Comparison
Open-Prompt-Injection vs GPTFuzz
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 GPTFuzz if gPTFuzz leverages auto-generated jailbreak prompts to red team large language models for testing and evaluation.
Markdown twin · Open-Prompt-Injection alternatives · GPTFuzz alternatives
GraphCanon updated Oct 5, 2026
20views this month
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Trust & integrity
| Signal | Open-Prompt-Injection | GPTFuzz |
|---|---|---|
| Maintenance | Very active (6d since push) As of Oct 4, 2026 · github_public_v1 | Slowing (219d since push) As of Oct 5, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Oct 4, 2026 · github_public_v1 | Not a fork · Personal account As of Oct 5, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 2026 · 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
- GPTFuzz
- Red Teaming Large Language Models with Auto-Generated Jailbreak Prompts
Stars
- Open-Prompt-Injection
- 503
- GPTFuzz
- 611
Forks
- Open-Prompt-Injection
- 81
- GPTFuzz
- 87
Open issues
- Open-Prompt-Injection
- 2
- GPTFuzz
- 17
Language
- Open-Prompt-Injection
- Python
- GPTFuzz
- 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.
- GPTFuzz
- GPTFuzz leverages auto-generated jailbreak prompts to red team large language models for testing and evaluation.
Persona
- Open-Prompt-Injection
- -
- GPTFuzz
- -
Runtime
- Open-Prompt-Injection
- -
- GPTFuzz
- -
License
- Open-Prompt-Injection
- MIT
- GPTFuzz
- MIT
Last pushed
- Open-Prompt-Injection
- Sep 27, 2026
- GPTFuzz
- Feb 27, 2026
Categories
- Open-Prompt-Injection
- Evaluation & Observability, LLM Frameworks
- GPTFuzz
- Evaluation & Observability, LLM Frameworks
Trust and health
Maintenance
- Open-Prompt-Injection
- Very active (96%)
- GPTFuzz
- Slowing (36%)
Days since push
- Open-Prompt-Injection
- 6d
- GPTFuzz
- 219d
Open issues (now)
- Open-Prompt-Injection
- 2
- GPTFuzz
- 17
Stars delta
- Open-Prompt-Injection
- +33 (30d)
- GPTFuzz
- +3 (30d)
Open issues delta
- Open-Prompt-Injection
- -12 (30d)
- GPTFuzz
- 0 (30d)
Full report
- Open-Prompt-Injection
- Trust report
- GPTFuzz
- Trust report
Choose Open-Prompt-Injection if…
- Tags unique to Open-Prompt-Injection: llm, llm-security, prompt-injection, security-and-privacy.
- You prioritize security testing specifically for prompt injection vulnerabilities in your LLM applications.
- More recently updated (last pushed Sep 27, 2026).
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 GPTFuzz if…
- Tags unique to GPTFuzz: jailbreak prompts, large-language-models, red-teaming.
- When you need to test the robustness of LLMs against potential manipulative input designed to bypass content controls.
- More GitHub stars (611 vs 503) - visibility, not fit.
When NOT to use GPTFuzz
- If your project requires straightforward, uncontroversial testing tools that do not engage with sensitive content control evasion techniques.
- For general-purpose debugging and optimization tasks where red teaming tactics are not necessary or appropriate.
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 Oct 4, 2026
- GitHub forks (liu00222/Open-Prompt-Injection) · observed Oct 4, 2026
- Last push (liu00222/Open-Prompt-Injection) · observed Sep 27, 2026
- License file (MIT) · observed Oct 4, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (sherdencooper/GPTFuzz) · observed Oct 5, 2026
- GitHub forks (sherdencooper/GPTFuzz) · observed Oct 5, 2026
- Last push (sherdencooper/GPTFuzz) · observed Feb 27, 2026
- License file (MIT) · observed Oct 5, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: Open-Prompt-Injection 503 · GPTFuzz 611 (synced Oct 4, 2026).
Common questions
- What is the difference between Open-Prompt-Injection and GPTFuzz?
- Open-Prompt-Injection: Benchmark and toolkit for prompt injection attacks and defenses in LLMs. GPTFuzz: Red Teaming Large Language Models with Auto-Generated Jailbreak Prompts. See the comparison table for live GitHub stats and shared categories.
- When should I choose Open-Prompt-Injection over GPTFuzz?
- Choose Open-Prompt-Injection over GPTFuzz when Tags unique to Open-Prompt-Injection: llm, llm-security, prompt-injection, security-and-privacy; You prioritize security testing specifically for prompt injection vulnerabilities in your LLM applications; More recently updated (last pushed Sep 27, 2026).
- When should I choose GPTFuzz over Open-Prompt-Injection?
- Choose GPTFuzz over Open-Prompt-Injection when Tags unique to GPTFuzz: jailbreak prompts, large-language-models, red-teaming; When you need to test the robustness of LLMs against potential manipulative input designed to bypass content controls; More GitHub stars (611 vs 503) - visibility, not fit.
- 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 GPTFuzz?
- If your project requires straightforward, uncontroversial testing tools that do not engage with sensitive content control evasion techniques. For general-purpose debugging and optimization tasks where red teaming tactics are not necessary or appropriate.
- Is Open-Prompt-Injection or GPTFuzz more popular on GitHub?
- GPTFuzz has more GitHub stars (611 vs 503). Stars measure visibility, not whether either tool fits your constraints.
- Are Open-Prompt-Injection and GPTFuzz open source?
- Yes - both are open-source projects on GitHub (Open-Prompt-Injection: MIT, GPTFuzz: MIT).
- Where can I find alternatives to Open-Prompt-Injection or GPTFuzz?
- GraphCanon lists graph-backed alternatives at Open-Prompt-Injection alternatives and GPTFuzz alternatives (Open-Prompt-Injection markdown twin, GPTFuzz 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 GPTFuzz?
- Open-Prompt-Injection: Very active. GPTFuzz: Slowing. 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 GPTFuzz?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Open-Prompt-Injection trust report; GPTFuzz trust report.