What is LLM Honeypot?
LLM Honeypot is an AI security tool that deploys a deceptive fake chatbot interface to detect and trap prompt injection attacks for security researchers and developers. It presents itself as a convincing enterprise-grade AI assistant — branded as 'CorpAI Assistant, Enterprise AI Chatbot v2.1.4 • Secure Connection' — to lure attackers into revealing prompt injection and jailbreak attempts rather than targeting real LLM-powered systems. The interface is a fully rendered web chatbot with a live counter that increments each time an attack is trapped, giving operators real-time visibility into adversarial activity. Because LLM Honeypot is open-source and self-hosted, teams retain full control over the decoy environment and the captured attack data, with no dependency on external cloud services. It is particularly useful for blue teams studying attacker behavior, researchers cataloguing emerging prompt injection techniques, and developers who want to understand the threat landscape before deploying production AI chatbots. The tool fills a gap in the AI security toolkit: most honeypots are designed for network intrusion, not for LLM-specific attack vectors such as indirect prompt injection, system-prompt extraction, and role-play jailbreaks. By absorbing these attacks in a controlled environment, LLM Honeypot lets teams build better defenses for real AI applications. Best for: security researchers, red/blue teams, and developers who want to study and capture real-world prompt injection attacks against LLM-powered systems.
What is LLM Honeypot used for?
prompt injection detection, jailbreak attack research, LLM security testing, AI red teaming, adversarial attack logging, cybersecurity research
How much does LLM Honeypot cost?
Plan
Pricing not published — project is open-source; visit the website or repository for current deployment options
Pros and cons
Pros
- Deploys a convincing fake enterprise chatbot ('CorpAI Assistant v2.1.4') to attract real prompt injection and jailbreak attempts
- Live 'Attacks trapped' counter gives operators instant visibility into adversarial activity without manual log review
- Fully open-source and self-hosted — captured attack data stays on your own infrastructure, no vendor access
- Targets LLM-specific attack vectors (prompt injection, jailbreaks, system-prompt extraction) that traditional network honeypots miss
- Lightweight web UI means deployment requires minimal infrastructure, suitable for researchers spinning up quickly
Cons
- Pricing not published — project is open-source but managed hosting or commercial support options are not documented
- Limited to trapping chatbot-style LLM attacks; does not cover other AI attack surfaces such as model poisoning or adversarial inputs to vision models
- Self-hosting requires technical setup; there is no documented one-click cloud deployment option
- Active development status and long-term maintenance commitment are unclear from published information
Questions about LLM Honeypot
What is LLM Honeypot?
LLM Honeypot is an open-source AI security tool that simulates a fake enterprise AI chatbot to detect and log prompt injection and jailbreak attacks. It presents a convincing 'CorpAI Assistant' interface and tracks every trapped attack with a live counter, giving security teams visibility into real adversarial LLM attack techniques.
Is LLM Honeypot free?
LLM Honeypot is open-source, so the core software is free to use and self-host. No pricing plans or paid tiers are listed on the website; users deploy it on their own infrastructure.
How does LLM Honeypot work?
LLM Honeypot deploys a web-based chatbot interface designed to look like a legitimate enterprise AI assistant. When attackers interact with it and attempt prompt injections or jailbreaks, the tool detects and logs those attempts. A live 'Attacks trapped' counter updates in real time, and the captured data can be used to study attacker behavior and improve defenses for real LLM systems.
What attacks does LLM Honeypot detect?
LLM Honeypot is designed to trap LLM-specific attacks including prompt injection, system-prompt extraction attempts, and role-play jailbreaks — attack vectors that traditional network honeypots are not built to capture.
LLM Honeypot vs traditional honeypots — what's the difference?
Traditional honeypots simulate network services (SSH, HTTP) to catch intrusion attempts. LLM Honeypot specifically simulates an AI chatbot to catch LLM-targeted attacks like prompt injection and jailbreaks, making it the right tool for teams securing AI-powered applications rather than conventional infrastructure.
What are the best alternatives to LLM Honeypot?
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