The largest reported data leakage as of January 2024 was the Cam4 data breach in March 2020, which exposed more than 10 billion data records. The second-largest data breach in history so far, the Yahoo data breach, occurred in 2013. The company initially reported about one billion exposed data records, but after an investigation, the company updated the number, revealing that three billion accounts were affected. The National Public Data Breach was announced in August 2024. The incident became public when personally identifiable information of individuals became available for sale on the dark web. Overall, the security professionals estimate the leakage of nearly three billion personal records. The next significant data leakage was the March 2018 security breach of India's national ID database, Aadhaar, with over 1.1 billion records exposed. This included biometric information such as identification numbers and fingerprint scans, which could be used to open bank accounts and receive financial aid, among other government services.

Cybercrime - the dark side of digitalization As the world continues its journey into the digital age, corporations and governments across the globe have been increasing their reliance on technology to collect, analyze and store personal data. This, in turn, has led to a rise in the number of cyber crimes, ranging from minor breaches to global-scale attacks impacting billions of users – such as in the case of Yahoo. Within the U.S. alone, 1802 cases of data compromise were reported in 2022. This was a marked increase from the 447 cases reported a decade prior. The high price of data protection As of 2022, the average cost of a single data breach across all industries worldwide stood at around 4.35 million U.S. dollars. This was found to be most costly in the healthcare sector, with each leak reported to have cost the affected party a hefty 10.1 million U.S. dollars. The financial segment followed closely behind. Here, each breach resulted in a loss of approximately 6 million U.S. dollars - 1.5 million more than the global average.

View Data Breach Notification Reports, which include how many breaches are reported each year and the number of affected residents.

Explore the historical Whois records related to ios-security-breach.com (Domain). Get insights into ownership history and changes over time.

Explore the historical Whois records related to breach.biz (Domain). Get insights into ownership history and changes over time.

Washington law requires entities impacted by a data breach to notify the Attorney General’s Office (AGO) when more than 500 Washingtonians personal information was compromised as a result of the breach. This dataset breaks out the individual types of breached personal information that were identified in each notice our office received. This data is used to produce the AGO’s Annual Data Breach Report. For additional statistics relating to data breaches, also see the main dataset at: https://data.wa.gov/Consumer-Protection/Data-Breach-Notifications-Affecting-Washington-Res/sb4j-ca4h.

This database includes observed characteristics from 12 tailings dam breach events, with a specific focus on observations that are needed for numerical modelling. The characteristics relevant to modelling include outflow volumes, breach processes, breach geometries, and runout observations local to the downstream area. The new database sheds light on the diversity of outflow materials, facility arrangements, breach processes, and downstream environments that affect the breach development and tailings runout. Familiarity with case studies is a crucial element of expert judgement for forward-analysis of tailings dam breaches, which this database supports. The database can also be used to define model inputs for back-analysis of additional tailings dam breach events, and simultaneously provides calibration or validation constraints with the runout observations.

In this document, comprehensive datasets are presented to advance research on information security breaches. The datasets include data on disclosed information security breaches affecting S&P500 companies between 2020 and 2023, collected through manual search of the Internet. Overall, the datasets include 504 companies, with detailed information security breach and financial data available for 97 firms that experienced a disclosed information security breach. This document will describe the datasets in detail, explain the data collection procedure and shows the initial versions of the datasets. Contact at Tilburg University Francesco Lelli Data files: 6 raw Microsoft Excel files (.xls) Supplemental material: Data_Publication_Package.pdf Detailed description of the data has been released in the following preprint: [Preprint in progress] Structure data package The folder contains the 6 .xls documents, the data publication package. Link to the preprint describing the dataset is in the description of the dataset itself. The six .xls documents are also present in their preferred file format csv (see Notes for further explanation). Production date: 01-2024---- 05-2024 Method: Data on information security breaches through manual search of the Internet, financial data through Refinitiv (LSEG). (Approval obtained from Refinitiv to publish these data) Universe: S&P500 companies Country / Nation: USA

Explore historical ownership and registration records by performing a reverse Whois lookup for the email address breached.com@contactprivacy.com..

The Security Baseline Check market is experiencing robust growth, driven by the increasing sophistication of cyber threats and the stringent regulatory compliance requirements across various industries. The market, estimated at $15 billion in 2025, is projected to maintain a healthy Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $50 billion by 2033. This expansion is fueled by several key factors. Firstly, the rising adoption of cloud computing and digital transformation initiatives across SMEs and large enterprises necessitates comprehensive security assessments. Secondly, the increasing frequency and severity of data breaches are compelling organizations to proactively invest in robust security baseline checks to mitigate risks and protect sensitive data. Furthermore, evolving regulatory landscapes like GDPR and CCPA mandate stringent security protocols, further bolstering the demand for these services. The market segmentation reveals a strong emphasis on host security checks, followed by database and network security equipment checks, reflecting the criticality of securing core infrastructure components. Geographically, North America and Europe currently hold significant market share, driven by high technological adoption and stringent security regulations. However, rapidly growing digital economies in Asia Pacific and the Middle East & Africa present lucrative growth opportunities. The competitive landscape is characterized by a mix of established cloud providers like Alibaba Cloud, Amazon, Microsoft, and Huawei Cloud, alongside specialized security firms like OWASP and Antiy Labs. These players are constantly innovating to offer comprehensive and integrated security solutions that meet the evolving needs of their clients. While the market is experiencing substantial growth, challenges such as the high cost of implementation, integration complexities, and the need for skilled professionals could potentially restrain its growth. However, the overall market trajectory points towards a sustained period of expansion, driven by the imperative to secure digital assets and comply with regulatory requirements. The continued evolution of cybersecurity threats will further fuel the demand for sophisticated baseline checks across all segments and regions.

Between January and September 2024, healthcare organizations in the United States saw 491 large-scale data breaches, resulting in the loss of over 500 records. This figure has increased significantly in the last decade. To date, the highest number of large-scale data breaches in the U.S. healthcare sector was recorded in 2023, with a reported 745 cases.

The Data-Loss Prevention (DLP) market is experiencing robust growth, driven by increasing cyber threats and stringent data privacy regulations like GDPR and CCPA. The market, estimated at $15 billion in 2025, is projected to achieve a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033, reaching approximately $40 billion by 2033. This expansion is fueled by the rising adoption of cloud computing, the proliferation of mobile devices, and the growing need to protect sensitive data across diverse environments. Key market drivers include the escalating costs associated with data breaches, the increasing awareness of data security risks amongst organizations, and the growing demand for advanced DLP solutions that can effectively address sophisticated attack vectors. Market segmentation reveals strong growth across all application areas—individuals, families, and enterprises—with the enterprise segment dominating due to its higher spending capacity and greater vulnerability to data breaches. The advanced measures segment within the DLP solutions category is experiencing particularly rapid expansion, driven by the demand for AI-powered threat detection and response capabilities. Geographic regions such as North America and Europe currently hold significant market share, but Asia-Pacific is poised for substantial growth due to increasing digitalization and rising adoption of DLP solutions in emerging economies. However, the market faces certain restraints, including the high cost of implementation and maintenance of DLP solutions, the complexity of integrating DLP technologies with existing security infrastructure, and the shortage of skilled cybersecurity professionals. Despite these challenges, the overall outlook for the DLP market remains positive. The increasing sophistication of cyberattacks and the growing regulatory landscape are expected to propel the adoption of more robust and comprehensive DLP solutions. Furthermore, advancements in artificial intelligence (AI) and machine learning (ML) are playing a significant role in enhancing the effectiveness of DLP technologies. Continuous innovation in areas such as data classification, anomaly detection, and endpoint security is contributing to the development of more sophisticated and adaptable DLP solutions, catering to the evolving needs of individuals, families, and enterprises alike. The market's trajectory strongly indicates a continued rise in demand for DLP solutions across diverse sectors, reinforcing the crucial role of data protection in the increasingly digital world.

Some industries are affected by cyber attacks more than others. These next cybersecurity statistics detail specifically who is affected by cyber-attacks and why they are.

The number of data breaches fluctuated in Poland in the observed period. The second quarter of 2020 recorded the highest number of data breaches. In the third quarter of 2024, this number decreased to over 150,000; however, it was 907 percent higher than in the previous quarter.

Hurricane Sandy made U.S. landfall, coincident with astronomical high tides, near Atlantic City, New Jersey, on October 29, 2012. The storm, the largest on historical record in the Atlantic basin, affected an extensive area of the east coast of the United States. The highest waves and storm surge were focused along the heavily populated New York and New Jersey coasts. At the height of the storm, a record significant wave height of 9.6 meters (m) was recorded at the wave buoy offshore of Fire Island, New York. During the storm an overwash channel opened a breach in the location of Old Inlet, in the Otis Pike High Dunes Wilderness Area. This breach is referred to as the wilderness breach (fig 1).

Fire Island, New York is the site of a long term coastal morphologic change and processes project conducted by the U.S. Geological Survey (USGS). One of the objectives of the project was to understand the morphologic evolution of the barrier system on a variety of time scales (days - years - decades - centuries). In response to Hurricane Sandy, this effort continued with the intention of resolving storm impact and the response and recovery of the beach. The day before Hurricane Sandy made landfall (October 28, 2012), a USGS field team conducted differential global positioning system (DGPS) surveys at Fire Island to quantify the pre-storm morphologic state of the beach and dunes. The area was re-surveyed after the storm, as soon as access to the island was possible. In order to fully capture the recovery of the barrier system, the USGS Hurricane Sandy Supplemental Fire Island Study was established to include collection in the weeks, months, and years following the storm.

As part of the USGS Hurricane Sandy Supplemental Fire Island Study, the beach is monitored periodically to enable better understanding of post-Sandy recovery. The alongshore state of the beach is recorded using a DGPS to collect data around the mean high water elevation (MHW; 0.46 meter North American Vertical Datum of 1988) to derive a shoreline, and the cross-shore response and recovery are measured along a series of 15 profiles. Monitoring continued in the weeks following Hurricane Sandy with additional monthly collection through April 2013 and repeat surveys every 2–3 months thereafter until October 2014. Bi-annual surveys have been collected through September 2016. Beginning in October 2014 the USGS also began collecting shoreline data at the Wilderness breach. The shoreline collected was an approximation of the MHW shoreline. The operator walked an estimated MHW elevation above the water line and below the berm crest, using knowledge of tides and local conditions to interpret a consistent shoreline. See below for survey collection dates for all data types.

This shapefile FIIS_Breach_Shorelines.shp consists of Fire Island, NY breach shorelines collected following an interpreted MHW shoreline as identified in the field.

Oct 28 2012 (MHW shoreline/Cross-shore data) Nov 01 2012 (MHW shoreline/Cross-shore data) Nov 04 2012 (Cross-shore data only) Dec 01 2012 (MHW shoreline/Cross-shore data) Dec 12 2012 (MHW shoreline/Cross-shore data) Jan 10 2013 (MHW shoreline/Cross-shore data) Feb 13 2013 (MHW shoreline/Cross-shore data) Mar 13 2013 (MHW shoreline/Cross-shore data) Apr 09 2013 (MHW shoreline/Cross-shore data) Jun 24 2013 (MHW shoreline/Cross-shore data) Sep 18 2013 (MHW shoreline/Cross-shore data) Dec 03 2013 (MHW shoreline/Cross-shore data) Jan 29 2014 (MHW shoreline/Cross-shore data) Jun 11 2014 (Cross-shore data only) Sep 09 2014 (MHW shoreline/Cross-shore data) Oct 07 2014 (Cross-shore data/MHW Breach shoreline) Jan 21 2015 (MHW shoreline/Cross-shore data/Breach shoreline) Mar 19 2015 (MHW shoreline/Cross-shore data) May 16 2015 (MHW shoreline/Cross-shore data/Breach shoreline) Set 28 2015 (MHW shoreline/Cross-shore data/Breach shoreline) Jan 21 2016 (MHW shoreline/Cross-shore data) Jan 25 2016 (MHW shoreline/Cross-shore data) Apr 06 2016 (Cross-shore data only) Apr 11 2016 (MHW shoreline/Cross-shore data/Breach shoreline) Jun 16 2016 (Cross-shore data only) Sep 27 2016 (MHW shoreline/Cross-shore data/Breach shoreline)

The Data Loss Prevention (DLP) market is experiencing robust growth, projected to reach $2.13 billion in 2025 and exhibiting a Compound Annual Growth Rate (CAGR) of 29.52% from 2025 to 2033. This surge is driven by the increasing frequency and severity of data breaches, stringent data privacy regulations like GDPR and CCPA, and the rising adoption of cloud computing and remote work models. Businesses across all sectors are prioritizing data security to protect sensitive customer information, intellectual property, and financial data, fueling demand for comprehensive DLP solutions. The market segmentation reveals key trends. Cloud-based DLP deployments are gaining significant traction due to their scalability, accessibility, and cost-effectiveness. Among technologies, endpoint DLP is witnessing strong adoption due to the proliferation of mobile devices and the need for robust data protection at the endpoint level. Network DLP solutions are also in high demand, enabling organizations to monitor and control data flow across their network infrastructure. North America currently holds a significant market share, driven by early adoption of DLP technologies and stringent regulatory frameworks. However, the APAC region, particularly China and Japan, is poised for rapid growth due to increasing digitalization and rising awareness of data security risks. Key players like Acronis, Broadcom, Check Point, and Cisco are strategically investing in R&D, acquisitions, and partnerships to enhance their product offerings and expand their market presence. The competitive landscape is characterized by intense innovation, with companies focusing on advanced features like AI-powered threat detection, automated remediation, and improved integration with existing security infrastructure. Despite this growth, market restraints include the high initial investment cost of DLP solutions, the complexity of implementation and management, and the potential for false positives.

The Firewall as a Service (FWaaS) market is experiencing robust growth, projected to reach $1.04 billion in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 31.8% from 2025 to 2033. This expansion is driven by several key factors. The increasing adoption of cloud-based infrastructure and applications necessitates robust security solutions like FWaaS, offering scalability, cost-effectiveness, and simplified management compared to traditional on-premise firewalls. Furthermore, the rise in sophisticated cyber threats and data breaches fuels demand for advanced security features offered by FWaaS providers, including intrusion prevention, malware protection, and advanced threat intelligence. The shift towards remote work models also significantly boosts the market, as organizations require secure access to corporate networks from various locations. The BFSI (Banking, Financial Services, and Insurance), Healthcare, and Retail sectors are leading adopters, driven by stringent regulatory compliance and the need to protect sensitive customer data. The competitive landscape is characterized by a mix of established players like Check Point, Palo Alto Networks, and Fortinet, alongside emerging vendors offering specialized solutions. Differentiation is achieved through advanced features, integration capabilities, and pricing models. While the market exhibits strong growth potential, challenges remain, including concerns about security vulnerabilities, vendor lock-in, and the need for robust integration with existing IT infrastructure. The geographic distribution shows a concentration in North America and Europe initially, but APAC is expected to witness significant growth fueled by increasing digital adoption and economic development in regions like China and India. This continued expansion will depend on factors such as advancements in artificial intelligence (AI) and machine learning (ML) for threat detection, as well as the ongoing evolution of cloud security architectures.

Over 1.1 billion personal data points were exposed during breaches in Russia in 2023. That was the highest figure over the observed period. To compare, in the previous year, the number of data points exposed stood at approximately 770 million.

DESCRIPTION

Sequences identified as Influenza A virus, Spodoptera frugiperda rhabdovirus and Nipah henipavirus have been previously identified within the early HiSeq 1000 and HiSeq 3000 sequencing data of SARS-CoV-2, SRR11092059,SRR11092060,SRR11092061 and SRR11092062, and were being used to support the hypothesis that a "simultaneous outbreak of multiple zoonotic viruses" have happened in the Huanan Seafood market. https://doi.org/10.31219/osf.io/s4td6

However, a closer examination of these sequences revealed that they were not sequences of actual wild viruses, but were in stead fragments left behind from PCR products and cloning vectors harboring both cDNA clones and infectious clones of such viruses, with evidence of viral sequences being joined directly to DNA sequences of vector and non-human origin within the same short reads.

Here are the vector sequences and PCR product-like sequences recovered from the earliest WIV SRA sequencing data of Human SARS-CoV-2 from dataset SRR11092059,SRR11092060,SRR11092061,SRR11092062.

Sequences associated with Vectors and PCR products from 3 distinct viral species have been obtained: The 3'-end of a Nipah Henipahvirus with fusion to a Hepatitis D virus Ribozyme, a T7 terminator and a Tetracycline resistance gene, The 5'-end of the same Nipah Henipahvirus with fusion to sequences found in diverse vectors, A complete vector genome encoding the HA gene of Influenza A virus subtype H7N9 under a CMV promoter and a bgH polyA terminator, and 221 Contiguous sequences corresponding to the Spodoptera frugiperda rhabdovirus reference genome fused to sequences that were homologous to multiple Plastid sequences and Notably Mitochondrial sequences of Rodents.

As sequences corresponding to a rescued infectious clone of a BSL-4 organism (Nipah Henipahvirus) were found in sample sequences that supposedy represents patient samples that were obtained from Hospital ICU and sequenced in a pathogen diagnosis laboratory (which is separate from the Virology Research laboratory which is implied by the context of an Infectious Clone of such an organism, evident by the 3'-HDV ribozyme and T7 terminator fused directly to the 3'-terminus of the Nipah Henipahvirus reads), The discovery of artifact-containing sequences of at least 3 different pathogen species that are phylogenetically and methodologically distinct from each other in samples that were supposedly submitted by a laboratory that is Separate from the virological research laboratories that could have hosted such clone sequences imply extensive crosstalk and cross-contamination between the various laboratories within the Wuhan Institute of Virology, which includes at least one BSL-4 laboratory with evidence of containment breach of a BSL-4 organism and it's subsequent introduction into RNA-seq samples that were processed by a laboratory of distinct and separate purposes than the basic virological research evidenced by the Infectious Clone of the Hipah Henipahvirus.

Such a discovery therefore likely imply a major security breach happening within the Wuhan institute of Virology at the time when the first sequences of SARS-CoV-2 was sampled and sequenced, which have important implications on the origins of the SARS-CoV-2 virus itself.

METHODS

The metagenomic sequencing datasets, SRR11092059,SRR11092060,SRR11092061 and SRR11092062 were first analyzed using the NCBI phylogenetic analysis tool, which identified viral sequences that is not related to SARS-CoV-2 itself. These include Influenza A virus (IAV, subtype H7N9), Spodoptera frugiperda rhabdovirus and Nipah Henipahvirus.

The datasets were then subjected to BLAST search using MEGABLAST against the reference sequences of such viruses to verify the existence of the viral sequences and determine the exact sybtype of such viruses and the closest sequences on GenBank that corresponds to the reads. There seuqences are MH926031.1 for the Spodoptera frugiperda rhabdovirus, KY199425.1 for the Influenza A virus and AY988601.1 for the Nipah Henipahvirus.

A second round BLAST analysis with these identified sequences were then performed, which unexpectedly revealed numerous reads corresponding to Cloning vectors and non-human Mitochondrial and Plastid sequences being fused directly to the sequences of the identified viral species. Reads were then downloaded and subjected to assembly using the CAP3 sequence assembly program and the EGASSEMBLER tool. Contig sequences were then queried against the NCBI nr/nt database which unanimously identified the original sample sequences as viral sequences inserted into cloning vectors.

The complete sequence of the Influenza A virus Haemagluttinin (HA) gene clone was obtained from SRR11092061,SRR11092062 using multiple rounds of BLAST search and sequence assembly expansion on the existing vector-virus junction contigs, and a partial sequence corresponding the 3'-end of Nipah Henipahvirus AY988601.1 fused to a 3'-HDV ribozyme, T7 terminator and a Tet resistance gene was obtained from SRR11092059. In addition, 221 Contig sequences corresponding to the Rhabdovirus MH926031.1 fused to Chloroplast sequence MN524635.1 and Rodent Mitochondrial sequence MT241668.1 have been recovered from SRR11092061.

We then performed a BLAST search using the identified vector sequences on SRR11092059,SRR11092060,SRR11092061 and SRR11092062, which confirms the existence of these two vetor sequences in all 4 datasets.

Scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center in St. Petersburg, Florida, conducted a bathymetric survey of Fire Island, New York, from October 5 to 10, 2014. The U.S. Geological Survey is involved in a post-Hurricane Sandy effort to map and monitor the morphologic evolution of the wilderness breach, which formed in October 2012 during Hurricane Sandy, as part of the Hurricane Sandy Supplemental Project GS2-2B. During this study, bathymetry data were collected, using single-beam echo sounders and global positioning systems mounted to personal watercraft, along the Fire Island shoreface and within the wilderness breach, Fire Island Inlet, Narrow Bay, and Great South Bay east of Nicoll Bay. Additional bathymetry and elevation data were collected using backpack and wheel-mounted global positioning systems along the subaerial beach (foreshore and backshore), and flood shoals and shallow channels within the wilderness breach and adjacent shoreface.

This dataset, 20130626_bathy_xyz.zip, consists of single-beam point data collected in June 2013 during a bathymetry survey of the Wilderness Breach and adjacent coastline that has been output in American Standard Code for Information Interchange (ASCII) format. Scientists from the U.S. Army Corps of Engineers (USACE), in collaboration with the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center (SPCMSC), conducted a bathymetric survey from June 22-26, 2013. The survey focused on a breach (Wilderness Breach) created by Hurricane Sandy near Pelican Island, NY, which is located in Great South Bay. A total of 41 shore-perpendicular transects with a 50-meter spacing were collected using a Knudsen 320BP single-beam echosounder, centered on the breach.