Version 3 with 517M hashes and counts of password usage ordered by most to least prevalent Pwned Passwords are 517,238,891 real world passwords previously exposed in data breaches. This exposure makes them unsuitable for ongoing use as they re at much greater risk of being used to take over other accounts. They re searchable online below as well as being downloadable for use in other online system. The entire set of passwords is downloadable for free below with each password being represented as a SHA-1 hash to protect the original value (some passwords contain personally identifiable information) followed by a count of how many times that password had been seen in the source data breaches. The list may be integrated into other systems and used to verify whether a password has previously appeared in a data breach after which a system may warn the user or even block the password outright.

The list contains every wordlist, dictionary, and password database leak that I could find on the internet (and I spent a LOT of time looking). It also contains every word in the Wikipedia databases (pages-articles, retrieved 2010, all languages) as well as lots of books from Project Gutenberg. It also includes the passwords from some low-profile database breaches that were being sold in the underground years ago. The format of the list is a standard text file sorted in non-case-sensitive alphabetical order. Lines are separated with a newline " " character. You can test the list without downloading it by giving SHA256 hashes to the free hash cracker or to @PlzCrack on twitter. Here s a tool for computing hashes easily. Here are the results of cracking LinkedIn s and eHarmony s password hash leaks with the list. The list is responsible for cracking about 30% of all hashes given to CrackStation s free hash cracker, but that figure should be taken with a grain of salt because s

Password Recovery Software Market Outlook

The global password recovery software market size was valued at USD 1.2 billion in 2023 and is expected to reach approximately USD 2.8 billion by 2032, growing at a compound annual growth rate (CAGR) of 9.5% from 2024 to 2032. A significant growth factor propelling the market is the increasing prevalence of cyber-attacks and data breaches, which necessitate robust password recovery solutions.

The growing occurrence of cybersecurity threats has significantly influenced the demand for password recovery software. Enterprises across various sectors, particularly in sensitive domains such as BFSI and healthcare, are increasingly opting for sophisticated recovery solutions to safeguard their data integrity and ensure continuity. This heightened demand is driven by the necessity to prevent unauthorized access and mitigate data loss, evidencing a strong market trajectory for password recovery solutions.

Technological advancements, such as the integration of artificial intelligence and machine learning into password recovery software, have further accelerated market growth. These innovations enhance the efficiency and reliability of software, making it more adept at handling complex password recovery scenarios. Additionally, the proliferation of multi-factor authentication and biometric verification methods is contributing to the evolving landscape of password recovery solutions, offering more secure and user-friendly experiences.

Another pivotal growth factor is the rising adoption of cloud computing and the increasing shift towards digital transformation initiatives by businesses worldwide. Cloud-based password recovery solutions offer scalability, cost-efficiency, and ease of deployment, appealing to organizations seeking to enhance their cybersecurity frameworks. Moreover, as more companies transition to remote working models, the need for robust and accessible password recovery tools has become more pronounced.

In today's digital landscape, the importance of File Recovery Software cannot be overstated. As organizations increasingly rely on digital data, the risk of accidental deletions, hardware failures, and cyber-attacks looms large. File recovery software serves as a critical tool in retrieving lost or corrupted files, ensuring business continuity and data integrity. These solutions are equipped with advanced algorithms that can recover a wide range of file types, from documents and images to databases and system files. As businesses continue to amass vast amounts of data, the demand for efficient and reliable file recovery solutions is expected to grow, paralleling the trends seen in password recovery software.

Regionally, North America held the largest market share in 2023, attributed to the early adoption of advanced cybersecurity measures and the presence of key market players. However, the Asia Pacific region is expected to witness the highest growth rate during the forecast period. Factors such as rapid digitalization, increasing internet penetration, and the rising number of small and medium enterprises (SMEs) are driving the demand for password recovery software in this region.

Component Analysis

The password recovery software market is segmented by component into software and services. The software segment is projected to dominate the market during the forecast period, driven by the continuous advancements in technology and the need for automated solutions to manage password-related issues. Software solutions offer a wide range of functionalities, including password reset tools, recovery protocols, and integration with existing IT infrastructure, making them indispensable for modern enterprises.

Within the software segment, enterprise password management tools are gaining traction due to their ability to streamline password recovery processes and reduce the administrative burden on IT departments. These tools often come equipped with features such as self-service password reset, policy enforcement, and audit trails, ensuring compliance with regulatory standards. The growing emphasis on enhancing user experience and minimizing downtime is further bolstering the demand for sophisticated software solutions.

On the other hand, the services segment encompasses consulting, implementation, and maintenance services. As organizations increasingly recognize the importance of tailored solutions and continuous support,

This database contains benchmark results for simulation of plasma population kinetics and emission spectra. The data were contributed by the participants of the 4th Non-LTE Code Comparison Workshop who have unrestricted access to the database. The only limitation for other users is in hidden labeling of the output results. Guest users can proceed to the database entry page without entering userid and password.

In 2023, ** percent of respondents among IT and cybersecurity leaders in the United States mentioned security misconfigurations as one of the main security risks their company would still face after going passwordless. In addition, ** percent of respondents noted that service accounts connecting databases, applications, platforms, and running processes within their organization would still be vulnerable. Overall, various threats such as phishing attacks, social engineering, biometrics thefts, or man-in-the middle attacks would still be possible even after a company has ceased to use passwords.

Covers data on bonds issued in Washington State since 2000 Search by issuer name, user name, or date range Many official statements and bond covenants for bonds issued since 2008 can be viewed and downloaded No password required

This database automatically captures metadata, the source of which is the GOVERNMENT OF THE REPUBLIC OF SLOVENIA STATISTICAL USE OF THE REPUBLIC OF SLOVENIA and corresponding to the source database entitled “Individuals who have used the Internet in the last 12 months and have a digital certificate or certificate or one-time password generator smsPASS and the reasons why they do not have them, by age class and sex, Slovenia, 2019”.

Actual data are available in Px-Axis format (.px). With additional links, you can access the source portal page for viewing and selecting data, as well as the PX-Win program, which can be downloaded free of charge. Both allow you to select data for display, change the format of the printout, and store it in different formats, as well as view and print tables of unlimited size, as well as some basic statistical analyses and graphics.

The Ligand Protein Database is designed to allow the selection of complexes based on various properties of receptors and ligands for the design and parametrization of new scoring functions or to assess and improve existing ones. Moreover, for each complex, a continuum of ligand positions ranging from the crystallographic position to points on the surface of the protein receptor allows an assessment of the energetic behavior of particular scoring functions. Access to the database is password protected. To obtain access to the LPDB, complete a form, available online, have it signed by your research advisor, and fax the completed form back to the attention of Professor Charles L. Brooks III, (858) 784-8688. There is no fee for academic use of the LPDB. We are currently working out details for licensing to our colleagues in industry. Please contact Professor Brooks to obtain current information on access to the LPDB.

The (Docker) source files for creating a read-only database container.

Note:

"tail -F /var/log/mysql/error.log" (after the demo of selecting all data) makes the container keep alive as a MySQL server.

To be Updated:

The database user and password are still hardcoded.

This dataset contains updates on export and import activities, including detailed records of transactions, commodities, volumes, and values across various countries provided by Volza FZ LLC.

This is supporting online material for the submission ``Supporting Quality Assurance with Automated Process-Centric Quality Constraints Checking''Contains:- Neo4J database containing the Jira issues and changes from the Dronology data set (all names of involved users have been anonymized in the issues and change events)- Process definitions and constraints for Dronology (a set of Drools .drl files in ProcessConstraints.zip) - java package names have been obfuscated to adhere to doubleblind requirements. DRL files are informative only, as due to double-blind requirements, we cannot provide the source code at this stage. We will make it available publicly via Github upon paper publication.- jupyter notebook analysing the output from evaluation runs (Evaluation.ipynb)- Raw data from the evaluation runs ( .csv files zipped in PerProcessedAndPerConstraintsCSVfiles.zip)Due to confidentiality agreements, we cannot provide any data from the industrial case study.To install the Neo4J database:1) Prepare an empty Neo4J database (version 3.5.15) e.g., useing Neo4J Desktop2) Extract the databases.zip file3) Copy the graph.db folder and store_lock file into the databases folder of your neo4j database4) Start the neo4j database, the password is: dronology

Context

The awesome datasets graph is a Neo4j graph database which catalogs and classifies datasets and data sources as scraped from the Awesome Public Datasets GitHub list.

Content

We started with a simple list of links on the Awesome Public Datasets page. We now have a semantic graph database with 10 labels, five relationship types, nine property keys, and more than 400 nodes. All within 1MB of database footprint. All database operations are query driven using the powerful and flexible Cypher Graph Query Language.

The download includes CSV files which were created as an interim step after scraping and wrangling the source. The download also includes a working Neo4j Graph Database. Login: neo4j | Password: demo.

Acknowledgements

Data scraped from Awesome Public Datasets page. Prepared for the book Data Science Solutions.

Inspiration

While we have done basic data wrangling and preparation, how can this graph prove useful for your data science workflow? Can we record our data science project decisions taken across workflow stages and how the data catalog (datasources, datasets, tools) use cases help in these decisions by achieving data science solutions strategies?

Central database to house data on morpholino screens currently containing over 700 morpholinos including control and multiple morpholinos against the same target. A publicly accessible sequence-based search opens this database for morpholinos against a particular target for the zebrafish community. Morpholino Screens: They set out to identify all cotranslationally translocated genes in the zebrafish genome (Secretome/CTT-ome). Morpholinos were designed against putative secreted/CTT targets and injected into 1-4 cell stage zebrafish embryos. The embryos were observed over a 5 day period for defects in several different systems. The first screen examined 184 gene targets of which 26 demonstrated defects of interest (Pickart et al. 2006). A collaboration with the Verfaillie laboratory examined the knockdown of targets identified in a comparative microarray analysis of hematopoietic stem cells demonstrating how microarray and morpholino technologies can be used in conjunction to enrich for defects in specific developmental processes. Currently, many collaborations are underway to identify genes involved in morphological, kidney, skin, eye, pigment, vascular and hematopoietic development, lipid metabolism and more. The screen types referred to in the search functions are the specific areas of development that were examined during the various screens, which include behavior, general morphology, pigmentation, toxicity, Pax2 expression, and development of the craniofacial structures, eyes, kidneys, pituitary, and skin. Only data pertaining to specific tests performed are presented. Due to the complexity of this international collaboration and time constraints, not all morpholinos were subjected to all screen types. They are currently expanding public access to the database. In the future we will provide: * Mortality curves and dose range for each morpholino * Preliminary data regarding the effectiveness of each morpholino * Expanded annotation for each morpholino * External linkage of our morpholino sequences to ZFIN and Ensembl. To submit morpholino-knockdown results to MODB please contact the administrator for a user name and password.

In 2018 the IPERION-CH Grounds Database was presented to examine how the data produced through the scientific examination of historic painting preparation or grounds samples, from multiple institutions could be combined in a flexible digital form. Exploring the presentation of interrelated high resolution images, text, complex metadata and procedural documentation. The original main user interface is live, though password protected at this time. Work within the SSHOC project aimed to reformat the data to create a more FAIR data-set, so in addition to mapping it to a standard ontology, to increase Interoperability, it has also been made available in the form of open linkable data combined with a SPARQL end-point. A draft version of this live data presentation can been found Here.

This is a draft data-set and further work is planned to debug and improve its semantic structure.This deposit contains the CIDOC-CRM mapped data formatted in XML and an example model diagram representing some of the key relationships covered in the data-set.

This database contains benchmark results for simulation of plasma population kinetics and emission spectra. The data were contributed by the participants of the 3rd Non-LTE Code Comparison Workshop who have unrestricted access to the database. The only limitation for other users is in hidden labeling of the output results. Guest users can proceed to the database entry page without entering userid and password.

Introduction

This datasets have SQL injection attacks (SLQIA) as malicious Netflow data. The attacks carried out are SQL injection for Union Query and Blind SQL injection. To perform the attacks, the SQLMAP tool has been used.

NetFlow traffic has generated using DOROTHEA (DOcker-based fRamework fOr gaTHering nEtflow trAffic). NetFlow is a network protocol developed by Cisco for the collection and monitoring of network traffic flow data generated. A flow is defined as a unidirectional sequence of packets with some common properties that pass through a network device.

Datasets

The firts dataset was colleted to train the detection models (D1) and other collected using different attacks than those used in training to test the models and ensure their generalization (D2).

The datasets contain both benign and malicious traffic. All collected datasets are balanced.

The version of NetFlow used to build the datasets is 5.

Infrastructure and implementation

Two sets of flow data were collected with DOROTHEA. DOROTHEA is a Docker-based framework for NetFlow data collection. It allows you to build interconnected virtual networks to generate and collect flow data using the NetFlow protocol. In DOROTHEA, network traffic packets are sent to a NetFlow generator that has a sensor ipt_netflow installed. The sensor consists of a module for the Linux kernel using Iptables, which processes the packets and converts them to NetFlow flows.

DOROTHEA is configured to use Netflow V5 and export the flow after it is inactive for 15 seconds or after the flow is active for 1800 seconds (30 minutes)

Benign traffic generation nodes simulate network traffic generated by real users, performing tasks such as searching in web browsers, sending emails, or establishing Secure Shell (SSH) connections. Such tasks run as Python scripts. Users may customize them or even incorporate their own. The network traffic is managed by a gateway that performs two main tasks. On the one hand, it routes packets to the Internet. On the other hand, it sends it to a NetFlow data generation node (this process is carried out similarly to packets received from the Internet).

The malicious traffic collected (SQLI attacks) was performed using SQLMAP. SQLMAP is a penetration tool used to automate the process of detecting and exploiting SQL injection vulnerabilities.

The attacks were executed on 16 nodes and launch SQLMAP with the parameters of the following table.

Every node executed SQLIA on 200 victim nodes. The victim nodes had deployed a web form vulnerable to Union-type injection attacks, which was connected to the MYSQL or SQLServer database engines (50% of the victim nodes deployed MySQL and the other 50% deployed SQLServer).

The web service was accessible from ports 443 and 80, which are the ports typically used to deploy web services. The IP address space was 182.168.1.1/24 for the benign and malicious traffic-generating nodes. For victim nodes, the address space was 126.52.30.0/24.
The malicious traffic in the test sets was collected under different conditions. For D1, SQLIA was performed using Union attacks on the MySQL and SQLServer databases.

However, for D2, BlindSQL SQLIAs were performed against the web form connected to a PostgreSQL database. The IP address spaces of the networks were also different from those of D1. In D2, the IP address space was 152.148.48.1/24 for benign and malicious traffic generating nodes and 140.30.20.1/24 for victim nodes.

To run the MySQL server we ran MariaDB version 10.4.12.
Microsoft SQL Server 2017 Express and PostgreSQL version 13 were used.

In 2022, the most used authentication technology by companies worldwide was multi-factor authentication (MFA), followed by cloud-based single sign-on. Moreover, ** percent of respondents stated that their company used a passwordless authentication system.

An additional layer of security over the passwords

MFA uses extra verification information over a generic password, resulting in an additional layer of authentication for security, with a market size close to ** billion U.S. dollars worldwide in 2022. Most MFA authentication methods rely on one of three types of information: something you know - like a password or PIN; something you have - like a security token or smartphone; or something you are - like a biometric such as fingerprints or facial recognition.

Barriers to the adoption of MFA

Implementing MFA can be challenging due to user resistance with concerns of mass surveillance using linked databases. Some of the other concerns include poor user experience and difficulties in integration into legacy systems. To overcome these adoption barriers, educating users about the benefits and risks of MFA with regard to biometrics and making the authentication process as seamless and user-friendly as possible is essential. 

The Regional DataBase, RDB, is a database and estimation system where countries upload catch and sample data for commercial fish species requested in Regional Coordination Groups' Data Call for coordination of sampling of commercial fish species. To upload data, work on data, raise/estimate data and to download data, a password is required.

PRV publishes the contents of the Swedish Trademark Database via a collection of files that can be downloaded from our ftp server. The data files and associated image files (compressed in zip archives) are made available in XML format and are updated daily. They are available via a full withdrawal as well as via daily incremental updates.

The database is available from our ftp-server with the following connection information: URL: ftp://opendata.prv.se Username: OpenDataSource Password: opendata

Further documentation about usage and formats is available on the ftp-server in the folder "TrademarkExport/NewExport/Documentation".