Nova is a software application for preventing and detecting hostile network reconnaissance (such as nmap scans). It does this by first creating the Haystack: a large collection of low interaction honeypots using an updated version of Honeyd. Finding real machines on the network becomes like finding a needle in a haystack of fake machines. Second, Nova uses machine learning algorithms to automatically detect and classify attempts at hostile reconnaissance, so there's no need to go searching manually through your honeypot's log files. It provides an easy to use Web-based interface powered by Node.js to configure itself and Honeyd instances.
MASTIFF is a static analysis framework which automates the process of extracting key characteristics from a number of different file formats. To ensure the framework remains flexible and extensible, a community-driven set of plugins is used to perform file analysis and data extraction. While originally designed to support malware, intrusion, and forensic analysis, the framework is well-suited to support a broader range of analytic needs. In a nutshell, MASTIFF allows analysts to focus on analysis rather than figuring out how to parse files.
ARP Neighbor Cache Fingerprinter is a tool that provides a mechanism for remote operating system detection by extrapolating characteristics of the target system's underlying neighbor cache and general ARP behavior. Given the non-existence of any standard specification for how the neighbor cache should behave, several differences in network stack implementations can be used for unique identification. The main disadvantage of this tool versus traditional fingerprinting is that because it's based on a Layer 2 protocol instead of a Layer 3 protocol, the target machine that is being tested must reside on the same Ethernet broadcast domain (usually the same physical network).