Preeti
Large language models (LLMs) have significantly improved in the past year, with OpenAI releasing GPT-4 in March 2023, approaching human capabilities. However, threat actors have quickly exploited generative AI for malicious purposes, creating AI chatbots for cybercrime. Security teams have also adopted generative AI to enhance their defenses, with 67% of organizations leveraging this technology.
Threat actors are using LLMs for activities like writing convincing phishing emails, voice phishing, and speeding up cybercrime processes. These malicious applications pose a significant threat, especially in targeted phishing attacks, which are more effective than generic phishing emails. Cybersecurity teams are working to outsmart threat actors by evolving their security operations ahead of AI applications used for malicious purposes.
To protect organizations, AI can be used to analyze large amounts of information, create secure documentation, develop secure coding practices, and identify external threats faster. Implementing policies, tokenization, and training employees on AI risks are crucial steps to use AI models safely. Looking ahead, short-term risks include data leakage and model attacks, while medium-term risks involve AI agents automating manual tasks like vulnerability scanning and deepfake campaigns.
Understanding how LLMs are weaponized and implementing strategies like continuous monitoring, user education, and AI-powered security solutions can help cybersecurity professionals stay ahead of malicious actors in the evolving digital landscape. By leveraging AI in cybersecurity effectively, organizations can strengthen their defenses and protect against emerging threats.
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Source link: https://www.spiceworks.com/it-security/cyber-risk-management/guest-article/llms-impact-on-cybersecurity/
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