOD](https://github.com/naver-ai/JOOD) has 21 stars, 4 forks, and 2 open issues, last pushed Jun 11, 2025. Figures are from public GitHub metadata via [multilingual-safety-for-LLMs's repository](https://github.com/DAMO-NLP-SG/multilingual-safety-for-LLMs) and [JOOD's repository](https://github.com/naver-ai/JOOD). | | [multilingual-safety-for-LLMs](/tools/damo-nlp-sg-multilingual-safety-for-llms.md) | [JOOD](/tools/naver-ai-jood.md) | | --- | --- | --- | | Tagline | Data for Multilingual Jailbreak Challenges in Large Language Models | Implementation for multimodal LLM jailbreaking strategy | | Stars | 107 | 21 | | Forks | 8 | 4 | | Open issues | 0 | 2 | | Language | - | Python | | Adopt for | Data for studying multilingual jailbreak safety in LLMs, including nine non-English languages categorized by resource availability. | JOOD is an implementation for exploring strategies to jailbreak language and multimodal models using out-of-distribution inputs. It leverages Python and is licensed under Apache-2.0. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | Evaluation & Observability, Model Training | Computer Vision, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [multilingual-safety-for-LLMs](/tools/damo-nlp-sg-multilingual-safety-for-llms.md) | [JOOD](/tools/naver-ai-jood.md) | | --- | --- | --- | | Days since push | 880d | 419d | | Open issues (now) | 0 | 2 | | Full report | [trust report](/tools/damo-nlp-sg-multilingual-safety-for-llms/trust.md) | [trust report](/tools/naver-ai-jood/trust.md) | ## Decision facts: multilingual-safety-for-LLMs - **Adopt for:** Data for studying multilingual jailbreak safety in LLMs, including nine non-English languages categorized by resource availability. ## Decision facts: JOOD - **Requirements:** Python version to install requirements: Python >= 3.12.7; The package list for dependencies should be sourced from the `requirements.txt` file provided in the repository. - **Adopt for:** JOOD is an implementation for exploring strategies to jailbreak language and multimodal models using out-of-distribution inputs. It leverages Python and is licensed under Apache-2.0. ## Choose when ### Choose multilingual-safety-for-LLMs if… - License: multilingual-safety-for-LLMs is MIT, JOOD is Apache-2.0. - Tags unique to multilingual-safety-for-LLMs: jailbreak, llm, multilingual, safety. - Also covers Evaluation & Observability. - When evaluating the robustness of large language models against malicious prompts in multiple languages. ### Choose JOOD if… - License: JOOD is Apache-2.0, multilingual-safety-for-LLMs is MIT. - Requirements: Python version to install requirements: Python >= 3.12.7; The package list for dependencies should be sourced from the `requirements.txt` file provided in the repository.. - Tags unique to JOOD: jailbreaking, multimodal-llms. - Also covers Computer Vision. - Use JOOD when you need to explore how a multimodal model behaves with unforeseen or out-of-distribution inputs, thus pushing the boundaries of its conventional responses or outputs. ## When NOT to use multilingual-safety-for-LLMs - If solely focused on English-language security analysis, as this dataset emphasizes non-English prompts. - When the target audience for your LLM is limited to high-resource language speakers only. ## When NOT to use JOOD - Avoid using JOOD if jailbreaking strategies are not of interest, such as in scenarios requiring strict adherence to model limitations and ethical constraints. - JOOD may not be suitable if you require tools that focus on improving performance or stability of models rather than exploring unconventional behavior or vulnerabilities. ## Common questions ### What is the difference between multilingual-safety-for-LLMs and JOOD? multilingual-safety-for-LLMs: Data for Multilingual Jailbreak Challenges in Large Language Models. JOOD: Implementation for multimodal LLM jailbreaking strategy. See the comparison table for live GitHub stats and shared categories. ### When should I choose multilingual-safety-for-LLMs over JOOD? Choose multilingual-safety-for-LLMs over JOOD when License: multilingual-safety-for-LLMs is MIT, JOOD is Apache-2.0; Tags unique to multilingual-safety-for-LLMs: jailbreak, llm, multilingual, safety; Also covers Evaluation & Observability; When evaluating the robustness of large language models against malicious prompts in multiple languages. ### When should I choose JOOD over multilingual-safety-for-LLMs? Choose JOOD over multilingual-safety-for-LLMs when License: JOOD is Apache-2.0, multilingual-safety-for-LLMs is MIT; Requirements: Python version to install requirements: Python >= 3.12.7; The package list for dependencies should be sourced from the `requirements.txt` file provided in the repository.; Tags unique to JOOD: jailbreaking, multimodal-llms; Also covers Computer Vision; Use JOOD when you need to explore how a multimodal model behaves with unforeseen or out-of-distribution inputs, thus pushing the boundaries of its conventional responses or outputs. ### When should I avoid multilingual-safety-for-LLMs? If solely focused on English-language security analysis, as this dataset emphasizes non-English prompts. When the target audience for your LLM is limited to high-resource language speakers only. ### When should I avoid JOOD? Avoid using JOOD if jailbreaking strategies are not of interest, such as in scenarios requiring strict adherence to model limitations and ethical constraints. JOOD may not be suitable if you require tools that focus on improving performance or stability of models rather than exploring unconventional behavior or vulnerabilities. ### Is multilingual-safety-for-LLMs or JOOD more popular on GitHub? multilingual-safety-for-LLMs has more GitHub stars (107 vs 21). Stars measure visibility, not whether either tool fits your constraints. ### Are multilingual-safety-for-LLMs and JOOD open source? Yes - both are open-source projects on GitHub (multilingual-safety-for-LLMs: MIT, JOOD: Apache-2.0). ### Where can I find alternatives to multilingual-safety-for-LLMs or JOOD? GraphCanon lists graph-backed alternatives at [multilingual-safety-for-LLMs alternatives](/tools/damo-nlp-sg-multilingual-safety-for-llms/alternatives) and [JOOD alternatives](/tools/naver-ai-jood/alternatives) ([multilingual-safety-for-LLMs markdown twin](/tools/damo-nlp-sg-multilingual-safety-for-llms/alternatives.md), [JOOD markdown twin](/tools/naver-ai-jood/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/damo-nlp-sg-multilingual-safety-for-llms-vs-naver-ai-jood.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, multilingual-safety-for-LLMs or JOOD? multilingual-safety-for-LLMs: Dormant. JOOD: 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 multilingual-safety-for-LLMs and JOOD? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [multilingual-safety-for-LLMs trust report](/tools/damo-nlp-sg-multilingual-safety-for-llms/trust); [JOOD trust report](/tools/naver-ai-jood/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=damo-nlp-sg-multilingual-safety-for-llms`](/api/graphcanon/graph?tool=damo-nlp-sg-multilingual-safety-for-llms) - 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/_