I2P is an anonymizing network, offering a simple layer that identity-sensitive applications can use to securely communicate. All data is wrapped with several layers of encryption, and the network is both distributed and dynamic, with no trusted parties. This is the source code release version.
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OpenDNSSEC is software that manages the security of domain names on the Internet. The project intends to drive adoption of Domain Name System Security Extensions (DNSSEC) to further enhance Internet security.
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This is a custom firmware written for the Proxmark3 device. It extends the currently available firmware.
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nfstream is a Python package providing fast, flexible, and expressive data structures designed to make working with online or offline network data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world network data analysis in Python. Additionally, it has the broader goal of becoming a common network data processing framework for researchers providing data reproducibility across experiments.
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MutableSecurity is a Linux CLI program for making cybersecurity solution management easier and more accessible, from deployment and configuration to monitoring. It supports multiple solutions (teler as web IDS, Fail2ban as host IPS, Let's Encrypt for generating SSL certificates, and ClamAV as antimalware), password-based and key-based SSH authentication, and parallel deployment to multiple remote hosts.
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This tool packs up to 4KB of compressed shellcode into an executable binary, near-instantly. The output file will always have the same MD5 hash: 3cebbe60d91ce760409bbe513593e401. Currently, only Linux x86-64 is supported. It would be trivial to port this technique to other platforms, although each version would end up with a different MD5.
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nfstream is a Python package providing fast, flexible, and expressive data structures designed to make working with online or offline network data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world network data analysis in Python. Additionally, it has the broader goal of becoming a common network data processing framework for researchers providing data reproducibility across experiments.
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PacketFence is a network access control (NAC) system. It is actively maintained and has been deployed in numerous large-scale institutions. It can be used to effectively secure networks, from small to very large heterogeneous networks. PacketFence provides NAC-oriented features such as registration of new network devices, detection of abnormal network activities including from remote snort sensors, isolation of problematic devices, remediation through a captive portal, and registration-based and scheduled vulnerability scans.
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I2P is an anonymizing network, offering a simple layer that identity-sensitive applications can use to securely communicate. All data is wrapped with several layers of encryption, and the network is both distributed and dynamic, with no trusted parties. This is the source code release version.
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AIEngine is a packet inspection engine with capabilities of learning without any human intervention. It helps network/security professionals to identify traffic and develop signatures for use them on NIDS, Firewalls, Traffic classifiers and so on.
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This tool can be embedded into AI systems for storing information and deleting it very efficiently by using queues disguising themselves as arrays and adding data and removing the data using pointers and flags.
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Blue Team Training Toolkit (BT3) is an attempt to introduce improvements in current computer network defense analysis training. Based on adversary replication techniques, and with reusability in mind, BT3 allows individuals and organizations to create realistic computer attack scenarios, while reducing infrastructure costs, implementation time and risk. The Blue Team Training Toolkit is written in Python, and it includes the latest versions of Encripto's Maligno and Pcapteller.
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I2P is an anonymizing network, offering a simple layer that identity-sensitive applications can use to securely communicate. All data is wrapped with several layers of encryption, and the network is both distributed and dynamic, with no trusted parties. This is the source code release version.
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This is a small tool written to help decrypt encrypted TP-Link backups.
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Cooper utilizes cooperative mutation to test the binding code of scripting languages to find memory-safe issues. Cooperative mutation simultaneously modifies the script code and the related document objects to explore various code paths of the binding code. To support cooperative mutation, the authors infer the relationship between script code and document objects to guide the two-dimensional mutation. They applied their tool Cooper on three popular commercial PDF tools, Adobe Acrobat, Foxit Reader, and Microsoft Word. Cooper detected 134 previously unknown bugs, which resulted in 33 CVE entries and 22K bug bounties.
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Adversary3 is a tool to navigate the vast www.malvuln.com malware vulnerability dataset.
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nfstream is a Python package providing fast, flexible, and expressive data structures designed to make working with online or offline network data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world network data analysis in Python. Additionally, it has the broader goal of becoming a common network data processing framework for researchers providing data reproducibility across experiments.
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AIEngine is a packet inspection engine with capabilities of learning without any human intervention. It helps network/security professionals to identify traffic and develop signatures for use them on NIDS, Firewalls, Traffic classifiers and so on.
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haveged is a daemon that feeds the /dev/random pool on Linux using an adaptation of the HArdware Volatile Entropy Gathering and Expansion algorithm invented at IRISA. The algorithm is self-tuning on machines with cpuid support, and has been tested in both 32-bit and 64-bit environments. The tarball uses the GNU build mechanism, and includes self test targets and a spec file for those who want to build an RPM.
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Adversary3 is a tool to navigate the vast www.malvuln.com malware vulnerability dataset.
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nfstream is a Python package providing fast, flexible, and expressive data structures designed to make working with online or offline network data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world network data analysis in Python. Additionally, it has the broader goal of becoming a common network data processing framework for researchers providing data reproducibility across experiments.
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PacketFence is a network access control (NAC) system. It is actively maintained and has been deployed in numerous large-scale institutions. It can be used to effectively secure networks, from small to very large heterogeneous networks. PacketFence provides NAC-oriented features such as registration of new network devices, detection of abnormal network activities including from remote snort sensors, isolation of problematic devices, remediation through a captive portal, and registration-based and scheduled vulnerability scans.
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I2P is an anonymizing network, offering a simple layer that identity-sensitive applications can use to securely communicate. All data is wrapped with several layers of encryption, and the network is both distributed and dynamic, with no trusted parties. This is the source code release version.
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nfstream is a Python package providing fast, flexible, and expressive data structures designed to make working with online or offline network data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world network data analysis in Python. Additionally, it has the broader goal of becoming a common network data processing framework for researchers providing data reproducibility across experiments.
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nfstream is a Python package providing fast, flexible, and expressive data structures designed to make working with online or offline network data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world network data analysis in Python. Additionally, it has the broader goal of becoming a common network data processing framework for researchers providing data reproducibility across experiments.
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