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Comparison

Open-Prompt-Injection vs MultiPL-E

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 MultiPL-E if multiPL-E is a benchmark system translating Python-based coding challenges across multiple programming languages.

Markdown twin · Open-Prompt-Injection alternatives · MultiPL-E alternatives

GraphCanon updated Oct 8, 2026

11views this month

Open-Prompt-Injection logo

Open-Prompt-Injection

liu00222/Open-Prompt-Injection

★ 503pushed Sep 27, 2026
vs
MultiPL-E logo

MultiPL-E

nuprl/MultiPL-E

★ 316pushed Apr 12, 2026

Trust & integrity

SignalOpen-Prompt-InjectionMultiPL-E
Maintenance
Very active (6d since push)
As of Oct 4, 2026 · github_public_v1
Slowing (178d since push)
As of Oct 8, 2026 · github_public_v1
Provenance
Not a fork · Personal account
As of Oct 4, 2026 · github_public_v1
Not a fork · Organization account
As of Oct 8, 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
Open-Prompt-Injection trust reportMultiPL-E trust reportTrust methodology

Tagline

Open-Prompt-Injection
Benchmark and toolkit for prompt injection attacks and defenses in LLMs
MultiPL-E
A multi-programming language benchmark for LLMs

Stars

Open-Prompt-Injection
503
MultiPL-E
316

Forks

Open-Prompt-Injection
81
MultiPL-E
59

Open issues

Open-Prompt-Injection
2
MultiPL-E
16

Language

Open-Prompt-Injection
Python
MultiPL-E
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.
MultiPL-E
MultiPL-E is a benchmark system translating Python-based coding challenges across multiple programming languages.

Persona

Open-Prompt-Injection
-
MultiPL-E
-

Runtime

Open-Prompt-Injection
-
MultiPL-E
-

License

Open-Prompt-Injection
MIT
MultiPL-E
Other

Last pushed

Open-Prompt-Injection
Sep 27, 2026
MultiPL-E
Apr 12, 2026

Categories

Open-Prompt-Injection
Evaluation & Observability, LLM Frameworks
MultiPL-E
Evaluation & Observability, LLM Frameworks

Trust and health

Maintenance

Open-Prompt-Injection
Very active (96%)
MultiPL-E
Slowing (36%)

Days since push

Open-Prompt-Injection
6d
MultiPL-E
178d

Open issues (now)

Open-Prompt-Injection
2
MultiPL-E
16

Stars delta

Open-Prompt-Injection
+33 (30d)
MultiPL-E
+2 (30d)

Open issues delta

Open-Prompt-Injection
-12 (30d)
MultiPL-E
0 (30d)

Owner type

Open-Prompt-Injection
User
MultiPL-E
Organization

Full report

Open-Prompt-Injection
Trust report
MultiPL-E
Trust report

Shared compatibility

  • Python · Open-Prompt-Injection: Python runtime · MultiPL-E: Python runtime

Choose Open-Prompt-Injection if…

  • License: Open-Prompt-Injection is MIT, MultiPL-E is Other.
  • 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.

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.
GitHubDetails

Choose MultiPL-E if…

  • License: MultiPL-E is Other, Open-Prompt-Injection is MIT.
  • Pricing: Free to use but requires local compute resources and potentially licensed libraries.
  • Tags unique to MultiPL-E: ai benchmark, benchmarking, code-generation, multilingual benchmark.
  • Use MultiPL-E for evaluating large language models' performance on code generation tasks in different languages directly without needing to create new benchmarks from scratch.

When NOT to use MultiPL-E

  • Avoid using MultiPL-E if you need a more challenging benchmark; consider Ag-LiveCodeBench-X instead.
  • Do not use MultiPL-E if your evaluation environment lacks GPU resources for completion generation or does not support Docker or Podman for execution of generated code.
GitHubDetails

Explore

Open-Prompt-Injection trust report →MultiPL-E trust report →Evaluation & Observability category →LLM Frameworks category →All comparisonsStack workflowsTrending tools

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: Open-Prompt-Injection 503 · MultiPL-E 316 (synced Oct 4, 2026).

Common questions

What is the difference between Open-Prompt-Injection and MultiPL-E?
Open-Prompt-Injection: Benchmark and toolkit for prompt injection attacks and defenses in LLMs. MultiPL-E: A multi-programming language benchmark for LLMs. See the comparison table for live GitHub stats and shared categories.
When should I choose Open-Prompt-Injection over MultiPL-E?
Choose Open-Prompt-Injection over MultiPL-E when License: Open-Prompt-Injection is MIT, MultiPL-E is Other; 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.
When should I choose MultiPL-E over Open-Prompt-Injection?
Choose MultiPL-E over Open-Prompt-Injection when License: MultiPL-E is Other, Open-Prompt-Injection is MIT; Pricing: Free to use but requires local compute resources and potentially licensed libraries; Tags unique to MultiPL-E: ai benchmark, benchmarking, code-generation, multilingual benchmark; Use MultiPL-E for evaluating large language models' performance on code generation tasks in different languages directly without needing to create new benchmarks from scratch.
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 MultiPL-E?
Avoid using MultiPL-E if you need a more challenging benchmark; consider Ag-LiveCodeBench-X instead. Do not use MultiPL-E if your evaluation environment lacks GPU resources for completion generation or does not support Docker or Podman for execution of generated code.
Is Open-Prompt-Injection or MultiPL-E more popular on GitHub?
Open-Prompt-Injection has more GitHub stars (503 vs 316). Stars measure visibility, not whether either tool fits your constraints.
Are Open-Prompt-Injection and MultiPL-E open source?
Yes - both are open-source projects on GitHub (Open-Prompt-Injection: MIT, MultiPL-E: Other).
Where can I find alternatives to Open-Prompt-Injection or MultiPL-E?
GraphCanon lists graph-backed alternatives at Open-Prompt-Injection alternatives and MultiPL-E alternatives (Open-Prompt-Injection markdown twin, MultiPL-E 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 MultiPL-E?
Open-Prompt-Injection: Very active. MultiPL-E: 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 MultiPL-E?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Open-Prompt-Injection trust report; MultiPL-E trust report.

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