Shattered.io has released a 12-step Python harness that tests Claude, GPT, Gemini, Mistral, and DeepSeek against 14 OWASP LLM01 attacks. The test lab, designed to run in 60 minutes, evaluates the models' resistance to prompt injection vulnerabilities.
TL;DR
- Shattered.io's test lab evaluates five major AI models against 14 OWASP LLM01 attacks in a 60-minute Python harness.
- The lab tests models' resistance to prompt injection, a critical security concern for AI applications.
- Developers and security researchers can use this lab to assess and improve the security of their AI implementations.
What happened
Shattered.io has developed a comprehensive test lab to evaluate the security of major AI models against prompt injection attacks. The lab, which can be set up and run in 60 minutes, tests Claude, GPT, Gemini, Mistral, and DeepSeek models against 14 OWASP LLM01 attacks. The test harness is designed to be easy to use, requiring only basic Python knowledge and a Linux environment. The lab includes a variety of attack scenarios, including direct and indirect prompt injection, jailbreaks, and tool hijacking. The results are scored using plain code, ensuring consistent and reliable evaluations.
Why it matters
Prompt injection is a critical security concern for AI applications, as it can lead to unauthorized access, data leaks, and other malicious activities. The OWASP LLM01 list highlights the most common and dangerous prompt injection attacks, making it an essential benchmark for evaluating AI model security. Developers and security researchers can use Shattered.io's test lab to assess the security of their AI implementations and identify potential vulnerabilities. The lab's comprehensive evaluation of five major AI models provides valuable insights into the current state of AI security and highlights areas for improvement. By using this lab, developers can ensure that their AI applications are secure and resilient against prompt injection attacks.
Key facts
- The test lab evaluates Claude, GPT, Gemini, Mistral, and DeepSeek models.
- It tests against 14 OWASP LLM01 attacks, including direct and indirect prompt injection, jailbreaks, and tool hijacking.
- The lab can be set up and run in 60 minutes using a 12-step Python harness.
- It requires only basic Python knowledge and a Linux environment.
- Results are scored using plain code, ensuring consistent and reliable evaluations.
- The lab includes a variety of attack scenarios to provide a comprehensive evaluation of AI model security.
- Developers and security researchers can use this lab to assess and improve the security of their AI implementations.
Context
Prompt injection is a growing concern in the AI community, as the increasing use of AI assistants and agents in various applications exposes them to potential security threats. The OWASP LLM01 list, published in Q3 2026, highlights the most common and dangerous prompt injection attacks, emphasizing the need for robust security measures in AI applications. Shattered.io's test lab addresses this need by providing a comprehensive and easy-to-use tool for evaluating AI model security. The lab's focus on major AI models and its alignment with the OWASP LLM01 list make it a valuable resource for developers and security researchers. As the AI landscape continues to evolve, the importance of AI security cannot be overstated, and tools like Shattered.io's test lab play a crucial role in ensuring the safety and reliability of AI applications.
