In 2023, the most common type of cyber crime reported to the United States internet Crime Complaint Center was phishing and spoofing, affecting approximately 298 thousand individuals. In addition, over 55 thousand cases of personal data breaches cases were reported to the IC3 during that year. Dynamic of phishing attacks Over the past few years, phishing attacks have increased significantly. In 2023, almost 300 thousand individuals fell victim to such attacks. The highest number of phishing scam victims since 2018 was recorded in 2021, approximately 324 thousand.Phishing attacks can take many shapes. Bulk phishing, smishing, and business e-mail compromise (BEC) are the most common types. In 2023, 76 percent of the surveyed worldwide organizations reported encountering bulk phishing attacks, while roughly three in four were targeted by smishing scams. Impact of phishing attacks Among the most targeted industries by cybercriminals are healthcare, financial, manufacturing, and education institutions. An observation carried out in the first quarter of 2023 found that social media was most likely to encounter phishing attacks. According to the reports, almost a quarter of them stated being targeted by a phishing scam in the measured period. Very often, phishing e-mails contain a crucial risk for the organization. Almost three in ten worldwide organizations that have experienced phishing attacks suffered from a customer or a client data breach as a consequence. Phishing scams that delivered ransomware infections were also common for the surveyed organizations.

During the fourth quarter of 2024, nearly 23 percent of phishing attacks worldwide targeted social media. Web-based software services and webmail were targeted by over 23 percent of registered phishing attacks. Furthermore, financial institutions accounted for 12 percent of attacks.

In 2024, over 193,000 individuals in the United States reported encountering phishing attacks. This figure had decreased compared to the previous year, when the number of phishing attacks nationwide amounted to nearly 300,000. However, in 2020 and 2019, this number was relatively low, around 241 thousand and 114 thousand, respectively.

The phishing protection market is experiencing robust growth, driven by the escalating sophistication and frequency of phishing attacks targeting individuals and organizations across diverse sectors. The increasing reliance on digital platforms for banking, e-commerce, and communication has created a fertile ground for cybercriminals, necessitating robust security measures. The market's expansion is fueled by several key factors, including the rising adoption of cloud-based security solutions, the proliferation of mobile devices, and the increasing awareness of phishing threats among both individuals and businesses. Furthermore, stringent government regulations concerning data privacy and security are compelling organizations to invest heavily in advanced phishing protection technologies. While the BFSI (Banking, Financial Services, and Insurance) sector remains a significant adopter, growth is also observed across other sectors like healthcare, government, and telecommunications, due to their sensitive data assets and heightened regulatory scrutiny. The market is segmented by application (BFSI, Government, Healthcare, Telecommunications and IT, Transportation, Education, Retail) and type of phishing (email-based, non-email-based), each presenting unique opportunities for specialized solutions. Companies like Cyren, BAE Systems, Microsoft, FireEye, Symantec, Proofpoint, GreatHorn, Cisco, Phishlabs, Intel, and Mimecast are key players, constantly innovating to counter evolving phishing tactics. The market's growth trajectory is projected to remain positive over the forecast period (2025-2033), although challenges remain. These include the ever-evolving nature of phishing techniques, the difficulty in detecting sophisticated attacks, and the ongoing skills gap in cybersecurity expertise. Despite these obstacles, the market’s future looks promising, spurred by continuous advancements in artificial intelligence (AI) and machine learning (ML) technologies which enhance threat detection and response capabilities. The increasing adoption of multi-layered security solutions, incorporating phishing protection alongside other security measures, further contributes to the overall market growth. The geographical distribution of the market indicates strong growth in North America and Europe, while the Asia-Pacific region is poised for significant expansion in the coming years, driven by increasing internet penetration and digitalization.

The dataset 1 contains the age, qualification level, their awareness about phishing and if they became victim to phishing. The dataset 1 contains the result to detection rate before awareness and briefing of phishing after a successful spear phishing.

The dataset 2 contains the age, qualification level, their awareness about phishing and if they became victim to phishing. The dataset 2 contains the result to detection rate after awareness and briefing of phishing after a successful smishing.

In 2024, the number of reported phishing attacks increased by three percent year-over-year. In 2022, this annual increase was at 28 percent. Between 2021 and 2024, the cumulative increase in the number of reported phishing attacks was 49 percent.

The spear phishing market is experiencing robust growth, driven by the increasing sophistication of cyberattacks and the expanding digital landscape. While precise market sizing data is unavailable, considering the substantial investments in cybersecurity and the consistent rise in reported phishing incidents, a reasonable estimate for the 2025 market size would be in the range of $5-7 billion. This figure reflects the rising costs associated with data breaches, regulatory fines, and the increasing demand for advanced threat detection and response solutions. A Compound Annual Growth Rate (CAGR) of 12-15% over the forecast period (2025-2033) is plausible, considering ongoing technological advancements in spear phishing techniques and the corresponding need for robust countermeasures. Key drivers include the growth of remote work, increasing reliance on cloud services, and the evolving tactics employed by cybercriminals to target specific individuals and organizations. Trends point towards a greater focus on artificial intelligence (AI) and machine learning (ML) in threat detection, as well as a shift towards proactive security measures and employee training programs to mitigate the impact of spear phishing attacks. However, restraints include the ever-evolving nature of spear phishing techniques, the persistent skills gap in cybersecurity professionals, and the potential for false positives in automated detection systems. Segmentation within the market is likely to exist based on solution type (e.g., email security, security awareness training), deployment model (cloud, on-premises), and target industry (financial services, healthcare, government). Companies like BAE Systems, Check Point Software Technologies, Cisco Systems, and Proofpoint are key players actively innovating and competing within this dynamic market. The significant market expansion is further fueled by the high financial stakes involved in successful spear phishing campaigns. The impact of successful attacks, including data breaches, financial losses, and reputational damage, encourages organizations to invest heavily in comprehensive security solutions. The proliferation of sophisticated spear phishing techniques, such as personalized phishing emails and the use of social engineering, necessitates advanced detection and prevention technologies. The market's competitive landscape is characterized by both established cybersecurity vendors and emerging players who are constantly developing new solutions to combat the threat of spear phishing. The competitive dynamics will likely lead to further innovation and drive market growth in the coming years, enhancing the overall sophistication of spear phishing detection and prevention solutions.

1) Data Introduction • The Email Phishing Dataset is designed for phishing email detection using machine learning.

2) Data Utilization (1) Email Phishing Dataset has characteristics that: • All emails were refined and subjected to a custom NLP feature extraction pipeline focused on phishing metrics. • This dataset contains no raw text or headers, only features engineered for model training/testing. (2) Email Phishing Dataset can be used to: • Developing an email detection model: It can be used to train and evaluate AI models that classify normal mail and phishing mail using various characteristics such as email body, subject, and sender. • E-mail security policy and threat analysis research: Analyzing real phishing cases and normal email data to derive the characteristics of phishing attacks, and use them to establish effective email security policies and develop threat response strategies.

Network Phishing Simulator Market Outlook

The global network phishing simulator market size was estimated to be USD 900 million in 2023 and is projected to reach USD 2.7 billion by 2032, growing at a compound annual growth rate (CAGR) of 12.8% from 2024 to 2032. This market is driven by the increasing need for organizations to strengthen their cybersecurity protocols against phishing attacks, which have become more sophisticated and frequent over the years.

The proliferation of digital transformation initiatives across industries is one of the primary growth factors for the network phishing simulator market. As businesses increasingly migrate to digital platforms and cloud-based solutions, the risk of cyber-attacks, particularly phishing, has escalated. Phishing attacks often target employees, exploiting their lack of awareness to breach organizational security. Hence, there is a growing demand for effective simulation tools to train employees to recognize and respond to phishing attempts. This increased focus on cybersecurity training is a significant driver for the market.

Another key growth factor is the stringent regulatory requirements and compliance standards introduced by various governments globally. Regulations such as the General Data Protection Regulation (GDPR) in Europe and the Health Insurance Portability and Accountability Act (HIPAA) in the United States mandate stringent data protection measures. Organizations are required to ensure their employees are well-versed in identifying potential threats like phishing. Network phishing simulators help fulfill these regulatory requirements, as they provide an effective means of testing and training employees without exposing them to real cyber-threats.

The rise in remote working trends due to the COVID-19 pandemic has also contributed to the market’s growth. With more employees working remotely, often using personal devices and unsecured networks, the risk of phishing attacks has surged. Organizations are increasingly investing in phishing simulators to safeguard their remote workforce. These simulators help identify vulnerabilities in employee behavior and provide targeted training, thereby reducing the risk of successful phishing attacks.

Regionally, North America is expected to dominate the network phishing simulator market due to the high adoption rate of advanced cybersecurity solutions and the presence of major market players. Additionally, the increasing frequency of cyber-attacks in the region, coupled with stringent regulatory frameworks, drives the demand for phishing simulators. Europe follows closely, driven by compliance with GDPR and a high level of cybersecurity awareness. The Asia Pacific region is anticipated to witness substantial growth due to the rapid digital transformation in emerging economies and the increasing instances of cyber-attacks.

Component Analysis

The component segment of the network phishing simulator market is categorized into software and services. The software segment holds a significant share due to the wide range of functionalities it offers. These include customizable phishing simulations, detailed reporting, and analytics to track employee progress. The software solutions are designed to mimic real-world phishing scenarios, thereby providing a comprehensive training experience. The increasing sophistication of phishing attacks necessitates advanced software solutions capable of evolving alongside these threats.

Services, on the other hand, play a crucial role in the deployment and effective utilization of phishing simulators. These services include implementation, training, and support services. Implementation services ensure that the software is seamlessly integrated into an organization's existing IT infrastructure. Training services are essential to maximize the simulator's effectiveness, as they help employees understand how to use the software and interpret the results. Support services provide ongoing assistance, ensuring that the software remains up-to-date and any issues are promptly addressed.

The integration of Artificial Intelligence (AI) and Machine Learning (ML) into phishing simulation software is a growing trend. These technologies enhance the software’s ability to detect and adapt to new phishing tactics. AI-driven simulators can analyze user behavior patterns and tailor simulations to target specific vulnerabilities, making the training process more effective. The incorporation of these advanced technologies is expected to further drive the growth of the software segment.

These data consist of a collection of legitimate as well as phishing website instances. Each website is represented by the set of features which denote, whether website is legitimate or not. Data can serve as an input for machine learning process.

In this repository the two variants of the Phishing Dataset are presented.

Full variant - dataset_full.csv Short description of the full variant dataset: Total number of instances: 88,647 Number of legitimate website instances (labeled as 0): 58,000 Number of phishing website instances (labeled as 1): 30,647 Total number of features: 111

Small variant - dataset_small.csv Short description of the small variant dataset: Total number of instances: 58,645 Number of legitimate website instances (labeled as 0): 27,998 Number of phishing website instances (labeled as 1): 30,647 Total number of features: 111

IntroductionThe dynamic and sophisticated nature of phishing attacks, coupled with the relatively weak anti-phishing tools, has made phishing detection a pressing challenge. In light of this, new gaps have emerged in phishing detection, including the challenges and pitfalls of existing phishing detection techniques. To bridge these gaps, this study aims to develop a more robust, effective, sophisticated, and reliable solution for phishing detection through the optimal feature vectorization algorithm (OFVA) and supervised machine learning (SML) classifiers.MethodsInitially, the OFVA was utilized to extract the 41 optimal intra-URL features from a novel large dataset comprising 2,74,446 raw URLs (134,500 phishing and 139,946 legitimate URLs). Subsequently, data cleansing, curation, and dimensionality reduction were performed to remove outliers, handle missing values, and exclude less predictive features. To identify the optimal model, the study evaluated and compared 15 SML algorithms arising from different machine learning (ML) families, including Bayesian, nearest-neighbors, decision trees, neural networks, quadratic discriminant analysis, logistic regression, bagging, boosting, random forests, and ensembles. The evaluation was performed based on various metrics such as confusion matrix, accuracy, precision, recall, F-1 score, ROC curve, and precision-recall curve analysis. Furthermore, hyperparameter tuning (using Grid-search) and k-fold cross-validation were performed to optimize the detection accuracy.Results and discussionThe findings indicate that random forests (RF) outperformed the other classifiers, achieving a greater accuracy rate of 97.52%, followed by 97.50% precision, and an AUC value of 97%. Finally, a more robust and lightweight anti-phishing model was introduced, which can serve as an effective tool for security experts, practitioners, and policymakers to combat phishing attacks.

This dataset contains a collection of legitimate and phishing websites, along with information on the target brands (brands.csv) being impersonated in the phishing attacks. The dataset includes a total of 10,395 websites, 5,244 of which are legitimate and 5,151 of which are phishing websites. These websites impersonate a total of 86 different target brands.

For phishing datasets, the files can be downloaded in a zip file with a "phishing" prefix, while for legitimate websites, the files can be downloaded in a zip file with a "not-phishing" prefix.

In addition, the dataset includes features such as screenshots, text, CSS, and HTML structure for each website, as well as domain information (WHOIS data), IP information, and SSL information. Each website is labeled as either legitimate or phishing and includes additional metadata such as the date it was discovered, the target brand being impersonated, and any other relevant information.

The dataset has been curated for research purposes and can be used to analyze the effectiveness of phishing attacks, develop and evaluate anti-phishing solutions, and identify trends and patterns in phishing attacks. It is hoped that this dataset will contribute to the advancement of research in the field of cybersecurity and help improve our understanding of phishing attacks.

Phishing is an attack where a scammer calls you, texts or emails you, or uses social media to trick you into clicking a malicious link, downloading malware, or sharing sensitive information. Phishing attempts are often generic mass messages, but the message appears to be legitimate and from a trusted source (e.g. from a bank, courier company).

data-phishing-detection

A dataset to test methods to detect phishing emails The file data.parquet contains the dataset, 400 emails. 200 are synthetic phishing attempts and 200 are synthetic regular emails.

  Schema

input - an email, synthesized by an LLM, that is either a phishing attempt or a regular email. output - 'Yes' if the email is a phishing attempt, 'No' otherwise.

  Prompt

The prompt.md file contains a prompt that can be used with an LLM as a starting… See the full description on the dataset page: https://huggingface.co/datasets/RevaHQ/data-phishing-detection.

Analysis of ‘Phishing Dataset for Machine Learning’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/shashwatwork/phishing-dataset-for-machine-learning on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

Anti-phishing refers to efforts to block phishing attacks. Phishing is a kind of cybercrime where attackers pose as known or trusted entities and contact individuals through email, text or telephone and ask them to share sensitive information. Typically, in a phishing email attack, and the message will suggest that there is a problem with an invoice, that there has been suspicious activity on an account, or that the user must login to verify an account or password. Users may also be prompted to enter credit card information or bank account details as well as other sensitive data. Once this information is collected, attackers may use it to access accounts, steal data and identities, and download malware onto the user’s computer.

Content

This dataset contains 48 features extracted from 5000 phishing webpages and 5000 legitimate webpages, which were downloaded from January to May 2015 and from May to June 2017. An improved feature extraction technique is employed by leveraging the browser automation framework (i.e., Selenium WebDriver), which is more precise and robust compared to the parsing approach based on regular expressions.

Anti-phishing researchers and experts may find this dataset useful for phishing features analysis, conducting rapid proof of concept experiments or benchmarking phishing classification models.

Acknowledgements

Tan, Choon Lin (2018), “Phishing Dataset for Machine Learning: Feature Evaluation”, Mendeley Data, V1, doi: 10.17632/h3cgnj8hft.1 Source of the Dataset.

--- Original source retains full ownership of the source dataset ---

This API is providing the information of press releases issued by the authorized institutions and other similar press releases issued by the HKMA in the past regarding fraudulent bank websites, phishing E-mails and similar scams information.

AI-Driven Phishing Detection Market Outlook

According to our latest research, the global AI-Driven Phishing Detection market size reached USD 2.85 billion in 2024, reflecting robust adoption across multiple industries. The market is projected to grow at a CAGR of 21.9% during the forecast period, reaching USD 20.1 billion by 2033. This rapid expansion is primarily fueled by the escalating sophistication of phishing attacks and the urgent need for advanced, automated security solutions worldwide.

One of the most significant growth factors propelling the AI-Driven Phishing Detection market is the exponential increase in phishing incidents, both in terms of frequency and complexity. Cybercriminals are leveraging advanced techniques such as deepfakes, spear-phishing, and social engineering, making it increasingly difficult for traditional security solutions to keep pace. As a result, organizations across sectors are turning to AI-driven technologies that can analyze vast datasets, detect subtle anomalies, and respond to threats in real time. The ability of AI to continuously learn and adapt to new attack vectors makes it an indispensable tool in the modern cybersecurity arsenal, driving sustained investment and adoption across both private and public sectors.

Another key driver of the AI-Driven Phishing Detection market is the growing digital transformation across enterprises of all sizes. As more organizations migrate to cloud-based environments and adopt hybrid work models, the attack surface has expanded dramatically. This shift has heightened the need for comprehensive security solutions that can protect endpoints, networks, emails, and mobile devices seamlessly across distributed environments. AI-powered phishing detection platforms offer the scalability and agility required to safeguard dynamic digital ecosystems, further accelerating market growth. Additionally, regulatory mandates and compliance requirements in sectors such as BFSI, healthcare, and government are compelling organizations to adopt advanced threat detection mechanisms to avoid costly breaches and penalties.

Furthermore, the rising awareness about the financial and reputational risks associated with phishing attacks is catalyzing investments in AI-driven security solutions. High-profile breaches and data leaks have underscored the inadequacies of legacy security frameworks, prompting enterprises to prioritize proactive threat detection and response strategies. AI-driven solutions not only enhance detection accuracy but also reduce response times, minimize false positives, and free up valuable security resources. The integration of AI with other emerging technologies, such as machine learning, natural language processing, and behavioral analytics, is amplifying the effectiveness of phishing detection systems, ensuring that organizations remain a step ahead of cyber adversaries.

From a regional perspective, North America currently dominates the global AI-Driven Phishing Detection market, owing to its mature cybersecurity ecosystem, high incidence of cyberattacks, and substantial investments in advanced technologies. However, Asia Pacific is emerging as the fastest-growing region, driven by rapid digitalization, increasing internet penetration, and heightened awareness about cybersecurity threats. Europe also holds a significant market share, supported by stringent data protection regulations and a strong focus on enterprise security. Meanwhile, Latin America and the Middle East & Africa are witnessing steady growth as organizations in these regions ramp up their cybersecurity infrastructure to counter rising phishing threats.

Component Analysis

The AI-Driven Phishing 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, as organizations increasingly deploy AI-powered platforms for real-time threat detection and automated respon

The phishing url dataset contains synthetic data of urls - some regular and some used for phishing. This is the training dataset.The dataset is based on the project (https://github.com/Rohith-2/url_classification_dl) byRohith Ramakrishnan (https://www.linkedin.com/in/rohith-ramakrishnan-54094a1a0/) and others, accompanied bya blog post (https://medium.com/nerd-for-tech/url-feature-engineering-and-classification-66c0512fb34d>).The dataset is released under Creative Commons Zero v1.0 Universal (CC0 1.0).

The Bahrain cybersecurity market, valued at $402.16 million in 2025, is projected to experience robust growth, driven by increasing digitalization across various sectors and heightened cybersecurity threats. The compound annual growth rate (CAGR) of 5.67% from 2025 to 2033 indicates a significant expansion in market size over the forecast period. Key drivers include the rising adoption of cloud computing, the growing importance of data protection regulations, and the increasing sophistication of cyberattacks targeting critical infrastructure and financial institutions. The BFSI, IT and Telecom, and government sectors are major contributors to this growth, fueled by their reliance on digital technologies and sensitivity to data breaches. The market is segmented into solutions (application security, cloud security, data security, identity and access management, etc.), services (professional and managed services), and deployment models (cloud and on-premise). The competitive landscape features a mix of global giants like Microsoft, IBM, and Cisco, alongside specialized regional players. The increasing prevalence of ransomware attacks, phishing scams, and data leaks will continue to propel demand for advanced cybersecurity solutions and services in Bahrain. The strategic adoption of proactive security measures, such as advanced threat detection and incident response systems, is expected to gain traction. Growth will also be driven by government initiatives aimed at strengthening national cybersecurity infrastructure and the development of a skilled cybersecurity workforce. While the market faces challenges such as budget constraints for smaller businesses and a shortage of skilled cybersecurity professionals, the overall outlook remains positive, with significant investment opportunities anticipated for cybersecurity solution providers and service companies focused on meeting the evolving needs of businesses and government agencies in Bahrain. Specific market segments, like cloud security and managed security services, are expected to exhibit particularly strong growth, reflecting the evolving security requirements of a rapidly digitalizing economy. This comprehensive report provides an in-depth analysis of the Bahrain cybersecurity market, covering the period 2019-2033. With a base year of 2025 and an estimated year of 2025, this report offers valuable insights for businesses, investors, and policymakers seeking to understand the dynamics of this rapidly evolving sector. The market is segmented by offering (solutions and services), deployment (cloud and on-premise), and end-user industry, offering a granular view of the market landscape. The report also analyzes key market trends, driving forces, challenges, and growth opportunities, and profiles leading players in the Bahrain cybersecurity market. This report is a must-have for anyone looking to navigate the complexities of the Bahrain cybersecurity market. Recent developments include: December 2023: Resecurity, a cybersecurity firm, officially rolled out its advanced Identity Protection solution in Bahrain. This launch took place after the Arab International Cybersecurity Summit, held at Exhibition World Bahrain and hosted by the National Cyber Security Center., December 2023: Risk Associates Bahrain took a pivotal step in bolstering cybersecurity by forging a strategic alliance with Oman's National Security Services Group (NSSG). NSSG, as the local provider of PCI DSS Audit compliance services, is poised to transform cybersecurity within the BFSI industry.. Key drivers for this market are: Digital Transformation Technologies and Rise of Security Intelligence, High Potential Damages From Attacks on Critical Infrastructure and Increasing Sophistication of Attacks; Increase in Adoption of Data-intensive Approach and Decisions. Potential restraints include: Digital Transformation Technologies and Rise of Security Intelligence, High Potential Damages From Attacks on Critical Infrastructure and Increasing Sophistication of Attacks; Increase in Adoption of Data-intensive Approach and Decisions. Notable trends are: Rise in Digital Transformation Technologies is Expected to Drive the Market.