thefatrat is an exploiting tool which compiles a malware with famous payload, and then the compiled maware can be executed on Linux , Windows , Mac and Android. TheFatRat Provides An Easy way to create Backdoors and Payload which can bypass most anti-virus. the author has some tools to share.
pupy is an opensource, cross-platform (Windows, Linux, OSX, Android) C2 and post-exploitation framework written in python and C
thezoo A repository of LIVE malwares for your own joy and pleasure. theZoo is a project created to make the possibility of malware analysis open and available to the public.
cyber-challenge Some toy examples, to demonstrate ideas that could be used in DARPA’s Cyber Grand Challenge including modifying java bytecode and filter out html requests on the fly
EVIL (Exploiting software VIa natural Language) is an approach to automatically generate software exploits in assembly/Python language from descriptions in natural language. The approach leverages Neural Machine Translation (NMT) techniques and a dataset that we developed for this work.
Invicti is a web application security scanner hacking tool to find SQL Injection, XSS, and vulnerabilities in web applications or services automatically.
Fortify WebInspect
It is used to identify security vulnerabilities by allowing it to test the dynamic behavior of running web applications.
Cain & Abel
It is used to recover the MS Access passwords
Nmap (Network Mapper)
Used in port scanning, one of the phases in ethical hacking, is the finest hacking software ever.
Nessus
Nessus is the world’s most well-known vulnerability scanner, which was designed by tenable network security. It is free and is chiefly recommended for non-enterprise usage.
Nikto
Checks web servers and identifies over 6400 CGIs or files that are potentially dangerous
Kismet
Kismet is basically a sniffer and wireless-network detector that works with other wireless cards and supports raw-monitoring mode.
NetStumbler
Identifying AP (Access Point) network configuration
Acunetix
Integration of scanner results into other platforms and tools
Netsparker
Uniquely verifies identified vulnerabilities, showing that they are genuine, not false positives
Intruder
Integrates with Slack, Jira, and major cloud providers
Nmap
Contains a data transfer, redirection, and debugging tool
Metasploit
Ideal for finding security vulnerabilities
Aircrack-Ng
It can crack WEP keys and WPA2-PSK, and check Wi-Fi cards
Wireshark
Allows coloring rules to packet lists to facilitate analysis
OpenVAS
OpenVAS has the capabilities of various high and low-level Internet and industrial protocols, backed up by a robust internal programming language.
SQLMap
Supports executing arbitrary commands
Ettercap
Live connections sniffer
Maltego
Performs real-time information gathering and data mining
Burp Suite
Uses out-of-band techniques
John the Ripper
Tests different encrypted passwords
Angry IP Scanner
This is a free tool for scanning IP addresses and ports
SolarWinds Security Event Manage
Recognized as one of the best SIEM tools, helping you easily manage memory stick storage
Traceroute NG
Detects paths changes and alerts you about them
LiveAction
Its packet intelligence provides deep analyses
QualysGuard
Responds to real-time threats
WebInspect
Tests dynamic behavior of web applications for the purpose of spotting security vulnerabilities
Hashcat
Supports distributed cracking networks
L0phtCrack
Fixes weak passwords issues by forcing a password reset or locking out accounts
Rainbow Crack
IKECrack
IKECrack is an authentication cracking tool with the bonus of being open source.
Sboxr
Checks for over two dozen types of web vulnerabilities
Medusa
One of the best tools for thread-based parallel testing and brute-force testing
Cain and Abel
uncovers password fields, sniffs networks, recovers MS Access passwords, and cracks encrypted passwords using brute-force, dictionary, and cryptanalysis attacks.
Zenmap
Administrators can track new hosts or services that appear on their networks and track existing downed services
semrush contains multiple services, and it is paid. many online tools are paid as well. to find open source alternatives (usually it can’t be achieved with a single tool alone, from scraping to analyzing), let’s figure out what does this tool do, also few tech terms.
semrush does SEO, SEM, and SMM.
put social media buttons on webpages to let users share the content, usually by passing parameters in url, which is part of SMM.
tools
keyword mining (by search engine or more): 2 words -> 3 words -> 4 words -> 5 words (recursive)
keyword-suggest-tool is a simple tool that provides you keyword suggestion from multiple search engines like google, bing, yahoo, ebay, amazon, ebay, deployed on sutlej.net/seo-tools
ULTRA Unbiased Learning To Rank Algorithms, sorting things out, find what users like the most
keyword tool The Keyword Manager is a tool to support SEAs and SEOs finding new keywords from a website.
keyword_tool Web app to extract keywords from pasted text. Built with NLTK and Streamlit.
keywordshitter2 A website to find long-tail keywords using search suggestions, still works on here
PURR (PUppeteer RunneR) is a devops-friendly tool for browser testing and monitoring by semrush
awesome-local-seo A curated list of amazingly awesome local seo resources.
seo-audits-toolkit SEO & Security Audit for Websites. Lighthouse & Security Headers crawler, Sitemap/Keywords/Images Extractor, Summarizer, etc …
seo_keyword_research_tools The Keyword Volume Tool uses the Google Adwords API Targeting Ideas Service to return the search volume and competition of a massive list of keywords. The Keyword Expansion Tool uses the Google Adwords API Targeting Ideas Service to expand an input keyword into up to 500 related keywords with search volume.
KoboldAI considered OPT and GPT-Neo as generic LMs. special models like NSFW shits may serve some purposes better.
many alternatives, but many are specialized in marketing and content generation, some are chatgpt replica, like chatsonic (with google knowledge) and youchat (from you.com (awesome!))
open assistant now has a data collection website, in which you can only perform tasks given and earn points (working for free? nah?)
it is adviced to run this chatgpt program with libraries instead of manually, to prevent issues.
my account has been banned from trying chatgpt. though it is not going to be free forever, you need to moderate your input (multi-language support, not only english but chinese) using some api to prevent similar incidents. also some topics outside of blacklist are banned intentionally so you need to check if the model is really producing the answer. if not you should avoid or change the way of asking it.
from my point of view, this is a service you cannot replicate at home, either requires smaller models with different architecture, or requires crowd-sourced computational power.
saying chatgpt is powered by ray, increasing parallelism.
since many different models are derived from the original pretrained language model, opendelta can save disk space by freezing main parameters, only tuning few of them.
this gpt seems really good. currently only api access.
but it is provided by openai which is no longer so “open” in the sense of “open-source”.
according to my point of view, chatgpt is just specialized on chat, or socialized in other words.
the elo rating system is the key to facebook social network, many zero-sum games. basically it is some revolution rating system. to do such rating system effectively one shall use along with classifiers and embeddings.
according to the training process of instructgpt and webgpt, we know that gpt has learned more by interacting with people (multiple QA), doing self-examination (learning a reward model) and performing actions (searching and quoting on web).
gpt3 is capable of imitation (cause it is unsupervised.)
but! if you want to get things done (when you really need it!), you better want some aligned AI.
two similar models by openai: webgpt and instructgpt
about instructgpt
it is first fine-tuned on supervised datasets, then train some reward model, then use the reward model to handle prompts and do reinforcement learning with PPO.
details on webgpt environment
guess: create states by performing actions, then generate templates to allow model filling blanks.
Our text-based web-browsing environment is written mostly in Python with some JavaScript. For a high-level overview, see Section 2. Further details are as follows: • When a search is performed, we send the query to the Microsoft Bing Web Search API, and convert this to a simplified web page of results. • When a link to a new page is clicked, we call a Node.js script that fetches the HTML of the web page and simplifies it using Mozilla’s Readability.js. • We remove any search results or links to reddit.com or quora.com, to prevent the model copying answers from those sites. • We take the simplified HTML and convert links to the special format 【<link ID>†<link text>†<destination domain>】, or 【<link ID>†<link text>】 if the destination and source domains are the same. Here, the link ID is the index of the link on the page, which is also used for the link-clicking command. We use special characters such as 【 and 】 because they are rare and encoded in the same few ways by the tokenizer, and if they appear in the page text then we replace them by similar alternatives. • We convert superscripts and subscripts to text using ^ and _, and convert images to the special format [Image: <alt text>], or [Image] if there is no alt text. • We convert the remaining HTML to text using html2text. • For text-based content types other than HTML, we use the raw text. For PDFs, we convert them to text using pdfminer.six. For all other content types, and for errors and timeouts, we use an error message. • We censor any pages that contain a 10-gram overlap with the question (or reference answer, if provided) to prevent the model from cheating, and use an error message instead. • We convert the title of the page to text using the format <page title> (<page domain>). For search results pages, we use Search results for: <query>. • When a find in page or quote action is performed, we compare the text from the command against the page text with any links stripped (i.e., including only the text from each link). We also ignore case. For quoting, we also ignore whitespace, and allow the abbreviated format <start text>━<end text> to save tokens. • During browsing, the state of the browser is converted to text as shown in Figure 1(b). For the answering phase (the last step of the episode), we convert the question to text using the format <question>■, and follow this by each of the collected quotes in the format [<quote number>] <quote page title> (<quote page domain>) <double new line><quote extract>■.
awesome transformer language models a huge collection on transformer based LMs, huge models by megacorps, with some introduction and analogy on chatgpt
bilibili sends me lots of videos (and articles) on hacking and ai (including chatgpt) via its android app. recommend you to scrape this source and collect transcription and screenshots for searching and content generation.