--- title: "FuzzyAI vs eval-view" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/cyberark-fuzzyai-vs-hidai25-eval-view" tools: ["cyberark-fuzzyai", "hidai25-eval-view"] --- # FuzzyAI vs eval-view *GraphCanon updated Sep 20, 2026* ## Verdict Pick FuzzyAI if fuzzyAI is an automated tool from cyberark for detecting and mitigating jailbreaks in LLM APIs using fuzzing techniques; pick eval-view if eval-view is a Python-based tool for regression testing of AI agents, supporting multiple platforms like LangGraph, CrewAI, OpenAI, and Anthropic. It snapshots AI behavior and detects regressions through diffing tool and. [FuzzyAI](https://github.com/cyberark/FuzzyAI) reports 1.6k GitHub stars, 217 forks, and 7 open issues, last pushed Feb 6, 2026. [eval-view](https://evalview.com) has 134 stars, 24 forks, and 2 open issues, last pushed Sep 5, 2026. Figures are from public GitHub metadata via [FuzzyAI's repository](https://github.com/cyberark/FuzzyAI) and [eval-view's repository](https://github.com/hidai25/eval-view). | | [FuzzyAI](/tools/cyberark-fuzzyai.md) | [eval-view](/tools/hidai25-eval-view.md) | | --- | --- | --- | | Tagline | A tool for automated LLM fuzzing to detect and mitigate jailbreaks | Regression testing for AI agents, snapshots behavior, diffs tool calls, catches regressions in CI | | Stars | 1,576 | 134 | | Forks | 217 | 24 | | Open issues | 7 | 2 | | Language | Jupyter Notebook | Python | | Adopt for | FuzzyAI is an automated tool from cyberark for detecting and mitigating jailbreaks in LLM APIs using fuzzing techniques. | Eval-view is a Python-based tool for regression testing of AI agents, supporting multiple platforms like LangGraph, CrewAI, OpenAI, and Anthropic. It snapshots AI behavior and detects regressions through diffing tool and | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Evaluation & Observability | AI Agents, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [FuzzyAI](/tools/cyberark-fuzzyai.md) | [eval-view](/tools/hidai25-eval-view.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Active (82%) | | Days since push | 225d | 13d | | Open issues (now) | 7 | 2 | | Stars delta | +33 (30d) | +8 (30d) | | Open issues delta | +1 (30d) | -1 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/cyberark-fuzzyai/trust.md) | [trust report](/tools/hidai25-eval-view/trust.md) | ## Shared compatibility - **Python**: [FuzzyAI](/tools/cyberark-fuzzyai.md) - Python runtime; [eval-view](/tools/hidai25-eval-view.md) - Python runtime ## Decision facts: FuzzyAI - **Adopt for:** FuzzyAI is an automated tool from cyberark for detecting and mitigating jailbreaks in LLM APIs using fuzzing techniques. ## Decision facts: eval-view - **Adopt for:** Eval-view is a Python-based tool for regression testing of AI agents, supporting multiple platforms like LangGraph, CrewAI, OpenAI, and Anthropic. It snapshots AI behavior and detects regressions through diffing tool and ## Choose when ### Choose FuzzyAI if… - FuzzyAI is primarily Jupyter Notebook; eval-view is Python. - Tags unique to FuzzyAI: ai, ai-red-team, fuzzing, jailbreak. - When you need to identify vulnerabilities specifically within the API layer of your large language models (LLMs). ### Choose eval-view if… - eval-view is primarily Python; FuzzyAI is Jupyter Notebook. - Tags unique to eval-view: agent-benchmark, agent-evaluation, agentic-ai, ai-agents. - Also covers AI Agents. - eval-view ships Docker support for self-hosted deployment. - When you need to snapshot and diff the behavior of AI agents across multiple platforms, including LangGraph, CrewAI, OpenAI, and Anthropic. ## When NOT to use FuzzyAI - For general application or code-level vulnerability scanning, as it is specialized for LLM APIs. - In scenarios where manual penetration testing of applications outside the scope of LLMs is required. ## When NOT to use eval-view - If you are working exclusively with AI platforms not supported by eval-view, such as those not listed among LangGraph, CrewAI, OpenAI, and Anthropic. - When you do not require regression testing or behavior snapshotting for your AI agents, as eval-view is specifically designed for these purposes. - If you are looking for a tool that does not involve backend API charges for executing your agent, as eval-view does not skip these charges even with the --no-judge flag. - If you need a tool that automatically handles the migration from the OpenAI Assistants API to the Responses API without manual intervention, as eval-view requires following a migration guide for this. ## Common questions ### What is the difference between FuzzyAI and eval-view? FuzzyAI: A tool for automated LLM fuzzing to detect and mitigate jailbreaks. eval-view: Regression testing for AI agents, snapshots behavior, diffs tool calls, catches regressions in CI. See the comparison table for live GitHub stats and shared categories. ### When should I choose FuzzyAI over eval-view? Choose FuzzyAI over eval-view when FuzzyAI is primarily Jupyter Notebook; eval-view is Python; Tags unique to FuzzyAI: ai, ai-red-team, fuzzing, jailbreak; When you need to identify vulnerabilities specifically within the API layer of your large language models (LLMs). ### When should I choose eval-view over FuzzyAI? Choose eval-view over FuzzyAI when eval-view is primarily Python; FuzzyAI is Jupyter Notebook; Tags unique to eval-view: agent-benchmark, agent-evaluation, agentic-ai, ai-agents; Also covers AI Agents; eval-view ships Docker support for self-hosted deployment; When you need to snapshot and diff the behavior of AI agents across multiple platforms, including LangGraph, CrewAI, OpenAI, and Anthropic. ### When should I avoid FuzzyAI? For general application or code-level vulnerability scanning, as it is specialized for LLM APIs. In scenarios where manual penetration testing of applications outside the scope of LLMs is required. ### When should I avoid eval-view? If you are working exclusively with AI platforms not supported by eval-view, such as those not listed among LangGraph, CrewAI, OpenAI, and Anthropic. When you do not require regression testing or behavior snapshotting for your AI agents, as eval-view is specifically designed for these purposes. If you are looking for a tool that does not involve backend API charges for executing your agent, as eval-view does not skip these charges even with the --no-judge flag. If you need a tool that automatically handles the migration from the OpenAI Assistants API to the Responses API without manual intervention, as eval-view requires following a migration guide for this. ### Is FuzzyAI or eval-view more popular on GitHub? FuzzyAI has more GitHub stars (1,576 vs 134). Stars measure visibility, not whether either tool fits your constraints. ### Are FuzzyAI and eval-view open source? Yes - both are open-source projects on GitHub (FuzzyAI: Apache-2.0, eval-view: Apache-2.0). ### Where can I find alternatives to FuzzyAI or eval-view? GraphCanon lists graph-backed alternatives at [FuzzyAI alternatives](/tools/cyberark-fuzzyai/alternatives) and [eval-view alternatives](/tools/hidai25-eval-view/alternatives) ([FuzzyAI markdown twin](/tools/cyberark-fuzzyai/alternatives.md), [eval-view markdown twin](/tools/hidai25-eval-view/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/cyberark-fuzzyai-vs-hidai25-eval-view.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, FuzzyAI or eval-view? FuzzyAI: Slowing. eval-view: Active. 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 FuzzyAI and eval-view? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [FuzzyAI trust report](/tools/cyberark-fuzzyai/trust); [eval-view trust report](/tools/hidai25-eval-view/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=cyberark-fuzzyai`](/api/graphcanon/graph?tool=cyberark-fuzzyai) - 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/_