LLMs can be used maliciously in cyberattacks, such as generating phishing emails, automating social engineering tactics, or creating malware code. Their ability to generate highly convincing text makes them a tool for attackers to deceive victims or bypass detection systems. For example, an attacker could use an LLM to craft personalized phishing messages that are harder to identify as fraudulent.
They can also assist in automating cyberattacks by generating scripts or code snippets for exploitation. While LLMs are not inherently designed for malicious purposes, their misuse highlights the need for strict access controls and safeguards.
To prevent such misuse, developers implement content moderation, monitor API usage, and set strict terms of service. Encouraging collaboration between AI developers and cybersecurity professionals is also essential to identify and mitigate potential risks associated with malicious applications of LLMs.