Security measures against prompt injections, jailbreak attacks, and secrets leakage


As AI systems like Writer models become increasingly integrated into a wide range of applications, the importance of securing them against various types of attacks becomes paramount. In this article, we delve into the technical details of how Writer safeguards its AI models against prompt injections, jailbreak attempts, and the leakage of sensitive information.

Measures against prompt injections

One of the first lines of defense is input sanitization, where incoming prompts are screened for potentially malicious code or harmful strings. Sophisticated Natural Language Processing (NLP) techniques, combined with standard cybersecurity measures, are used to detect and remove or neutralize suspicious inputs.

Safeguards against jailbreak attacks

The runtime environment in which the AI models operate is isolated from the rest of the system. This isolation is often achieved using containerization technologies like Docker, which limit the resources and system calls available to the running model.

Measures against secrets leakage

All sensitive information, including security keys and credentials, is encrypted using state-of-the-art encryption algorithms. These encrypted secrets are stored in secure vaults that are accessible only to authorized personnel.


Security is a multi-faceted challenge that requires a holistic approach. Writer employs a combination of advanced technologies and best practices to safeguard its AI models against prompt injections, jailbreak attacks, and the leakage of sensitive information. While no system can be 100% secure, these measures provide a robust framework for identifying, mitigating, and responding to various security threats.