What is social engineering, and why is healthcare vulnerable?

Social engineering, as per a Springer Link research paper, is “a type of attack in which the attacker exploits human vulnerabilities (by means such as influence, persuasion, deception, manipulation, and inducing) to breach the security goals”. In healthcare, the risk is extremely high since it takes advantage of routine behavior and how urgent things are in clinical and administrative contexts.

Healthcare organizations have many structural problems that make these attacks more likely to work. A report published in the Journal of Medical Internet Research notes that 11% of breaches are caused by human mistakes, which is often due to not enough training and not being aware of security issues. Old legacy systems are to blame for 16% of the problems, while not spending enough on cybersecurity is to blame for 21%. To lower the risk of social engineering, healthcare organizations need better staff training paired with system integration using software like Paubox to secure emails without additional steps.

What is social engineering?

Social engineering is a cybersecurity technique that employs psychological manipulation to deceive individuals into disclosing private information. The technique operates through techniques such as luring, pretexting, or phishing by exploiting inherent human vulnerabilities, including trust, curiosity, and compliance.

For instance, a Frontiers in Psychology article describes it as "a kind of psychological attack that exploits weaknesses in human cognitive functions," The study goes on to note that, “Adequate defense against social engineering cyberattacks requires a deeper understanding of what aspects of human cognition are exploited by these cyberattacks, why humans are susceptible to these cyberattacks, and how we can minimize or at least mitigate their damage.” Cognitive biases (including authority bias and reciprocity) and social dynamics create vulnerabilities, leaving individuals susceptible to falling for an attack.

Why email remains the main delivery channel

In simulated campaigns from a JAMA Network Open study, 16.7% of the nearly three million messages sent to employees at six US institutions were clicked on, amounting to nearly one in seven instances of hazardous engagement. This results in automatic responses that disregard urgent messages that resemble faxes or IT alerts from trusted sources, as well as messages from unusual senders.

The pace of healthcare makes this worse because it makes it harder to spot lies when workloads are high, and realistic fakes take advantage of authority bias and reciprocity, which can lead to ransomware attacks or credential theft. Repeated simulations cut the chances of clicks by more than 65%, showing that email is still the most popular form of communication even as threats change.

Why third parties and vendors add more risk

Third parties and vendors make cybersecurity risks in healthcare worse by adding untested access points, weaker defenses, and supply chain weaknesses. A 2025 Applied Clinical Informatics survey of healthcare delivery organizations (HDOs) found that 56% of them had third-party breaches in the previous year. Of those breaches, 54% were caused by too much privileged access, due to incomplete inventories (only 51% of HDOs track all vendors), manual monitoring (53%), and not checking security practices (57%).

Hackers can get in through vendors because of old systems and weak governance. For example, in Broward Health's 2021 case, a third-party provider's network let hackers access the PHI of 1.35 million patients, including their SSNs and medical histories. Another study titled Human Factors in Electronic Health Records Cybersecurity Breach: An Exploratory Analysis found that vendors' turnover (22% barrier), resource shortages (48%), and overreliance on reputation erode oversight, increasing attack surfaces amid complex integrations.

Why social engineering is getting harder to detect

The detection of social engineering attacks is becoming increasingly challenging due to their ability to manipulate the cognitive abilities of individuals and their ability to evolve rapidly beyond conventional technical signatures. Zero-day attacks that circumvent blacklists pose a challenge for phishing detection.

As the 20222 paper Applications of deep learning for phishing detection: a systematic literature review explains, “The problem with the denunciation platforms is that the zero-day phishing attack, which is related to a newly designed phishing site, cannot be identified because it will not be on the blacklist for a while.” Small URL changes can also help malicious sites slip past older blacklist-based filters.

Cognitive biases, including attentional vigilance decrement, can reduce an individual’s ability to detect visual irregularities. Differences in search efficiency may also make it more difficult to distinguish between legitimate and malicious content. In addition, heuristic processing is a mental shortcut that allows people to make quick decisions based on limited information rather than careful, detailed analysis. It is shaped by personality traits such as openness or a sense of urgency, which can override more systematic analysis, increasing susceptibility to threats on platforms like email.

What generative AI changes in inbound email security

Paubox’s generative AI feature uses large language models (LLMs) and vector databases to look at the tone, sender behavior, intent, and anomalies of each email as a whole. This lets it find advanced phishing, BEC, and social engineering that older tools cannot. It, for example, flags small changes like urgent lures that look like coworkers or hidden attachments, giving admins clear confidence scores and easy-to-understand reasons for why they should look at patterns in logs.

This continuous learning automatically improves defenses. As threats change (like AI-generated spoofs), the system gets better based on feedback from the organization, cutting down on false positives and the need for manual changes. ExecProtect+ stops lookalike domains and spoofing. It also has built-in malware scanning and transcription to make sure it follows HIPAA rules without sharing data.

FAQs

What are common examples of social engineering?

Common examples include phishing emails, fake password reset messages, business email compromise, phone scams, text-message scams, fake tech support calls, impersonation of a boss or vendor, and pretexting.

Who is most at risk from social engineering?

Anyone can be targeted. Employees in healthcare, finance, legal, education, and government are often heavily targeted because they handle sensitive data and move quickly.

Why is healthcare especially vulnerable to social engineering?

Healthcare moves fast, depends on trust, and handles large volumes of sensitive information.