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Derek's Projects

csirt-collect icon csirt-collect

PowerShell script to collect memory and (triage) disk forensics

ctf-party icon ctf-party

:flags: A library to enhance and speed up script/exploit writing for CTF players

cti-stix-common-objects icon cti-stix-common-objects

OASIS Cyber Threat Intelligence (CTI) TC: A repository for commonly used STIX objects in order to avoid needless duplication. https://github.com/oasis-open/cti-stix-common-objects

curlconverter icon curlconverter

:curly_loop: :arrow_right: :heavy_minus_sign: Translate cURL command lines into parameters for use with httr or actual httr calls (R)

cymruservices icon cymruservices

:dragon: package that provides interfaces to various Team Cymru Services

dalfox icon dalfox

🌙🦊 DalFox is an powerful open source XSS scanning tool and parameter analyzer, utility

data icon data

This repository contains general data for Web technologies

deck.gl icon deck.gl

WebGL2 powered visualization framework

deep-learning-for-hackers icon deep-learning-for-hackers

Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)

deepfacelab icon deepfacelab

DeepFaceLab is the leading software for creating deepfakes.

detectionlab icon detectionlab

Automate the creation of a lab environment complete with security tooling and logging best practices

dfirmindmaps icon dfirmindmaps

A repository of DFIR-related Mind Maps geared towards the visual learners!

discord-console-hacks icon discord-console-hacks

A collection of JavaScript Codes I've made to enhance the User Experience of Discord and some other Discord related stuff

django-diy-blog icon django-diy-blog

Basic blog site written in Django (part of MDN Django module assessment).

django-locallibrary-tutorial icon django-locallibrary-tutorial

Local Library website written in Django; example for the MDN server-side development Django module: https://developer.mozilla.org/en-US/docs/Learn/Server-side/Django.

dns-spoofer icon dns-spoofer

DNS-domain name server spoofing, changing the requested domain by the victim to as adversary needs

dnsspoofanddetect icon dnsspoofanddetect

develop 1) an on-path DNS packet injector, and 2) a passive DNS poisoning attack detector. Part 1: The DNS packet injector you are going to develop, named 'dnsinject', will capture the traffic from a network interface in promiscuous mode, and attempt to inject forged responses to selected DNS A requests with the goal to poison the resolver's cache. Your program should conform to the following specification: dnsinject [-i interface] [-h hostnames] expression -i Listen on network device <interface> (e.g., eth0). If not specified, dnsinject should select a default interface to listen on. The same interface should be used for packet injection. -h Read a list of IP address and hostname pairs specifying the hostnames to be hijacked. If '-h' is not specified, dnsinject should forge replies for all observed requests with the local machine's IP address as an answer. <expression> is a BPF filter that specifies a subset of the traffic to be monitored. This option is useful for targeting a single or a set of particular victims. The <hostnames> file should contain one IP and hostname pair per line, separated by whitespace, in the following format: 10.6.6.6 foo.example.com 10.6.6.6 bar.example.com 192.168.66.6 www.cs.stonybrook.edu Pay attention to the time needed for generating the spoofed response! Your code should be fast enough so that the injected reply reaches the victim sooner than the server's actual response. The spoofed packet and content should also be valid according to the initial DNS request, and the forged response should be accepted and processed normally by the victim. Part 2: The DNS poisoning attack detector you are going to develop, named 'dnsdetect', will capture the traffic from a network interface in promiscuous mode and detect DNS poisoning attack attempts, such as those generated by dnsinject. Detection will be based on identifying duplicate responses towards the same destination that contain different answers for the same A request, i.e., the observation of the attacker's spoofed response followed by the server's actual response. You should make every effort to avoid false positives, e.g., due to legitimate consecutive responses with different IP addresses for the same hostname due to round robin DNS load balancing. Your program should conform to the following specification: dnsdetect [-i interface] [-r tracefile] expression -i Listen on network device <interface> (e.g., eth0). If not specified, the program should select a default interface to listen on. -r Read packets from <tracefile> (tcpdump format). Useful for detecting DNS poisoning attacks in existing network traces. <expression> is a BPF filter that specifies a subset of the traffic to be monitored. Once an attack is detected, dnsdetect should print to stdout a detailed alert containing a printout of both the spoofed and legitimate responses. You can format the output in any way you like. Output must contain the detected DNS transaction ID, attacked domain name, and the original and malicious IP addresses - for example: 20160406-15:08:49.205618 DNS poisoning attempt TXID 0x5cce Request www.example.com Answer1 [List of IP addresses] Answer2 [List of IP addresses]

dnsvalidator icon dnsvalidator

Maintains a list of IPv4 DNS servers by verifying them against baseline servers, and ensuring accurate responses.

dnsx icon dnsx

dnsx is a fast and multi-purpose DNS toolkit allow to run multiple DNS queries of your choice with a list of user-supplied resolvers.

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