In 2023, half of the social engineering attacks worldwide were scams, making it the most common type of cyberattack in this category. Phishing ranked second, with **** percent of the attacks, while business e-mail compromise (BEC) made up nearly ** percent of the total spear-phishing attacks.

Introduction

Social Engineering Statistics: Social Engineering refers to the use of psychological tricks by perpetrators to obtain critical and sensitive information from the victims. Although the methods have changed with technology, the purpose of deceit to obtain information remains a significant threat to the general population.

In this blog, we will review social engineering statistics to provide a holistic overview of the dangerous aspects of negative factors involving social engineering. By venturing into this topic, one can avoid getting compromised and be aware of measures to prevent cybersecurity attacks.

******** and*************************************n was the most common social engineering method used by cybercriminals in Poland in 2023.

In 2023, business e-mail compromise (BEC) scams were the most common type of social engineering attacks using Gmail.com. Roughly **** percent of such cyberattacks detected on Gmail.com were identified as BEC scams. General scamming ranked second, with over ** percent, and phishing was identified in *** percent of social engineering attacks abusing Gmail.com.

Social Engineering Protection Market Outlook

According to our latest research, the global Social Engineering Protection market size reached USD 2.97 billion in 2024, driven by the escalating sophistication of cyber threats and an increasing reliance on digital platforms across industries. The market is projected to grow at a robust CAGR of 12.6% from 2025 to 2033, reaching a forecasted value of USD 8.69 billion by 2033. This significant growth trajectory is underpinned by rising awareness about the risks of social engineering attacks and the urgent need for comprehensive security solutions to protect organizations’ data, reputation, and operational continuity.

The primary growth factor for the Social Engineering Protection market is the exponential increase in cyberattacks targeting human vulnerabilities rather than technical flaws. As organizations digitize their operations and expand their remote workforces, attackers are increasingly leveraging phishing, pretexting, baiting, and other social engineering tactics to bypass traditional security defenses. The resulting financial and reputational damage has compelled enterprises to invest in advanced social engineering protection solutions, such as real-time threat intelligence, automated detection systems, and employee security awareness training. These solutions are now seen as critical layers of defense, especially as attack vectors become more targeted and sophisticated.

Another key driver is the tightening of regulatory requirements and compliance standards across various industries. Regulatory frameworks such as GDPR in Europe, HIPAA in the United States, and similar mandates in Asia Pacific are compelling organizations to adopt comprehensive security measures to safeguard sensitive data. Failure to comply can result in substantial fines and loss of consumer trust, making social engineering protection not just a technical necessity but a business imperative. The market is also benefiting from increased investments in cybersecurity infrastructure by both public and private sectors, further accelerating the adoption of innovative solutions that detect and mitigate social engineering threats in real-time.

The rapid proliferation of cloud-based applications and the Internet of Things (IoT) has expanded the attack surface for social engineering threats. As organizations migrate critical workloads to the cloud and integrate connected devices into their operations, the complexity of securing these environments grows. This complexity necessitates a multi-layered approach to security, incorporating email security, endpoint protection, identity and access management, and continuous employee training. Vendors are responding by offering integrated platforms that address these diverse needs, driving market growth through product innovation and the delivery of tailored solutions for different industry verticals.

From a regional perspective, North America continues to dominate the Social Engineering Protection market, accounting for the largest share in 2024 due to its advanced IT infrastructure, high digital adoption rates, and early implementation of cybersecurity regulations. However, Asia Pacific is emerging as the fastest-growing region, fueled by rapid digital transformation, a surge in cybercrime incidents, and increasing government initiatives to enhance cybersecurity readiness. Europe remains a strong market, driven by stringent data protection laws and heightened awareness among enterprises. Meanwhile, Latin America and the Middle East & Africa are witnessing steady growth as organizations in these regions recognize the importance of protecting against sophisticated social engineering attacks.

Component Analysis

The Component segment of the Social Engineering Protection market is bifurcated into Software and Services, both of which play pivotal roles in safeguarding organizations from human-centric cyber threats. Software solutions encompass a wide range of applications, including email security, endpoint protection, and identity management, all designed to automate the detection and mitigation of social engineering attacks. The increasing sophistication of phishing campaigns and business email compromise (BEC) schemes has driven organizations to adopt advanced software platforms that leverage artificial intelligence and machine learning for real-time threat analysis. These solutions offer centralized dashboards,

In today's digitally-driven world, the Social Engineering Attack Defense Solution market is rapidly emerging as a vital component of cybersecurity strategies across various industries. Social engineering attacks, which exploit human psychology rather than technical vulnerabilities, have become increasingly sophistic

Social Engineering Detection AI Market Outlook

According to our latest research, the global Social Engineering Detection AI market size reached USD 1.42 billion in 2024. With a robust growth trajectory, the market is expected to expand at a CAGR of 29.4% during the forecast period, culminating in a projected market size of USD 12.32 billion by 2033. This remarkable growth is primarily fueled by the escalating sophistication of cyber threats, increased adoption of AI-driven security solutions, and the growing necessity for organizations to protect sensitive data against social engineering attacks.

The rapid evolution of cyber threats, particularly those leveraging human vulnerabilities through social engineering, stands as a critical driver for the Social Engineering Detection AI market. Organizations are witnessing a surge in phishing, pretexting, baiting, and other manipulation-based attacks that traditional security tools often fail to detect. The increasing frequency and complexity of these attacks have underscored the limitations of conventional security measures, prompting enterprises to invest in more advanced, AI-powered detection solutions. These AI systems employ machine learning, natural language processing, and behavioral analytics to proactively identify and mitigate social engineering threats, thereby reducing the risk of costly data breaches and reputational damage.

Another significant growth factor is the heightened regulatory pressure across industries to bolster cyber defense mechanisms. Governments and regulatory bodies worldwide are imposing stricter compliance requirements on data protection and privacy, compelling organizations to adopt state-of-the-art security technologies. The integration of AI into social engineering detection not only helps meet these regulatory standards but also provides a competitive edge by enhancing incident response capabilities. Furthermore, the proliferation of remote work and digital transformation initiatives has expanded the attack surface for cybercriminals, making AI-driven detection solutions indispensable for safeguarding distributed workforces and digital assets.

The market's expansion is further propelled by the increasing awareness among enterprises about the financial and operational repercussions of social engineering attacks. High-profile security breaches and their associated costs have made cybersecurity a board-level concern, leading to greater budget allocations for advanced detection technologies. AI-powered social engineering detection solutions are gaining traction due to their ability to learn from evolving attack patterns, automate threat identification, and deliver real-time alerts, thereby minimizing the window of vulnerability. As organizations continue to digitize their operations, the demand for scalable, intelligent, and adaptive security solutions is expected to rise sharply, driving sustained growth in the Social Engineering Detection AI market.

Regionally, North America dominates the market, accounting for the largest share in 2024, primarily due to the high concentration of technology-driven enterprises, stringent regulatory frameworks, and the presence of leading AI solution providers. However, Asia Pacific is emerging as the fastest-growing region, propelled by rapid digitalization, increasing cybercrime incidents, and rising investments in cybersecurity infrastructure. Europe, Latin America, and the Middle East & Africa are also witnessing steady adoption, with governments and enterprises ramping up efforts to counteract the growing menace of social engineering attacks. This regional diversification reflects the universal recognition of social engineering threats and the global shift towards AI-enabled security solutions.

Component Analysis

The Social Engineering Detection AI market is segmented by component into Software, Hardware, and Services. The software segment holds the lion’s share of the market, largely driven by the demand for robust, scalable, and easily deployable AI-powered security platforms. These software solutions leverage advanced algorithms to analyze vast amounts of data, detect anomalies, and identify potential social engineering threats in real-time. The flexibility and integration capabilities of software solutions make them an attractive choice for organizations of all sizes, especially as cybercriminals continuously adapt their tactics. Furthermore, the rise of SaaS-based security offer

Financial overview and grant giving statistics of Social Engineering Project Inc.

Social Engineering Signal Detection Market Outlook

As per our latest research, the global Social Engineering Signal Detection market size was valued at USD 2.8 billion in 2024, with a robust growth trajectory evidenced by a CAGR of 15.2% projected through the forecast period. By 2033, the market is expected to reach USD 10.3 billion, driven primarily by the increasing sophistication and frequency of cyber threats targeting organizations worldwide. This growth is underpinned by a surge in demand for advanced security solutions capable of detecting and mitigating social engineering attacks, which are becoming more prevalent and damaging across industries.

The growth of the Social Engineering Signal Detection market is propelled by the rapid evolution of cyber threats, particularly those leveraging human vulnerabilities. Social engineering attacks, such as phishing, spear-phishing, and business email compromise, have seen a dramatic rise in both frequency and complexity. These attacks exploit psychological manipulation rather than technical vulnerabilities, making them harder to detect with traditional security measures. As businesses shift towards digital transformation, the attack surface expands, necessitating the adoption of specialized detection tools that can analyze behavioral signals, communication patterns, and anomalous activities. This trend is further amplified by the proliferation of remote work and cloud-based collaboration, which increases the potential vectors for social engineering exploits.

Another significant driver for market expansion is the regulatory landscape, which is becoming increasingly stringent regarding data protection and cybersecurity. Governments and regulatory bodies across the globe are introducing stricter compliance requirements, such as the General Data Protection Regulation (GDPR) in Europe and the California Consumer Privacy Act (CCPA) in the United States. These mandates obligate organizations to implement advanced security measures, including social engineering signal detection, to safeguard sensitive information and maintain customer trust. The financial and reputational repercussions of data breaches have made proactive threat detection and response a top priority for companies, further accelerating market growth.

In addition, the integration of artificial intelligence (AI) and machine learning (ML) technologies into social engineering signal detection solutions is reshaping the market landscape. AI-powered platforms can analyze vast volumes of data in real-time, identifying subtle indicators of social engineering attempts that would otherwise go unnoticed. These technologies enable adaptive learning, allowing detection systems to evolve alongside emerging threats. The growing investment in AI-driven cybersecurity solutions by enterprises of all sizes is a testament to the effectiveness and necessity of these advanced tools. As organizations recognize the limitations of traditional security approaches, the demand for innovative, AI-enabled social engineering detection systems is set to rise exponentially.

From a regional perspective, North America currently dominates the Social Engineering Signal Detection market, accounting for the largest share owing to the high incidence of cyberattacks, a mature cybersecurity ecosystem, and significant investments in advanced security technologies. Europe follows closely, driven by rigorous regulatory frameworks and a strong emphasis on data privacy. The Asia Pacific region is witnessing the fastest growth, fueled by rapid digitalization, increasing awareness of cyber risks, and substantial investments in cybersecurity infrastructure. Latin America and the Middle East & Africa are also experiencing steady growth, albeit from a smaller base, as organizations in these regions ramp up their cybersecurity capabilities to counter rising threats.

Component Analysis

The Social Engineering Signal Detection market is segmented by component into Software, Hardware, and Services, each playing a pivotal role in the overall ecosystem. The software segment commands the largest share, driven by the growing adoption of advanced analytics, threat intelligence, and behavioral analysis platforms. These solutions are designed to detect and respond to social engineering signals in real-time, leveraging machine learning algorithms and big data analytics to identify patterns indicative of malicious activity. The software l

Social Engineering Signal Detection Market Outlook

According to our latest research, the global Social Engineering Signal Detection market size reached USD 1.82 billion in 2024, with a robust year-over-year growth driven by escalating cyber threats and the proliferation of sophisticated social engineering attacks. The market is projected to expand at a CAGR of 16.1% from 2025 to 2033, reaching a forecasted value of USD 7.64 billion by 2033. This remarkable growth is attributed to increasing digital transformation initiatives, the rising complexity of cyberattacks, and growing regulatory compliance requirements across various industry verticals. As organizations worldwide prioritize cyber resilience, the demand for advanced social engineering signal detection solutions continues to surge.

One of the primary growth drivers for the Social Engineering Signal Detection market is the exponential increase in cyberattacks leveraging human vulnerabilities. With cybercriminals deploying ever-more sophisticated phishing, pretexting, baiting, and impersonation tactics, traditional security measures are proving inadequate. Organizations are recognizing the need for proactive detection tools that analyze behavioral signals, communication patterns, and contextual data to identify potential social engineering threats before they can inflict damage. The integration of artificial intelligence and machine learning into signal detection platforms has further enhanced their accuracy and adaptability, enabling real-time threat identification and response. This technological evolution is a critical factor fueling market expansion, as enterprises strive to stay ahead of emerging attack vectors.

Another significant growth factor is the stringent regulatory landscape and the increasing emphasis on data privacy and security. Governments and regulatory bodies across the globe are enacting and enforcing laws such as GDPR, CCPA, and other cybersecurity frameworks that mandate organizations to implement robust security measures, including advanced threat detection systems. Non-compliance can result in severe financial penalties and reputational damage, compelling organizations to invest in comprehensive security solutions. The need to safeguard sensitive customer data, maintain business continuity, and uphold stakeholder trust is driving widespread adoption of social engineering signal detection technologies, particularly in highly regulated sectors such as BFSI, healthcare, and government.

The rapid digitalization of business operations and the widespread adoption of remote and hybrid work models have also contributed to market growth. As employees access corporate networks from diverse locations and devices, the attack surface for social engineering threats has expanded significantly. Organizations are increasingly deploying signal detection solutions to monitor and secure distributed endpoints, communication channels, and cloud-based resources. The integration of these tools with existing security information and event management (SIEM) systems, identity and access management (IAM) platforms, and threat intelligence feeds is enhancing their effectiveness and scalability. This trend is expected to continue as businesses embrace digital transformation and prioritize cybersecurity as a strategic imperative.

From a regional perspective, North America dominates the Social Engineering Signal Detection market, accounting for the largest revenue share in 2024, followed by Europe and Asia Pacific. The region’s leadership is underpinned by the presence of major cybersecurity vendors, early adoption of advanced technologies, and a strong regulatory environment. However, Asia Pacific is anticipated to witness the fastest growth during the forecast period, driven by increasing cybercrime incidents, rapid digitalization, and rising awareness about the importance of proactive threat detection. Other regions, including Latin America and the Middle East & Africa, are also experiencing steady growth, supported by expanding IT infrastructure and government-led cybersecurity initiatives.

Social Engineering Attack Scenarios collected from various sources : News papers, Government advisories, Police education materials and interviews.

Discover the booming Social Engineering Audit market! This comprehensive analysis reveals a $500 million market in 2025 projected to reach $1.8 billion by 2033, driven by rising cyber threats and compliance needs. Learn about market trends, key players, and regional growth forecasts. Get your free insights now!

Social Engineering Fraud Insurance Market Outlook

As per our latest research, the global Social Engineering Fraud Insurance market size reached USD 1.42 billion in 2024, registering a robust year-on-year growth. Driven by heightened awareness and increased sophistication of cyber-attacks, the market is expected to grow at a CAGR of 18.6% from 2025 to 2033, reaching an estimated USD 7.43 billion by 2033. The primary growth factors include the rapid digital transformation across industries, increasing frequency of social engineering fraud incidents, and the growing need for specialized insurance products to mitigate emerging cyber risks.

The proliferation of digital communication channels and remote work environments has significantly amplified the exposure of organizations to social engineering fraud. Companies are increasingly recognizing that traditional cyber insurance policies often exclude or inadequately cover losses arising from sophisticated scams such as invoice fraud, phishing, and business email compromise. This realization has fueled the demand for specialized Social Engineering Fraud Insurance products. Furthermore, regulatory mandates and compliance requirements across various sectors, especially in BFSI and healthcare, are compelling businesses to adopt comprehensive risk management strategies, including dedicated insurance against social engineering threats. The rising cost of data breaches, coupled with the reputational damage associated with such incidents, further underscores the necessity for robust insurance coverage.

Another significant growth driver for the Social Engineering Fraud Insurance market is the increased targeting of small and medium enterprises (SMEs) by cybercriminals. SMEs often lack the sophisticated cybersecurity infrastructure and dedicated IT teams that larger enterprises possess, making them vulnerable to social engineering attacks. As awareness grows, insurance providers are developing tailored policies that cater to the specific needs of SMEs, offering affordable premiums and comprehensive coverage. Additionally, the expansion of digital banking, e-commerce, and online business transactions has created new attack vectors, prompting organizations across all verticals to seek proactive risk mitigation solutions, thereby fueling market growth.

Technological advancements in threat detection and risk assessment are also shaping the trajectory of the Social Engineering Fraud Insurance market. Insurers are leveraging artificial intelligence, machine learning, and data analytics to better assess client risk profiles, streamline claims processing, and offer more personalized insurance products. This technological integration not only enhances the value proposition for policyholders but also enables insurers to manage their own risk exposure more effectively. The convergence of technology and insurance is expected to further accelerate market expansion, as it allows for more accurate underwriting and innovative product offerings tailored to the evolving threat landscape.

Regionally, North America holds the largest share of the Social Engineering Fraud Insurance market, driven by a high incidence of social engineering attacks, stringent regulatory frameworks, and advanced digital infrastructure. Europe follows closely, with growing adoption of cyber insurance products in response to GDPR and other data protection regulations. The Asia Pacific region is witnessing the fastest growth, propelled by rapid digitalization, increasing cybercrime rates, and rising awareness among businesses about the importance of insurance coverage against social engineering fraud. Latin America and the Middle East & Africa are also emerging as promising markets, albeit from a lower base, as organizations in these regions increasingly recognize the financial and reputational risks associated with social engineering attacks.

As the market for Social Engineering Fraud Insurance continues to expand, the role of Commercial Crime Insurance becomes increasingly significant. This type of insurance provides a broader scope of protection against various forms of criminal activities that can impact businesses. While Social Engineering Fraud Insurance focuses on specific cyber threats, Commercial Crime Insurance covers a wide range of risks, including employee theft, forgery, and fraud. Busin

According to surveys of working adults and IT professionals conducted in 2023, almost ***** in ** respondents reported having encountered vishing attacks. This represents a slight decrease from ** percent in the year prior. Vishing attacks are a type of social engineering attacks performed over phone calls or voice messages for phishing.

The Social Engineering Audit market has emerged as a crucial element in safeguarding organizations against sophisticated cyber threats. In an era where human behaviors can significantly influence cybersecurity, a comprehensive social engineering audit assesses vulnerabilities created by employees and organizational

Between November 2023 and October 2024, 72 percent of compromised information through privilege misuse was personal data. Furthermore, 85 percent of the compromised data through system intrusion was internal data.

The Social Engineering Attack Defense Solution market is booming, projected to reach $15 billion by 2033. Learn about key drivers, trends, and restraints shaping this rapidly evolving sector, including AI-powered solutions, regulatory compliance, and the escalating threat of sophisticated phishing attacks. Explore market size, CAGR, and regional breakdowns in our comprehensive analysis.

📁 SE-Phish: Annotated Email Dataset for Social Engineering Feature Analysis

SE-Phish is a curated dataset of 2,000 email samples labeled as either Phishing or Benign, designed to support research in social engineering detection. Each email is annotated with five psychological feature scores — Urgency, Authority, Reciprocity, Scarcity, and SocialProof — reflecting the persuasive tactics embedded in the message. The dataset includes realistic subject lines and body snippets, enabling fine-grained analysis of social engineering intensity across diverse email types. It is suitable for training supervised models, benchmarking feature extraction pipelines, and evaluating interpretability frameworks in phishing detection.

📁 SE-Phish: Annotated Email Dataset for Social Engineering Feature Analysis

SE-Phish is a curated dataset of 2,000 email samples labeled as either Phishing or Benign, designed to support research in social engineering detection. Each email is annotated with five psychological feature scores — Urgency, Authority, Reciprocity, Scarcity, and SocialProof — reflecting the persuasive tactics embedded in the message. The dataset includes realistic subject lines and body snippets, enabling fine-grained analysis of social engineering intensity across diverse email types. It is suitable for training supervised models, benchmarking feature extraction pipelines, and evaluating interpretability frameworks in phishing detection.

The Social Engineering Penetration Testing market plays a crucial role in today's cybersecurity landscape, where organizations increasingly recognize the significance of human factors in their security protocols. Social engineering attacks exploit psychological manipulation to trick individuals into divulging confid