Social Engineering is a non-technical attack method that exploits human psychology to deceive, manipulate, or persuade victims into revealing sensitive information, performing actions that benefit the attacker, or inadvertently facilitating a cyberattack. This technique is widely used by hackers as an initial step in executing large-scale attack campaigns, targeting top organizations and companies by exploiting the weakest link in cybersecurity—human factors.

With the rapid advancement of technology, particularly the explosive growth of artificial intelligence (AI) in recent years, social engineering attacks have also evolved. They are becoming increasingly complex, powerful, bold, and sophisticated, thanks to AI's assistance.

How AI Enhances Social Engineering Attacks?

Research shows that AI has significantly assisted hackers in executing social engineering attacks. Some key ways AI contributes include:

• Personalized Phishing: AI algorithms can analyze data from social media, such as a victim’s background, interests, job, location, and relationships, using various OSINT sources. This allows attackers to craft highly personalized social engineering attacks, increasing their chances of success.

• Content Translation and Refinement: Tools like ChatGPT, Copilot, and Gemini enable hackers to generate well-written phishing emails free of grammar and spelling errors. These tools also help maintain a natural and coherent writing style, ensuring responses align with the victim’s behavior. Since grammatical and spelling mistakes can often expose phishing emails, eliminating these weaknesses significantly improves the effectiveness of such attacks.

• Deepfake Integration: Hackers can leverage deepfake technology to create realistic fake personas and voice recordings of important figures. These can then be used in social media conversations to persuade victims into sharing sensitive information, transferring money, or granting access to an organization’s internal network.

Agentic AI and Its Amplification of Social Engineering Attacks

Agentic AI is an emerging branch of artificial intelligence. It refers to AI systems capable of reinforcement learning, self-awareness in language, and context-based decision-making. These AI systems can analyze data, set goals, plan strategies, make autonomous decisions, and adjust their behavior through trial and error to ensure they achieve objectives without continuous human intervention. A key feature of Agentic AI is its ability to "chain" tasks—breaking down complex objectives into smaller, manageable steps that can be executed efficiently.

Due to its autonomy, independent reasoning, and context-driven decision-making, the risk of Agentic AI being misused for malicious purposes is increasing. If left unchecked, it can cause severe damage in cybersecurity, including:

• Self-Improvement and Adaptation: Agentic AI's standout feature is its ability to learn, adapt, and enhance existing social engineering techniques. If exploited for malicious intent, it can autonomously identify and target victims at scale, refine attack strategies, and adjust tactics for each target. By analyzing past attack campaigns, it can fine-tune its approach, making future attacks more sophisticated, powerful, and unpredictable.

• Intelligent Phishing Attacks: Traditional AI-generated phishing emails require attackers to provide input data. However, Agentic AI can automatically gather data from social media, leaked databases, and other sources to craft highly personalized phishing content tailored to each target. Its ability to interact, persuade, and respond in real time like a human significantly increases the success rate of phishing attacks.

• Multi-Stage Attacks: Agentic AI can generate deceptive content based on a target’s responses or location. It can leverage information from an initial interaction, gradually steering victims through multiple stages of manipulation in real time.

• Multi-Modal Social Engineering: Agentic AI can integrate with other AI-driven technologies, such as Deepfake, to enhance the sophistication and complexity of attack campaigns, making them even harder to detect.

Preventing Attacks from Agentic AI

Having clear strategies and measures to prevent cyberattacks leveraging Agentic AI is crucial for individuals, companies, and organizations today. A lack of information, knowledge, strategies, or specific countermeasures can inadvertently increase the success rate of these attacks.

• Using AI to Fight AI: One of the most effective ways to counter AI-driven cyberattacks is by leveraging AI itself. A range of Agentic AI models designed for monitoring and incident response are continuously being developed, updated, and deployed in real-world applications. These AI systems can detect unusual activities, analyze malicious behaviors, and assess data sources to identify potential cybersecurity threats early. Additionally, they can track and evaluate internal anomalies, prioritize security patches based on emerging exploitation trends, and respond proactively to threats.

• Enhancing Individual Awareness: Human factors remain the weakest link in cybersecurity. While AI can serve as an effective defense layer in some cases, as attack methods become more sophisticated, having a well-informed and cybersecurity-aware workforce strengthens overall defense. Individuals must remain vigilant against suspicious emails and messages, avoid clicking on unknown links, and refrain from downloading or executing unverified files. These fundamental principles should be strictly followed to ensure personal and organizational security in cyberspace.

References

1. Securityweek - How agentic AI will be weaponized for social engineering attacks