beelzebub-labs/beelzebub

• highreadme#1

  Reposition the README's opening paragraph to explicitly state its defensive cybersecurity purpose

  原因：

  当前

  **Deception Runtime Framework**
  
  Beelzebub is an open-source deception runtime that deploys adaptive, LLM-powered decoy services across SSH, HTTP, TCP, TELNET, and MCP protocols. It goes beyond passive honeypots by actively engaging attackers in realistic interactions, collecting high-fidelity threat intelligence, and detecting prompt injection attacks against AI agents.

  复制粘贴的修复

  复制

  Beelzebub is an open-source **defensive cybersecurity deception runtime framework**. It deploys adaptive, LLM-powered decoy services across SSH, HTTP, TCP, TELNET, and MCP protocols to actively engage attackers, collect high-fidelity threat intelligence, and detect prompt injection attacks against AI agents. Unlike offensive security tools, Beelzebub focuses on **threat detection and intelligence gathering**.

  待办完成忽略
• mediumabout#2

  Enhance the 'About' description to emphasize defensive cybersecurity and threat intelligence

  原因：

  当前

  A secure low code deception runtime framework, leveraging AI for System Virtualization.

  复制粘贴的修复

  复制

  A secure, low-code **defensive cybersecurity** deception runtime framework, leveraging AI for system virtualization and **threat intelligence gathering**.

  待办完成忽略
• lowreadme#3

  Add a 'Comparison' section to the README to differentiate from other tools

  原因：

  复制粘贴的修复

  复制

  ## Comparison to Other Deception Platforms
  
  Beelzebub stands apart from traditional offensive security frameworks like Metasploit or Cobalt Strike by focusing purely on defensive cybersecurity, threat detection, and intelligence gathering. Compared to other deception platforms (e.g., Attivo Networks, Illusive Networks, CounterCraft), Beelzebub's core differentiator is its open-source nature and deep integration of LLM-powered adaptive decoy services, specifically designed to counter advanced AI-driven threats and prompt injection attacks.

  待办完成忽略

本次扫描解析到的品类 GEO 通道：google/gemini-2.5-flash, deepseek/deepseek-v4-flash

• 品类问题

  How to deploy adaptive AI-powered decoy services to detect advanced cyber threats?

  你：未被推荐
  AI 推荐顺序：

  1. Attivo Networks ThreatDefend Platform
  2. Cymulate Extended Security Posture Management (XSPM) with Deception
  3. Illusive Networks Deception Everywhere
  4. CounterCraft The Deception Platform
  5. Microsoft Azure Sentinel

  AI 推荐了 5 个替代方案，却始终没点名 beelzebub-labs/beelzebub。这就是要补上的差距。

  查看 AI 完整回答
• 品类问题

  Looking for a framework to gather threat intelligence from interactive LLM honeypots.

  你：未被推荐
  AI 推荐顺序：

  1. OpenCTI
  2. MISP
  3. Dionaea
  4. T-Pot
  5. MHN
  6. Honeyd
  7. Flask
  8. Django
  9. Express
  10. langchain
  11. llama-index
  12. OpenAI
  13. Anthropic
  14. Hugging Face
  15. PostgreSQL
  16. MongoDB

  AI 推荐了 16 个替代方案，却始终没点名 beelzebub-labs/beelzebub。这就是要补上的差距。

  查看 AI 完整回答

• Metadata completeness

  pass

• README presence

  pass

• Compared to common alternatives in this category, what is the core differentiator of beelzebub-labs/beelzebub?

  pass
  ✓AI 明确点名了 beelzebub-labs/beelzebub

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

• If a team adopts beelzebub-labs/beelzebub in production, what risks or prerequisites should they evaluate first?

  pass
  ✓AI 明确点名了 beelzebub-labs/beelzebub

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

• In one sentence, what problem does the repo beelzebub-labs/beelzebub solve, and who is the primary audience?

  pass
  ✓AI 明确点名了 beelzebub-labs/beelzebub

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？