dejavu
Mythic
dejavu | Mythic | |
---|---|---|
15 | 5 | |
6,316 | 2,890 | |
- | - | |
0.0 | 9.6 | |
10 days ago | 9 days ago | |
Python | JavaScript | |
MIT License | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
dejavu
- Audio Fingerprinting and Recognition in Python
-
Contacting Collectors or Creating API to help with searching
This doesn't seem hard, you can use something like this to dwoanload the songs: https://stackoverflow.com/a/27481870/6151784 and something like this to calculate how much they match: https://github.com/worldveil/dejavu The question is would you create a (dedicated) server to do your work? Or your own pc? You could also create a very simple page where someone would paste you a YouTube profile URL and you would check all songs of this URL. Also to have a db and save information about the matching and which youtube profiles have alsready been checked. Something like that could work.
-
Tiny bit of experience but need to compile a Github program. What is the best video / resource to learn to do this quickly?
If you read the installation.md file it clearly states that it has only been tested on UNIX systems, so you might be on your own trying to get it to wor in windows.
- Help needed with school project
-
Identification of all usages of OSTs in Made in Abyss (S1)
Using neural networks seems complicated, did you tried audio fingerprinting? I have been using this audio fingerprinting library to power this anime song synchronization script. You can check Panako and dejavu too.
- Dejavu – Audio fingerprinting and recognition algorithm
-
fingerprinting sections of audio from file
I want to say these few seconds match these few seconds from a different audio track. Using dejavu raw has overhead I do not need/want and hence I've been fiddling around with the fingerprint script. When modifying the global variables I can get better hits or worse hits, I will admit that even after reading there recommended article and many other sources, I can't find some good explanations about the mathematics behind the filtering after the specgram has been applied. As far as a I am aware we first apply filters to find/make fine points across the spectrogram after that we only check the distance between points along the time axis not the frequency or a hypotenuse (weird).
- Some information and advice about DDoS, from someone who was there during #opPayback
- List of resources
-
Uploading an audio dataset into a database for comparison
I used a repo called https://github.com/worldveil/dejavu to compare audio hashed fingerprints and distinguish the difference between them.
Mythic
-
Install Mythic C2 server - Intro to C2 Infra for Red Teams
Learn the basic installation of Mythic Command and Control (C2) step by step. We'll configure Mythic C2 (open-source C2 framework https://github.com/its-a-feature/Mythic)
-
Mythic C2 Detections
title: Detect Mythic Agent Traffic Over Port 8443 status: experimental author: Rotten_Sec description: Detects traffic over port 8443 that matches the WebSocket handshake used by Mythic agents to communicate with the C2 server. references: - https://github.com/its-a-feature/Mythic tags: - attack.t1071.001 - attack.t1071.004 - attack.t1071.005 - attack.t1071.006 logsource: category: network keywords: [tcp, port, 8443] condition: tcp.port == 8443 and ( "GET /websocket HTTP/1.1\r\n" in to_string($data) or "HTTP/1.1 101 Switching Protocols\r\nUpgrade: websocket\r\nConnection: Upgrade\r\n" in to_string($data) )
-
Building a Red Team - Which C2 to pick?
In my opinion, Mythic is a great choice because it is free, extremely well developed, and provides a base capability that allows you to either extend it or to leverage the work of others. With Mythic, there are currently 16 public MythicAgents and 6 different MythicC2Profiles. You can use the public agents/C2profile and then switch to internal private versions if your team decides to go that way without the need to re-learn an entire framework. It has a web front end that provides a lot of (extendable) functionality I don't see in other tools. Additionally the lead developer is always extremely eager to provide help, add features, and fix bugs. Full disclosure: I'm the primary developer of Merlin.
- Some information and advice about DDoS, from someone who was there during #opPayback
- List of resources
What are some alternatives?
django-elastic-transcoder - Django + AWS Elastic Transcoder
sliver - Adversary Emulation Framework
m3u8 - Python m3u8 Parser for HTTP Live Streaming (HLS) Transmissions
CamPhish - Grab cam shots from target's phone front camera or PC webcam just sending a link.
audiolazy - Expressive Digital Signal Processing (DSP) package for Python
ScareCrow - ScareCrow - Payload creation framework designed around EDR bypass.
speech-to-text-websockets-python
maskphish - Introducing "URL Making Technology" to the world for the very FIRST TIME. Give a Mask to Phishing URL like a PRO.. A MUST have tool for Phishing.
pyechonest - Python client for the Echo Nest API
awesome-bbht - A bash script that will automatically install a list of bug hunting tools that I find interesting for recon, exploitation, etc. (minus burp) For Ubuntu/Debain.
pyAudioAnalysis - Python Audio Analysis Library: Feature Extraction, Classification, Segmentation and Applications
urh - Universal Radio Hacker: Investigate Wireless Protocols Like A Boss