Comparison
pentest-ai vs langchain
Verdict
Pick pentest-ai when tags unique to pentest-ai: cybersecurity, exploit-chaining, ctf, hacking-tools; pick langchain when pricing: LangChain itself is open-source and free to use. However, it might rely on paid services or premium models from external platforms like OpenAI..
Markdown twin · pentest-ai alternatives · langchain alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | pentest-ai | langchain |
|---|---|---|
| Maintenance | Very active (6d since push) As of today · github_public_v1 | Very active (0d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Personal account As of today · github_public_v1 | Not a fork · Organization account As of today · github_public_v1 |
| Security (OSV) | No MCP manifest As of today · mcp_manifest | No lockfile As of today · none |
Tagline
- pentest-ai
- Offensive-security MCP server with 205 wrapped tools, 17 specialist agents, and 60 SPA-aware probes for OWASP Top 10. CLI + MCP, BYO LLM. No API key needed on MCP path.
- langchain
- The agent engineering platform.
Stars
- pentest-ai
- 1.3k
- langchain
- 142k
Forks
- pentest-ai
- 249
- langchain
- 24k
Open issues
- pentest-ai
- 2
- langchain
- 419
Language
- pentest-ai
- Python
- langchain
- Python
Adopt for
- pentest-ai
- -
- langchain
- LangChain is an open-source platform designed specifically for building agents and applications that leverage large language models (LLMs). It provides a standard framework to develop interoperable components and connect
Persona
- pentest-ai
- -
- langchain
- -
Runtime
- pentest-ai
- -
- langchain
- -
License
- pentest-ai
- MIT
- langchain
- MIT License, allowing free use for both personal and commercial purposes under its stipulated terms.
Last pushed
- pentest-ai
- Jul 5, 2026
- langchain
- Jul 11, 2026
Categories
- pentest-ai
- Vector Databases, AI Agents, LLM Frameworks
- langchain
- LLM Frameworks, AI Agents
Trust and health
Days since push
- pentest-ai
- 6d
- langchain
- 0d
Open issues (now)
- pentest-ai
- 2
- langchain
- 419
Owner type
- pentest-ai
- User
- langchain
- Organization
Security scan
- pentest-ai
- No MCP manifest
- langchain
- No lockfile
Full report
- pentest-ai
- Trust report
- langchain
- Trust report
Choose pentest-ai if…
- Tags unique to pentest-ai: cybersecurity, exploit-chaining, ctf, hacking-tools.
- Also covers Vector Databases.
- Leaner open-issue backlog (2).
When NOT to use pentest-ai
- Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
- AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
Choose langchain if…
- Pricing: LangChain itself is open-source and free to use. However, it might rely on paid services or premium models from external platforms like OpenAI..
- Tags unique to langchain: agents, gemini, deepagents, generative-ai.
- * When aiming to build complex AI-powered agents or applications requiring high-level capabilities like planning, subagent interaction, and file system operations.
When NOT to use langchain
- * When working on smaller, less complex projects where full-scale integration with sophisticated components is not necessary as LangChain's extensive features might introduce unnecessary complexity.
- * If you are primarily focused on JavaScript or TypeScript development as the primary focus of LangChain is Python. Although there is a JS/TS equivalent (LangChain.js), it may not offer the same depth
- * For projects requiring heavy customization at lower levels, where a more granular control over individual components is required rather than working with an integrated framework.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (0xSteph/pentest-ai) · observed Jul 11, 2026
- GitHub forks (0xSteph/pentest-ai) · observed Jul 11, 2026
- Last push (0xSteph/pentest-ai) · observed Jul 5, 2026
- License file (MIT) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (langchain-ai/langchain) · observed Jul 11, 2026
- GitHub forks (langchain-ai/langchain) · observed Jul 11, 2026
- Last push (langchain-ai/langchain) · observed Jul 11, 2026
- License file (MIT) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: pentest-ai 1.3k · langchain 142k (synced Jul 11, 2026).
Common questions
- What is the difference between pentest-ai and langchain?
- pentest-ai: Offensive-security MCP server with 205 wrapped tools, 17 specialist agents, and 60 SPA-aware probes for OWASP Top 10. CLI + MCP, BYO LLM. No API key needed on MCP path.. langchain: The agent engineering platform.. See the comparison table for live GitHub stats and shared categories.
- When should I choose pentest-ai over langchain?
- Choose pentest-ai over langchain when Tags unique to pentest-ai: cybersecurity, exploit-chaining, ctf, hacking-tools; Also covers Vector Databases; Leaner open-issue backlog (2).
- When should I choose langchain over pentest-ai?
- Choose langchain over pentest-ai when Pricing: LangChain itself is open-source and free to use. However, it might rely on paid services or premium models from external platforms like OpenAI.; Tags unique to langchain: agents, gemini, deepagents, generative-ai; * When aiming to build complex AI-powered agents or applications requiring high-level capabilities like planning, subagent interaction, and file system operations.
- When should I avoid pentest-ai?
- Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- When should I avoid langchain?
- * When working on smaller, less complex projects where full-scale integration with sophisticated components is not necessary as LangChain's extensive features might introduce unnecessary complexity. * If you are primarily focused on JavaScript or TypeScript development as the primary focus of LangChain is Python. Although there is a JS/TS equivalent (LangChain.js), it may not offer the same depth * For projects requiring heavy customization at lower levels, where a more granular control over individual components is required rather than working with an integrated framework.
- Is pentest-ai or langchain more popular on GitHub?
- langchain has more GitHub stars (141,504 vs 1,269). Stars measure visibility, not whether either tool fits your constraints.
- Are pentest-ai and langchain open source?
- Yes - both are open-source projects on GitHub (pentest-ai: MIT, langchain: MIT).
- Where can I find alternatives to pentest-ai or langchain?
- GraphCanon lists graph-backed alternatives at pentest-ai alternatives and langchain alternatives (pentest-ai markdown twin, langchain 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, pentest-ai or langchain?
- pentest-ai: Very active. langchain: Very 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 pentest-ai and langchain?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: pentest-ai trust report; langchain trust report.