Question at position 3 Which of the following best describes a major risk of using generative AI in cybersecurity?Generative AI eliminates the need for human security analysts by automating all cybersecurity tasks.Generative AI can slow down the creation of phishing attacks, making them easier to detect.Generative AI always improves security systems without introducing new vulnerabilities.Generative AI can make phishing attacks faster, more personalised, and harder to recognise.

Question

Question at position 3 Which of the following best describes a major risk of using generative AI in cybersecurity?Generative AI eliminates the need for human security analysts by automating all cybersecurity tasks.Generative AI can slow down the creation of phishing attacks, making them easier to detect.Generative AI always improves security systems without introducing new vulnerabilities.Generative AI can make phishing attacks faster, more personalised, and harder to recognise.

BlackTom AI · Accepted Answer

This question asks about the major risk associated with using generative AI in cybersecurity, so we must evaluate what each statement implies about risk and reality.
Option 1: 'Generative AI eliminates the need for human security analysts by automating all cybersecurity tasks.' This is overstated and misleading. Generative AI can assist and automate certain tasks, but it does not replace all human analysts or cover all aspects of cybersecurity. Complex decision-making, intuition, contextual understanding, and adversarial thinking often require human judgment, so claiming elimination of analysts is inaccurate and ignores the continued need for human oversight.
Option 2: 'Generative AI can slow down the creation of phishing attacks, making them easier to detect.' This statement runs counter to known capabilities. In practice, generative AI can accelerate crafting convincing phishing messages, personalize payloads, and automate targeting, which would make attacks harder to detect, not slower. Therefore, this option mischaracterizes the risk by suggesting a protective effect that isn’t supported by evidence.
Option 3: 'Generative AI always improves security systems without introducing new vulnerabilities.' The claim that it always improves security is overly optimistic and false. While AI can enhance defenses in some contexts, it can also introduce new vulnerabilities, such as model misconfigurations, data leakage, adversarial manipulation, and over-reliance on automated signals. Hence, this option runs afoul of the nuanced reality that new tools can create new weaknesses as well as strengths.
Option 4: 'Generative AI can make phishing attacks faster, more personalised, and harder to recognise.' This statement accurately reflects a major risk: adversaries can leverage generative models to scale and tailor phishing at speed, increasing success rates and evading detection. The speed, personalization, and sophistication facilitated by AI raise the bar for defenders and represent a substantive security risk.
In evaluating these options, the emphasis is on how AI shapes attacker capability and defense posture. The first two options describe extreme or incorrect effects, while the third option claims universal improvement without risk, which is unrealistic. The fourth option aligns with documented and widely acknowledged risks in cybersecurity that AI-powered phishing can become more effective and harder to identify, making it the most accurate description among the choices.

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