ShadowLogic Attack Targets All Model Graphs to Create Codeless Backdoors

A new attack method has been discovered that targets all model graphs to create codeless backdoors. Researchers from ShadowLogic have uncovered this innovative technique, which could potentially lead to widespread security vulnerabilities.

The attack works by exploiting the underlying structure of model graphs, which are commonly used in various machine learning and artificial intelligence applications. By manipulating these graphs, attackers can introduce hidden backdoors that are difficult to detect using traditional security methods.

These codeless backdoors can be used to gain unauthorized access to sensitive data, disrupt operations, or even launch targeted attacks. The researchers warn that this attack method is particularly dangerous because it can be applied to a wide range of models and systems.

As this new attack method comes to light, it is crucial for organizations to be aware of the risks and take proactive steps to protect their systems. This includes implementing robust security measures, regularly updating software, and staying informed about the latest security threats.

Sources: Securityweek, Internet Archive, Cybersecurity Insights, Undercode Ai & Community, Wikipedia
Image Source: OpenAI, Undercode AI DI v2