Comparison
agentscope vs PentestGPT
Verdict
Pick agentscope if agentscope is a Python-based development tool focused on creating transparent and trustworthy AI agents. It supports the creation of both single and multi-agent systems incorporating large language models into its design; pick PentestGPT if pentestGPT specializes in automating parts of the penetration testing process through large language models, offering a unique approach to AI-assisted security assessments.
Markdown twin · agentscope alternatives · PentestGPT alternatives
GraphCanon updated 4d
vs
Trust & integrity
| Signal | agentscope | PentestGPT |
|---|---|---|
| Maintenance | Very active (2d since push) As of 5d · github_public_v1 | Steady (33d since push) As of 4d · github_public_v1 |
| Provenance | Not a fork · Organization account As of 5d · github_public_v1 | Not a fork · Personal account As of 4d · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · 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
- agentscope
- Build and run agents you can see, understand and trust.
- PentestGPT
- Automated Penetration Testing Agentic Framework Powered by Large Language Models
Stars
- agentscope
- 29k
- PentestGPT
- 15k
Forks
- agentscope
- 3.4k
- PentestGPT
- 2.6k
Open issues
- agentscope
- 354
- PentestGPT
- 65
Language
- agentscope
- Python
- PentestGPT
- Python
Adopt for
- agentscope
- agentscope is a Python-based development tool focused on creating transparent and trustworthy AI agents. It supports the creation of both single and multi-agent systems incorporating large language models into its design
- PentestGPT
- PentestGPT specializes in automating parts of the penetration testing process through large language models, offering a unique approach to AI-assisted security assessments.
Persona
- agentscope
- -
- PentestGPT
- -
Runtime
- agentscope
- -
- PentestGPT
- -
License
- agentscope
- Apache-2.0
- PentestGPT
- MIT License, which allows for free use, modification, and distribution provided that attribution is maintained and any warranties or liabilities are disclaimed.
Last pushed
- agentscope
- Aug 14, 2026
- PentestGPT
- Jul 14, 2026
Categories
- agentscope
- AI Agents, LLM Frameworks
- PentestGPT
- AI Agents, LLM Frameworks
Trust and health
Maintenance
- agentscope
- Very active (96%)
- PentestGPT
- Steady (60%)
Days since push
- agentscope
- 2d
- PentestGPT
- 33d
Open issues (now)
- agentscope
- 354
- PentestGPT
- 65
Stars delta
- agentscope
- +1.0k (30d)
- PentestGPT
- +597 (30d)
Open issues delta
- agentscope
- +70 (30d)
- PentestGPT
- +3 (30d)
Owner type
- agentscope
- Organization
- PentestGPT
- User
Full report
- agentscope
- Trust report
- PentestGPT
- Trust report
Choose agentscope if…
- License: agentscope is Apache-2.0, PentestGPT is MIT.
- Tags unique to agentscope: agent, chatbot, llm-agent, multi-agent.
- - You need to develop AI agents where transparency and interpretability are critical.
When NOT to use agentscope
- - If your project does not benefit from the transparency features offered by agentscope, and less emphasis is placed on interpretability and more on specialized machine learning tasks without a need
Choose PentestGPT if…
- License: PentestGPT is MIT, agentscope is Apache-2.0.
- Requirements: - Python environment; - Access to large language models as stipulated by PentestGPT's operational requirements.
- Tags unique to PentestGPT: penetration-testing, python.
- PentestGPT ships Docker support for self-hosted deployment.
- - When you need an automated framework for certain tasks within penetration testing that can be handled by large language models.
When NOT to use PentestGPT
- - Avoid using PentestGPT if manual, nuanced analysis is required, as its reliance on LLM might not cover all complexities of a security assessment.
- - If your organization does not have the legal authority to conduct penetration testing on specific targets, as indicated by its disclaimer for 'educational purposes and authorized security testing'.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (agentscope-ai/agentscope) · observed Aug 16, 2026
- GitHub forks (agentscope-ai/agentscope) · observed Aug 16, 2026
- Last push (agentscope-ai/agentscope) · observed Aug 14, 2026
- License file (Apache-2.0) · observed Aug 16, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (GreyDGL/PentestGPT) · observed Aug 17, 2026
- GitHub forks (GreyDGL/PentestGPT) · observed Aug 17, 2026
- Last push (GreyDGL/PentestGPT) · observed Jul 14, 2026
- License file (MIT) · observed Aug 17, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: agentscope 29k · PentestGPT 15k (synced Aug 16, 2026).
Common questions
- What is the difference between agentscope and PentestGPT?
- agentscope: Build and run agents you can see, understand and trust.. PentestGPT: Automated Penetration Testing Agentic Framework Powered by Large Language Models. See the comparison table for live GitHub stats and shared categories.
- When should I choose agentscope over PentestGPT?
- Choose agentscope over PentestGPT when License: agentscope is Apache-2.0, PentestGPT is MIT; Tags unique to agentscope: agent, chatbot, llm-agent, multi-agent; - You need to develop AI agents where transparency and interpretability are critical.
- When should I choose PentestGPT over agentscope?
- Choose PentestGPT over agentscope when License: PentestGPT is MIT, agentscope is Apache-2.0; Requirements: - Python environment; - Access to large language models as stipulated by PentestGPT's operational requirements; Tags unique to PentestGPT: penetration-testing, python; PentestGPT ships Docker support for self-hosted deployment; - When you need an automated framework for certain tasks within penetration testing that can be handled by large language models.
- When should I avoid agentscope?
- - If your project does not benefit from the transparency features offered by agentscope, and less emphasis is placed on interpretability and more on specialized machine learning tasks without a need
- When should I avoid PentestGPT?
- - Avoid using PentestGPT if manual, nuanced analysis is required, as its reliance on LLM might not cover all complexities of a security assessment. - If your organization does not have the legal authority to conduct penetration testing on specific targets, as indicated by its disclaimer for 'educational purposes and authorized security testing'.
- Is agentscope or PentestGPT more popular on GitHub?
- agentscope has more GitHub stars (28,973 vs 14,900). Stars measure visibility, not whether either tool fits your constraints.
- Are agentscope and PentestGPT open source?
- Yes - both are open-source projects on GitHub (agentscope: Apache-2.0, PentestGPT: MIT).
- Where can I find alternatives to agentscope or PentestGPT?
- GraphCanon lists graph-backed alternatives at agentscope alternatives and PentestGPT alternatives (agentscope markdown twin, PentestGPT 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, agentscope or PentestGPT?
- agentscope: Very active. PentestGPT: Steady. 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 agentscope and PentestGPT?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: agentscope trust report; PentestGPT trust report.