Comparison
Open-Prompt-Injection vs MGDebugger
Verdict
Pick Open-Prompt-Injection if open-Prompt-Injection is a Python-based toolkit for benchmarking prompt injection attacks on LLMs, offering customization through config files and support for various LLM APIs; pick MGDebugger if mGDebugger offers hierarchical debugging for various levels of code granularity, emphasizing efficient error resolution and improved debug accuracy.
Markdown twin · Open-Prompt-Injection alternatives · MGDebugger alternatives
GraphCanon updated 2w
vs
Trust & integrity
| Signal | Open-Prompt-Injection | MGDebugger |
|---|---|---|
| Maintenance | Slowing (279d since push) As of 2w · github_public_v1 | Dormant (395d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 2w · github_public_v1 | Not a fork · Personal account As of 2w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | Published findings 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
- Open-Prompt-Injection
- Benchmark and toolkit for prompt injection attacks and defenses in LLMs
- MGDebugger
- Multi-Granularity LLM Debugger
Stars
- Open-Prompt-Injection
- 470
- MGDebugger
- 101
Forks
- Open-Prompt-Injection
- 74
- MGDebugger
- 10
Open issues
- Open-Prompt-Injection
- 14
- MGDebugger
- 0
Language
- Open-Prompt-Injection
- Python
- MGDebugger
- Python
Adopt for
- Open-Prompt-Injection
- Open-Prompt-Injection is a Python-based toolkit for benchmarking prompt injection attacks on LLMs, offering customization through config files and support for various LLM APIs.
- MGDebugger
- MGDebugger offers hierarchical debugging for various levels of code granularity, emphasizing efficient error resolution and improved debug accuracy.
Persona
- Open-Prompt-Injection
- -
- MGDebugger
- -
Runtime
- Open-Prompt-Injection
- -
- MGDebugger
- -
License
- Open-Prompt-Injection
- MIT
- MGDebugger
- MIT
Last pushed
- Open-Prompt-Injection
- Oct 29, 2025
- MGDebugger
- Jul 6, 2025
Categories
- Open-Prompt-Injection
- Evaluation & Observability, LLM Frameworks
- MGDebugger
- Evaluation & Observability, LLM Frameworks
Trust and health
Maintenance
- Open-Prompt-Injection
- Slowing (36%)
- MGDebugger
- Dormant (18%)
Days since push
- Open-Prompt-Injection
- 279d
- MGDebugger
- 395d
Open issues (now)
- Open-Prompt-Injection
- 14
- MGDebugger
- 0
OSV dependency advisories
- Open-Prompt-Injection
- No lockfile (source not queried)
- MGDebugger
- Published findings
Full report
- Open-Prompt-Injection
- Trust report
- MGDebugger
- Trust report
Shared compatibility
- Python · Open-Prompt-Injection: Python runtime · MGDebugger: Python runtime
Choose Open-Prompt-Injection if…
- Tags unique to Open-Prompt-Injection: llm security, prompt-injection, security-and-privacy.
- You prioritize security testing specifically for prompt injection vulnerabilities in your LLM applications.
- More GitHub stars (470 vs 101) - visibility, not fit.
When NOT to use Open-Prompt-Injection
- You require broader, more generalized security features not centered on prompt injection attacks.
- Your project does not involve working with Google PaLM2 or other specific models like Meta's Llama and OpenAI's GPT.
Choose MGDebugger if…
- Pricing: MGDebugger is free to use under MIT license but may require users to manage model hosting costs and dependencies..
- Requirements: Min 4 GB RAM; Requires Python version 3.8 or later; vLLM version 0.6.0 or later must be installed for model inference.
- Tags unique to MGDebugger: automatic-program-repair, code generation, debugger, large language models.
- When you need to perform granular analysis on complex codes, progressing from subfunctions to the whole system to ensure precise error detection and correction.
When NOT to use MGDebugger
- Avoid using MGDebugger if you operate primarily on Mac systems and do not require support for quantized models (as some essential dependencies are unsupported on MacOS).
- If your model does not align well with the DeepSeek-Coder-V2-Lite-Instruct or similar models, since the effectiveness of MGDebugger might vary without support for those particular frameworks.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (liu00222/Open-Prompt-Injection) · observed Aug 5, 2026
- GitHub forks (liu00222/Open-Prompt-Injection) · observed Aug 5, 2026
- Last push (liu00222/Open-Prompt-Injection) · observed Oct 29, 2025
- License file (MIT) · observed Aug 5, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (YerbaPage/MGDebugger) · observed Aug 5, 2026
- GitHub forks (YerbaPage/MGDebugger) · observed Aug 5, 2026
- Last push (YerbaPage/MGDebugger) · observed Jul 6, 2025
- License file (MIT) · observed Aug 5, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: Open-Prompt-Injection 470 · MGDebugger 101 (synced Aug 5, 2026).
Common questions
- What is the difference between Open-Prompt-Injection and MGDebugger?
- Open-Prompt-Injection: Benchmark and toolkit for prompt injection attacks and defenses in LLMs. MGDebugger: Multi-Granularity LLM Debugger. See the comparison table for live GitHub stats and shared categories.
- When should I choose Open-Prompt-Injection over MGDebugger?
- Choose Open-Prompt-Injection over MGDebugger when Tags unique to Open-Prompt-Injection: llm security, prompt-injection, security-and-privacy; You prioritize security testing specifically for prompt injection vulnerabilities in your LLM applications; More GitHub stars (470 vs 101) - visibility, not fit.
- When should I choose MGDebugger over Open-Prompt-Injection?
- Choose MGDebugger over Open-Prompt-Injection when Pricing: MGDebugger is free to use under MIT license but may require users to manage model hosting costs and dependencies.; Requirements: Min 4 GB RAM; Requires Python version 3.8 or later; vLLM version 0.6.0 or later must be installed for model inference; Tags unique to MGDebugger: automatic-program-repair, code generation, debugger, large language models; When you need to perform granular analysis on complex codes, progressing from subfunctions to the whole system to ensure precise error detection and correction.
- When should I avoid Open-Prompt-Injection?
- You require broader, more generalized security features not centered on prompt injection attacks. Your project does not involve working with Google PaLM2 or other specific models like Meta's Llama and OpenAI's GPT.
- When should I avoid MGDebugger?
- Avoid using MGDebugger if you operate primarily on Mac systems and do not require support for quantized models (as some essential dependencies are unsupported on MacOS). If your model does not align well with the DeepSeek-Coder-V2-Lite-Instruct or similar models, since the effectiveness of MGDebugger might vary without support for those particular frameworks.
- Is Open-Prompt-Injection or MGDebugger more popular on GitHub?
- Open-Prompt-Injection has more GitHub stars (470 vs 101). Stars measure visibility, not whether either tool fits your constraints.
- Are Open-Prompt-Injection and MGDebugger open source?
- Yes - both are open-source projects on GitHub (Open-Prompt-Injection: MIT, MGDebugger: MIT).
- Where can I find alternatives to Open-Prompt-Injection or MGDebugger?
- GraphCanon lists graph-backed alternatives at Open-Prompt-Injection alternatives and MGDebugger alternatives (Open-Prompt-Injection markdown twin, MGDebugger 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, Open-Prompt-Injection or MGDebugger?
- Open-Prompt-Injection: Slowing. MGDebugger: 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 Open-Prompt-Injection and MGDebugger?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Open-Prompt-Injection trust report; MGDebugger trust report.