--- title: "giskard-oss vs rebuff" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/giskard-ai-giskard-oss-vs-protectai-rebuff" tools: ["giskard-ai-giskard-oss", "protectai-rebuff"] --- # giskard-oss vs rebuff *GraphCanon updated Jul 12, 2026* ## Verdict Pick giskard-oss when giskard-oss is primarily Python; rebuff is TypeScript; pick rebuff when rebuff is primarily TypeScript; giskard-oss is Python. [giskard-oss](https://docs.giskard.ai) reports 5.5k GitHub stars, 485 forks, and 70 open issues, last pushed Jul 10, 2026. [rebuff](https://playground.rebuff.ai) has 1.5k stars, 137 forks, and 33 open issues, last pushed Aug 7, 2024. Figures are from public GitHub metadata via [giskard-oss's repository](https://github.com/Giskard-AI/giskard-oss) and [rebuff's repository](https://github.com/protectai/rebuff). | | [giskard-oss](/tools/giskard-ai-giskard-oss.md) | [rebuff](/tools/protectai-rebuff.md) | | --- | --- | --- | | Tagline | 🐢 Open-Source Evaluation & Testing library for LLM Agents | LLM Prompt Injection Detector | | Stars | 5,505 | 1,511 | | Forks | 485 | 137 | | Open issues | 70 | 33 | | Language | Python | TypeScript | | Adopt for | Giskard-OSS is a Python library aimed at evaluating and testing AI agents, particularly language models. It includes modules for scenario-based tests, security scanning, and synthetic data generation. | - | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Vector Databases, LLM Frameworks, AI Agents | LLM Frameworks, Vector Databases, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [giskard-oss](/tools/giskard-ai-giskard-oss.md) | [rebuff](/tools/protectai-rebuff.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Archived (8%) | | Days since push | 1d | 703d | | Archived on GitHub | No | Yes | | Open issues (now) | 70 | 33 | | Full report | [trust report](/tools/giskard-ai-giskard-oss/trust.md) | [trust report](/tools/protectai-rebuff/trust.md) | ## Shared compatibility - **Python**: [giskard-oss](/tools/giskard-ai-giskard-oss.md) - Python runtime; [rebuff](/tools/protectai-rebuff.md) - Python runtime ## Decision facts: giskard-oss - **Requirements:** Requires Python 3.12 or higher. - **Adopt for:** Giskard-OSS is a Python library aimed at evaluating and testing AI agents, particularly language models. It includes modules for scenario-based tests, security scanning, and synthetic data generation. ## Choose when ### Choose giskard-oss if… - giskard-oss is primarily Python; rebuff is TypeScript. - Requirements: Requires Python 3.12 or higher.. - Tags unique to giskard-oss: llm-eval, agent-evaluation, fairness-ai, ai-security. - Also covers AI Agents. - - You need an open-source solution specifically designed for testing LLMs with built-in checks and vulnerability scans. ### Choose rebuff if… - rebuff is primarily TypeScript; giskard-oss is Python. - Tags unique to rebuff: llmops, prompt-injection, prompts, security. - Also covers Evaluation & Observability. ## When NOT to use giskard-oss - - If you prefer a tool without any potential telemetry data collection, even though Giskard allows opting out, as it could be seen as potentially intrusive despite safeguards. - - You are working with environments that only support Python versions below 3.12, since Giskard-OSS requires at least Python 3.12. ## When NOT to use rebuff - rebuff is archived on GitHub. Prefer an active alternative unless you maintain a private fork or need a frozen dependency. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. - Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. ## Common questions ### What is the difference between giskard-oss and rebuff? giskard-oss: 🐢 Open-Source Evaluation & Testing library for LLM Agents. rebuff: LLM Prompt Injection Detector. See the comparison table for live GitHub stats and shared categories. ### When should I choose giskard-oss over rebuff? Choose giskard-oss over rebuff when giskard-oss is primarily Python; rebuff is TypeScript; Requirements: Requires Python 3.12 or higher.; Tags unique to giskard-oss: llm-eval, agent-evaluation, fairness-ai, ai-security; Also covers AI Agents; - You need an open-source solution specifically designed for testing LLMs with built-in checks and vulnerability scans. ### When should I choose rebuff over giskard-oss? Choose rebuff over giskard-oss when rebuff is primarily TypeScript; giskard-oss is Python; Tags unique to rebuff: llmops, prompt-injection, prompts, security; Also covers Evaluation & Observability. ### When should I avoid giskard-oss? - If you prefer a tool without any potential telemetry data collection, even though Giskard allows opting out, as it could be seen as potentially intrusive despite safeguards. - You are working with environments that only support Python versions below 3.12, since Giskard-OSS requires at least Python 3.12. ### When should I avoid rebuff? rebuff is archived on GitHub. Prefer an active alternative unless you maintain a private fork or need a frozen dependency. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. ### Is giskard-oss or rebuff more popular on GitHub? giskard-oss has more GitHub stars (5,505 vs 1,511). Stars measure visibility, not whether either tool fits your constraints. ### Are giskard-oss and rebuff open source? Yes - both are open-source projects on GitHub (giskard-oss: Apache-2.0, rebuff: Apache-2.0). ### Where can I find alternatives to giskard-oss or rebuff? GraphCanon lists graph-backed alternatives at [giskard-oss alternatives](/tools/giskard-ai-giskard-oss/alternatives) and [rebuff alternatives](/tools/protectai-rebuff/alternatives) ([giskard-oss markdown twin](/tools/giskard-ai-giskard-oss/alternatives.md), [rebuff markdown twin](/tools/protectai-rebuff/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/giskard-ai-giskard-oss-vs-protectai-rebuff.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, giskard-oss or rebuff? giskard-oss: Very active. rebuff: Archived. 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 giskard-oss and rebuff? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [giskard-oss trust report](/tools/giskard-ai-giskard-oss/trust); [rebuff trust report](/tools/protectai-rebuff/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=giskard-ai-giskard-oss`](/api/graphcanon/graph?tool=giskard-ai-giskard-oss) - 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/_