Source URL: https://embracethered.com/blog/posts/2025/google-jules-invisible-prompt-injection/
Source: Embrace The Red
Title: Google Jules is Vulnerable To Invisible Prompt Injection
Feedly Summary: The latest Gemini models quite reliably interpret hidden Unicode Tag characters as instructions. This vulnerability, first reported to Google over a year ago, has not been mitigated at the model or API level, hence now affects all applications built on top of Gemini.
This includes Google’s own products and services, like Google Jules.
Hopefully, this post helps raise awareness of this emerging threat.
Invisible Prompt Injections in GitHub Issues When Jules is asked to work on a task, such as a GitHub issue, it is possible to plant invisible instructions into a GitHub issue to add backdoor code, or have it run arbitrary commands and tools.
AI Summary and Description: Yes
Summary: The text discusses a vulnerability in the Gemini AI models related to the interpretation of hidden Unicode Tag characters, which can be exploited through invisible prompt injections. This issue poses significant risks for applications built on Gemini, including Google’s own services, and highlights an emerging threat that AI security professionals must address.
Detailed Description: The content outlines critical security vulnerabilities associated with the Gemini AI models. Here are the main points:
– **Vulnerability Overview**: The Gemini models have a known issue that arises from their ability to interpret hidden Unicode Tag characters as executable instructions.
– **Duration of the Issue**: This vulnerability has been acknowledged by Google for over a year but remains unaddressed at the model or API level.
– **Impact on Applications**: As the vulnerability is not resolved, it affects all applications developed using the Gemini platform, which includes Google’s various products and services like Google Jules.
– **Emerging Threat Awareness**: The text serves to raise awareness of potential risks stemming from these vulnerabilities, particularly in the context of AI functionalities operating in environments such as GitHub.
– **Invisible Prompt Injections**: It is specified that during tasks (like handling GitHub issues), there is a risk of introducing invisible instructions that could lead to the execution of backdoor code or arbitrary command executions. This compromises the integrity of applications leveraging Gemini models.
This text is of particular relevance to professionals in AI security, emphasizing the importance of vigilance regarding vulnerabilities that can lead to severe security implications in AI systems and infrastructure. The threat of invisible prompt injections highlights the necessity for stronger security measures and controls to safeguard applications using AI technology.