Threats & Vulnerabilities in AI Models - How They Can be Abused

The rapid surge in LLMs (Large language models) across several industries and sectors has raised critical concerns about their safety, security, and potential for misuse. Threat actors can exploit LLMs for illicit purposes such as fraud, social engineering, phishing, impersonation, generation of malware, propaganda, and prompt injection and manipulation. A group of cybersecurity experts from various universities have conducted a study on how threat actors could abuse AI models for illicit purposes. Flaws in AI models make them vulnerable to threats and flaws, and there have been recent detections of cyber AI weapons. AI text generation aids in detecting malicious content and there are methods like watermarking, discriminating approaches, and zero-shot approaches. Red teaming tests LLMs for harmful language and content filtering methods aim to prevent it. There are various flaws in AI models such as prompt leaking, indirect prompt injection attacks, goal hijacking, jailbreaking, and universal adversarial triggers. LLMs face challenges in safety and security and peer review is needed to address concerns. #cyberattack #cybersecurity #vulnerability

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