We specialize in AI security auditing, ensuring that Artificial Intelligence systems are both robust and trustworthy.
Secure your LLM with
AIM
Intelligence SolutionOur Partner
Our Solution
AIM
RED
/GuardJailbreaking (Prompt Injection)
LLMs can unobey safety guardrails and can be manipulated to act in a way that is not intended.
Ethics Violation
AI can be biased and violate ethics. This can lead to serious social problems.
Task Specific Vulnerabilities
LLMs are used in various tasks. Each task has its own vulnerabilities, such as privacy violation, security breach, etc.
Plug and Play LLM Security for Your AI Service
You focus on business product,
we will take care of your security.
Real-time low overhead attack detection
We offer low overhead detection system for your AI service.
Customizable Security Policies and Rules
You can customize your security policies and rules as per your requirements.
Stronger
than PyRIT made by Microsoft
PyRIT vs AIM RED Performance comparison report :
Attack GPT 4 / 3.5
faster
🔺 96%cheaper
🔻 48.25%accurate
X 2Playground
**Disclaimer**
The content generated on this website may occasionally include material that could be harmful or offensive. We kindly advise users to use discretion and judgment when interpreting the generated outcomes.
Total Time Taken: -
Safety Status: -
AIM
Guard
Intuitive, Accurate, Scalability
Scans output and input of specific LLM services in real time and detects attacks and errors
Scan and secure LLM Application in real time
We provide a Safe Guard service to ensure that the LLM service
does not deviate from its intended purpose.
AIM
RED Force
RED-Teaming Game that anyone can enjoy
A game that anyone can play RED-Teaming in an easy and fun way (Lending Page)
LLM Bug Bounty via RED Teaming Game
Join the LLM RED Team in a fun and easy way through the game.
Participate in the RED TEAM Crowdsourcing Platform.
AIM
Scanner
Fast, Accurate, Comprehensive
Safety Status: -
Found Items: -
Total Time Taken: -
Want to learn about AI Safety & Security?
Check our latest articles in our blog
LLM Guardrail 방향성 제언
2024. 3. 11.
이 글은 다음 논문의 많은 부분을 참고했음을 알립니다. LLMs Can Defend Themselves Against Jailbreaking in a Practical Manner...
Neuro-Symbolic AI: Breakthrough of Trusthworthy
2024. 3. 1.
이 글은 다음 논문의 많은 부분을 참고했음을 알립니다. Towards Data-and Knowledge-Driven AI: A Survey on Neuro-Symbolic Comp...
LLM Guardrail의 현주소
2024. 2. 23.
LLM의 발전은 획기적이며, 거의 3일에 한번 꼴로 새로운 모델, 새로운 방법론, 새로운 응용 등이 이슈가 됩니다. 이는 시장에 많은 자금이 AI 모델의 연구 및 개발로 들어가고 ...