Comparison
JOOD vs Visual-Adversarial-Examples-Jailbreak-Large-Language-Models
Verdict
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; pick Visual-Adversarial-Examples-Jailbreak-Large-Language-Models if this tool focuses on generating and studying visual adversarial examples designed to exploit vulnerabilities in large language models such as MiniGPT-4.
Markdown twin · JOOD alternatives · Visual-Adversarial-Examples-Jailbreak-Large-Language-Models alternatives
GraphCanon updated 2w
vs
Visual-Adversarial-Examples-Jailbreak-Large-Language-Models
Unispac/Visual-Adversarial-Examples-Jailbreak-Large-Language-Models
★ 282pushed May 13, 2024
Trust & integrity
| Signal | JOOD | Visual-Adversarial-Examples-Jailbreak-Large-Language-Models |
|---|---|---|
| Maintenance | Dormant (419d since push) As of 2w · github_public_v1 | Dormant (813d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2w · github_public_v1 | Not a fork · Personal account As of 2w · github_public_v1 |
| OSV dependency advisories | Published findings As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- JOOD
- Implementation for multimodal LLM jailbreaking strategy
- Visual-Adversarial-Examples-Jailbreak-Large-Language-Models
- Repository for visual adversarial examples that jailbreak large language models
Stars
- JOOD
- 21
- Visual-Adversarial-Examples-Jailbreak-Large-Language-Models
- 282
Forks
- JOOD
- 4
- Visual-Adversarial-Examples-Jailbreak-Large-Language-Models
- 30
Open issues
- JOOD
- 2
- Visual-Adversarial-Examples-Jailbreak-Large-Language-Models
- 24
Language
- JOOD
- Python
- Visual-Adversarial-Examples-Jailbreak-Large-Language-Models
- Python
Adopt for
- JOOD
- 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.
- Visual-Adversarial-Examples-Jailbreak-Large-Language-Models
- This tool focuses on generating and studying visual adversarial examples designed to exploit vulnerabilities in large language models such as MiniGPT-4.
Persona
- JOOD
- -
- Visual-Adversarial-Examples-Jailbreak-Large-Language-Models
- -
Runtime
- JOOD
- -
- Visual-Adversarial-Examples-Jailbreak-Large-Language-Models
- -
License
- JOOD
- Apache-2.0
- Visual-Adversarial-Examples-Jailbreak-Large-Language-Models
- -
Last pushed
- JOOD
- Jun 11, 2025
- Visual-Adversarial-Examples-Jailbreak-Large-Language-Models
- May 13, 2024
Categories
- JOOD
- Computer Vision, Model Training
- Visual-Adversarial-Examples-Jailbreak-Large-Language-Models
- Computer Vision, Model Training
Trust and health
Days since push
- JOOD
- 419d
- Visual-Adversarial-Examples-Jailbreak-Large-Language-Models
- 813d
Open issues (now)
- JOOD
- 2
- Visual-Adversarial-Examples-Jailbreak-Large-Language-Models
- 24
Owner type
- JOOD
- Organization
- Visual-Adversarial-Examples-Jailbreak-Large-Language-Models
- User
OSV dependency advisories
- JOOD
- Published findings
- Visual-Adversarial-Examples-Jailbreak-Large-Language-Models
- No lockfile (source not queried)
Full report
- JOOD
- Trust report
- Visual-Adversarial-Examples-Jailbreak-Large-Language-Models
- Trust report
Choose JOOD if…
- 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.
- 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 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.
Choose Visual-Adversarial-Examples-Jailbreak-Large-Language-Models if…
- Tags unique to Visual-Adversarial-Examples-Jailbreak-Large-Language-Models: large-language-model, visual adversarial.
- If your goal is to research the resilience of Large Language Models against visual inputs that could mislead or 'jailbreak' their usual behavior.
- More GitHub stars (282 vs 21) - visibility, not fit.
When NOT to use Visual-Adversarial-Examples-Jailbreak-Large-Language-Models
- Avoid using this tool if your objective does not involve security testing or research concerning visual-linguistic interactions with large language models.
- If you are looking to enhance general-purpose AI applications without considering adversarial attacks, other frameworks would be more appropriate.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (naver-ai/JOOD) · observed Aug 5, 2026
- GitHub forks (naver-ai/JOOD) · observed Aug 5, 2026
- Last push (naver-ai/JOOD) · observed Jun 11, 2025
- License file (Apache-2.0) · observed Aug 5, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (Unispac/Visual-Adversarial-Examples-Jailbreak-Large-Language-Models) · observed Aug 5, 2026
- GitHub forks (Unispac/Visual-Adversarial-Examples-Jailbreak-Large-Language-Models) · observed Aug 5, 2026
- Last push (Unispac/Visual-Adversarial-Examples-Jailbreak-Large-Language-Models) · observed May 13, 2024
- License file (unknown) · observed Aug 5, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: JOOD 21 · Visual-Adversarial-Examples-Jailbreak-Large-Language-Models 282 (synced Aug 5, 2026).
Common questions
- What is the difference between JOOD and Visual-Adversarial-Examples-Jailbreak-Large-Language-Models?
- JOOD: Implementation for multimodal LLM jailbreaking strategy. Visual-Adversarial-Examples-Jailbreak-Large-Language-Models: Repository for visual adversarial examples that jailbreak large language models. See the comparison table for live GitHub stats and shared categories.
- When should I choose JOOD over Visual-Adversarial-Examples-Jailbreak-Large-Language-Models?
- Choose JOOD over Visual-Adversarial-Examples-Jailbreak-Large-Language-Models when Requirements: Python version to install requirements: Python >= 3.12.7; The package list for dependencies should be sourced from the
requirements.txtfile provided in the repository.; Tags unique to JOOD: jailbreaking, multimodal-llms; 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 choose Visual-Adversarial-Examples-Jailbreak-Large-Language-Models over JOOD?
- Choose Visual-Adversarial-Examples-Jailbreak-Large-Language-Models over JOOD when Tags unique to Visual-Adversarial-Examples-Jailbreak-Large-Language-Models: large-language-model, visual adversarial; If your goal is to research the resilience of Large Language Models against visual inputs that could mislead or 'jailbreak' their usual behavior; More GitHub stars (282 vs 21) - visibility, not fit.
- 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.
- When should I avoid Visual-Adversarial-Examples-Jailbreak-Large-Language-Models?
- Avoid using this tool if your objective does not involve security testing or research concerning visual-linguistic interactions with large language models. If you are looking to enhance general-purpose AI applications without considering adversarial attacks, other frameworks would be more appropriate.
- Is JOOD or Visual-Adversarial-Examples-Jailbreak-Large-Language-Models more popular on GitHub?
- Visual-Adversarial-Examples-Jailbreak-Large-Language-Models has more GitHub stars (282 vs 21). Stars measure visibility, not whether either tool fits your constraints.
- Are JOOD and Visual-Adversarial-Examples-Jailbreak-Large-Language-Models open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to JOOD or Visual-Adversarial-Examples-Jailbreak-Large-Language-Models?
- GraphCanon lists graph-backed alternatives at JOOD alternatives and Visual-Adversarial-Examples-Jailbreak-Large-Language-Models alternatives (JOOD markdown twin, Visual-Adversarial-Examples-Jailbreak-Large-Language-Models markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, JOOD or Visual-Adversarial-Examples-Jailbreak-Large-Language-Models?
- JOOD: Dormant. Visual-Adversarial-Examples-Jailbreak-Large-Language-Models: 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 JOOD and Visual-Adversarial-Examples-Jailbreak-Large-Language-Models?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: JOOD trust report; Visual-Adversarial-Examples-Jailbreak-Large-Language-Models trust report.