--- title: "chatgpt-plugin-eval vs BIPIA" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/llm-platform-security-chatgpt-plugin-eval-vs-microsoft-bipia" tools: ["llm-platform-security-chatgpt-plugin-eval", "microsoft-bipia"] --- # chatgpt-plugin-eval vs BIPIA *GraphCanon updated Aug 5, 2026* ## Verdict Pick chatgpt-plugin-eval if chatgpt-plugin-eval is an evaluation framework designed specifically to assess security, privacy, and safety concerns related to third-party plugins interfacing with large language models like ChatGPT; pick BIPIA if bIPIA, developed by Microsoft, is a benchmarking tool designed to assess the robustness and security of Large Language Models (LLMs) against indirect prompt injection attacks. [chatgpt-plugin-eval](https://llm-platform-security.github.io/chatgpt-plugin-eval/) reports 29 GitHub stars, 7 forks, and 1 open issues, last pushed Jul 29, 2024. [BIPIA](https://github.com/microsoft/BIPIA) has 149 stars, 19 forks, and 4 open issues, last pushed Apr 15, 2024. Figures are from public GitHub metadata via [chatgpt-plugin-eval's repository](https://github.com/llm-platform-security/chatgpt-plugin-eval) and [BIPIA's repository](https://github.com/microsoft/BIPIA). | | [chatgpt-plugin-eval](/tools/llm-platform-security-chatgpt-plugin-eval.md) | [BIPIA](/tools/microsoft-bipia.md) | | --- | --- | --- | | Tagline | Framework for Evaluating Security in LLM Plugin Ecosystems | Benchmark for evaluating LLM robustness to indirect prompt injection attacks. | | Stars | 29 | 149 | | Forks | 7 | 19 | | Open issues | 1 | 4 | | Language | HTML | Python | | Adopt for | chatgpt-plugin-eval is an evaluation framework designed specifically to assess security, privacy, and safety concerns related to third-party plugins interfacing with large language models like ChatGPT. | BIPIA, developed by Microsoft, is a benchmarking tool designed to assess the robustness and security of Large Language Models (LLMs) against indirect prompt injection attacks. | | Persona | - | - | | Runtime | - | - | | License | The license information for chatgpt-plugin-eval is unknown. | Other | | Categories | Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [chatgpt-plugin-eval](/tools/llm-platform-security-chatgpt-plugin-eval.md) | [BIPIA](/tools/microsoft-bipia.md) | | --- | --- | --- | | Days since push | 736d | 842d | | Open issues (now) | 1 | 4 | | Full report | [trust report](/tools/llm-platform-security-chatgpt-plugin-eval/trust.md) | [trust report](/tools/microsoft-bipia/trust.md) | ## Decision facts: chatgpt-plugin-eval - **Pricing:** freemium - **Adopt for:** chatgpt-plugin-eval is an evaluation framework designed specifically to assess security, privacy, and safety concerns related to third-party plugins interfacing with large language models like ChatGPT. - **License detail:** The license information for chatgpt-plugin-eval is unknown. ## Decision facts: BIPIA - **Requirements:** For API-based model experiments (like GPT), no GPU is needed but an account's API key must be set up.; For open-source models of 13B or below, test on a machine with at least 2 V100 GPUs. For larger models over 13B, 4-8 V100 GPUs are required. - **Adopt for:** BIPIA, developed by Microsoft, is a benchmarking tool designed to assess the robustness and security of Large Language Models (LLMs) against indirect prompt injection attacks. ## Choose when ### Choose chatgpt-plugin-eval if… - chatgpt-plugin-eval is primarily HTML; BIPIA is Python. - Tags unique to chatgpt-plugin-eval: chatgpt, llm-plugins, privacy, security. - - When evaluating the security risks of integrating third-party services into your LLM platform through plugins ### Choose BIPIA if… - BIPIA is primarily Python; chatgpt-plugin-eval is HTML. - Requirements: For API-based model experiments (like GPT), no GPU is needed but an account's API key must be set up.; For open-source models of 13B or below, test on a machine with at least 2 V100 GPUs. For larger models over 13B, 4-8 V100 GPUs are required.. - Tags unique to BIPIA: indirect-prompt-injection-attacks, llm security, microsoft-research, python library. - Use BIPIA when you need to evaluate your LLM's resilience specifically to indirect prompt injection attacks, a niche but critical type of adversarial attack. ## When NOT to use chatgpt-plugin-eval - - In cases where only generic, high-level security guidance is required without an in-depth framework analysis - - When the primary focus is on improving performance metrics rather than addressing specific security and privacy concerns of LLM plugins ## When NOT to use BIPIA - Avoid BIPIA if your primary focus is on general security enhancements without a particular emphasis on indirect prompt injection attacks. - Not recommended for users who primarily operate outside a Linux environment, specifically Ubuntu 20.04.6, as it can significantly affect compatibility and performance. ## Common questions ### What is the difference between chatgpt-plugin-eval and BIPIA? chatgpt-plugin-eval: Framework for Evaluating Security in LLM Plugin Ecosystems. BIPIA: Benchmark for evaluating LLM robustness to indirect prompt injection attacks.. See the comparison table for live GitHub stats and shared categories. ### When should I choose chatgpt-plugin-eval over BIPIA? Choose chatgpt-plugin-eval over BIPIA when chatgpt-plugin-eval is primarily HTML; BIPIA is Python; Tags unique to chatgpt-plugin-eval: chatgpt, llm-plugins, privacy, security; - When evaluating the security risks of integrating third-party services into your LLM platform through plugins. ### When should I choose BIPIA over chatgpt-plugin-eval? Choose BIPIA over chatgpt-plugin-eval when BIPIA is primarily Python; chatgpt-plugin-eval is HTML; Requirements: For API-based model experiments (like GPT), no GPU is needed but an account's API key must be set up.; For open-source models of 13B or below, test on a machine with at least 2 V100 GPUs. For larger models over 13B, 4-8 V100 GPUs are required.; Tags unique to BIPIA: indirect-prompt-injection-attacks, llm security, microsoft-research, python library; Use BIPIA when you need to evaluate your LLM's resilience specifically to indirect prompt injection attacks, a niche but critical type of adversarial attack. ### When should I avoid chatgpt-plugin-eval? - In cases where only generic, high-level security guidance is required without an in-depth framework analysis - When the primary focus is on improving performance metrics rather than addressing specific security and privacy concerns of LLM plugins ### When should I avoid BIPIA? Avoid BIPIA if your primary focus is on general security enhancements without a particular emphasis on indirect prompt injection attacks. Not recommended for users who primarily operate outside a Linux environment, specifically Ubuntu 20.04.6, as it can significantly affect compatibility and performance. ### Is chatgpt-plugin-eval or BIPIA more popular on GitHub? BIPIA has more GitHub stars (149 vs 29). Stars measure visibility, not whether either tool fits your constraints. ### Are chatgpt-plugin-eval and BIPIA open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to chatgpt-plugin-eval or BIPIA? GraphCanon lists graph-backed alternatives at [chatgpt-plugin-eval alternatives](/tools/llm-platform-security-chatgpt-plugin-eval/alternatives) and [BIPIA alternatives](/tools/microsoft-bipia/alternatives) ([chatgpt-plugin-eval markdown twin](/tools/llm-platform-security-chatgpt-plugin-eval/alternatives.md), [BIPIA markdown twin](/tools/microsoft-bipia/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/llm-platform-security-chatgpt-plugin-eval-vs-microsoft-bipia.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, chatgpt-plugin-eval or BIPIA? chatgpt-plugin-eval: Dormant. BIPIA: 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 chatgpt-plugin-eval and BIPIA? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [chatgpt-plugin-eval trust report](/tools/llm-platform-security-chatgpt-plugin-eval/trust); [BIPIA trust report](/tools/microsoft-bipia/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=llm-platform-security-chatgpt-plugin-eval`](/api/graphcanon/graph?tool=llm-platform-security-chatgpt-plugin-eval) - 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/_