Rushed Implementation of Generative AI
Posted: Thu Feb 13, 2025 4:46 am
Brings New Cybersecurity Challenges
To begin, a common issue when it comes to GenAI and LLMs is a broad overreliance on AI-generated content. Trusting AI-generated content without verifying or checking for misleading or misinformation without human input or oversight can lead to the propagation of erroneous data that informs poor decision-making and reduced critical thinking. LLMs are known to hallucinate, so some of the disinformation may not even result from malicious intent.
In the same vein, the quantity of insecure code that is iraq whatsapp number data being introduced following the evolution of GenAI will also become a significant challenge for CISOs, if not proactively anticipated. AI engines are known to write buggy code with security vulnerabilities. Without the proper human oversight, GenAI empowers people without the proper technical foundations to ship code. This leads to increased security risk throughout the software development lifecycle for organizations using these tools improperly.
Data leakage is another prevalent issue. In some cases, attackers can use prompt injection to extract sensitive information that the AI model has learned from another user. Many times this can be harmless, but malicious use is certainly not precluded. Bad actors could intentionally probe the AI tool with meticulously crafted prompts, aiming to extract sensitive information that the tool has memorized, leading to the leak of sensitive or confidential information.
To begin, a common issue when it comes to GenAI and LLMs is a broad overreliance on AI-generated content. Trusting AI-generated content without verifying or checking for misleading or misinformation without human input or oversight can lead to the propagation of erroneous data that informs poor decision-making and reduced critical thinking. LLMs are known to hallucinate, so some of the disinformation may not even result from malicious intent.
In the same vein, the quantity of insecure code that is iraq whatsapp number data being introduced following the evolution of GenAI will also become a significant challenge for CISOs, if not proactively anticipated. AI engines are known to write buggy code with security vulnerabilities. Without the proper human oversight, GenAI empowers people without the proper technical foundations to ship code. This leads to increased security risk throughout the software development lifecycle for organizations using these tools improperly.
Data leakage is another prevalent issue. In some cases, attackers can use prompt injection to extract sensitive information that the AI model has learned from another user. Many times this can be harmless, but malicious use is certainly not precluded. Bad actors could intentionally probe the AI tool with meticulously crafted prompts, aiming to extract sensitive information that the tool has memorized, leading to the leak of sensitive or confidential information.