The rapid rise of generative AI models is exciting. However, these powerful tools often lack robust safeguards against misuse. Examples include generating deceptive content and launching novel attacks based on user prompts. Yet, the AI bandwagon is shouting,"All aboard!" In the self-created sense of urgency in adopting AI to stay competitive, prioritizing cybersecurity shouldn't be sacrificed in the rush to embrace it.
We can mitigate the risk of injection attacks. However, if we don't know what to look out for or what to ask, we are setting ourselves up for terrible results. It's reasonable to expect an uptick in vulnerable code because of the heavy reliance on generative AI. One can even posit that the slimming down of experienced developers exposes companies to new security risks.
Malicious actors could exploit this data for financial gain, competitive advantage or other harmful purposes. Even regular customers may inadvertently be exposed to this data.Deepfakes are synthetic media generated by AI. Imagine training a powerful AI model on hours of video footage of someone. This model can then learn to create realistic and convincing videos of that person, even saying or doing things they never did.
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