94 Percent of LLMs Shown to Be Vulnerable to Attack

94 Percent of LLMs Shown to Be Vulnerable to Attack


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The unfortunate truth is that poorly designed and improperly secured Artificial Intelligence integrations can be misused or exploited by adversaries, to the detriment of companies and users. Some of the compromises will bypass the traditional cybersecurity and privacy controls, leaving victims very exposed.

Researchers at the University of Calabria demonstrated that LLMs can be tricked into installing and executing malware on victim machines using direct prompt injection (42.1%), RAG backdoor attacks (52.9%), and inter-agent trust exploitation (82.4%). Overall, 16 of 17 (94%) state-of-the-art LLMs were shown to be vulnerable.

We cannot afford to be distracted by dazzling AI functionality when we are inadvertently putting our security, privacy, and safety at risk. Let’s embrace AI, but in trustworthy ways.

Research Paper: https://arxiv.org/html/2507.06850v3

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Matthew Rosenquist
Matthew Rosenquist

Cybersecurity Strategist specializing in the evolution of threats, opportunities, and risks in pursuit of optimal security for our digital world.


Cybersecurity Tomorrow
Cybersecurity Tomorrow

Cybersecurity strategy perspectives for the emerging risks and opportunities of securing our digital world. The insights of today will lead to tomorrow's security, privacy, and safety foundations.

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