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AI is transforming cybersecurity, with technology that can detect and respond to threats far more quickly than human analysts. It can be used to prevent attacks by identifying anomalies and patterns across data sets and analyzing them for signs of malicious activity. It can also help organizations protect themselves from cyberattacks by assessing vulnerabilities and deploying patches to correct them.

But like any technology, it can be compromised by attackers, whose main goal is to steal data or launch attacks. An attacker may “poison” a training dataset with malicious information to corrupt the AI model’s decision-making, or even take control of a device or application to use it as a weapon. Indirect prompt injection attacks are a growing threat, and they’re often difficult to detect.

Despite these risks, many organizations are still leveraging AI to improve their security posture and protect themselves from cyberattacks. Those who want to make the most of this powerful new tool should understand the basics of AI and how it works, as well as develop skills in data science and analysis.

In addition, IT professionals must address data privacy concerns, as AI models require a significant amount of data to learn and improve their accuracy. This can lead to privacy breaches and leaks of sensitive data, which is why implementing strict data access controls and encryption is important.

Moreover, an AI-powered security solution can reduce the time to identify and mitigate threats by reducing false positives and negatives, which are caused by the tool misidentifying benign activities as malicious or failing to detect threats altogether. This can save IT and SOC teams valuable time, enabling them to focus on other threats that pose a more serious threat to the organization.