Pinned Repositories
0xsobky.github.io
Hacklog!
800-53-report-generator
Take notes organized by NIST 800-53 and export as CSV
AlgorithmVisualizer
Algorithm Visualizer
captchaTing
Google reCaptcha token harvester
chrome-vpn
Orchestrate half a dozen or so headless Chrome instances connected to random VPNs for global web surfing and content extraction.
Forex-Price-Predictor
Uses LSTM in Keras to predict foreign exchange prices, interfaces with oanda API for automated trading
LampCMS
Open source Question and Answer program similar to StackOverflow and Quora in PHP + MongoDB. Follow @snytkine on Twitter
lstm_normalizations
react-sonar
ReactJS component that detects when an wrapped element resizes
SGX-OrderBook-Tick-Data-Trading-Strategy
Modeling High-Frequency Limit Order Book Dynamics Using Machine Learning.
easyrider's Repositories
easyrider/chrome-vpn
Orchestrate half a dozen or so headless Chrome instances connected to random VPNs for global web surfing and content extraction.
easyrider/lstm_normalizations
easyrider/800-53-report-generator
Take notes organized by NIST 800-53 and export as CSV
easyrider/Assemblies-of-putative-SARS-CoV2-spike-encoding-mRNA-sequences-for-vaccines-BNT-162b2-and-mRNA-1273
RNA vaccines have become a key tool in moving forward through the challenges raised both in the current pandemic and in numerous other public health and medical challenges. With the rollout of vaccines for COVID-19, these synthetic mRNAs have become broadly distributed RNA species in numerous human populations. Despite their ubiquity, sequences are not always available for such RNAs. Standard methods facilitate such sequencing. In this note, we provide experimental sequence information for the RNA components of the initial Moderna (https://pubmed.ncbi.nlm.nih.gov/32756549/) and Pfizer/BioNTech (https://pubmed.ncbi.nlm.nih.gov/33301246/) COVID-19 vaccines, allowing a working assembly of the former and a confirmation of previously reported sequence information for the latter RNA. Sharing of sequence information for broadly used therapeutics has the benefit of allowing any researchers or clinicians using sequencing approaches to rapidly identify such sequences as therapeutic-derived rather than host or infectious in origin. For this work, RNAs were obtained as discards from the small portions of vaccine doses that remained in vials after immunization; such portions would have been required to be otherwise discarded and were analyzed under FDA authorization for research use. To obtain the small amounts of RNA needed for characterization, vaccine remnants were phenol-chloroform extracted using TRIzol Reagent (Invitrogen), with intactness assessed by Agilent 2100 Bioanalyzer before and after extraction. Although our analysis mainly focused on RNAs obtained as soon as possible following discard, we also analyzed samples which had been refrigerated (~4 ℃) for up to 42 days with and without the addition of EDTA. Interestingly a substantial fraction of the RNA remained intact in these preparations. We note that the formulation of the vaccines includes numerous key chemical components which are quite possibly unstable under these conditions-- so these data certainly do not suggest that the vaccine as a biological agent is stable. But it is of interest that chemical stability of RNA itself is not sufficient to preclude eventual development of vaccines with a much less involved cold-chain storage and transportation. For further analysis, the initial RNAs were fragmented by heating to 94℃, primed with a random hexamer-tailed adaptor, amplified through a template-switch protocol (Takara SMARTerer Stranded RNA-seq kit), and sequenced using a MiSeq instrument (Illumina) with paired end 78-per end sequencing. As a reference material in specific assays, we included RNA of known concentration and sequence (from bacteriophage MS2). From these data, we obtained partial information on strandedness and a set of segments that could be used for assembly. This was particularly useful for the Moderna vaccine, for which the original vaccine RNA sequence was not available at the time our study was carried out. Contigs encoding full-length spikes were assembled from the Moderna and Pfizer datasets. The Pfizer/BioNTech data [Figure 1] verified the reported sequence for that vaccine (https://berthub.eu/articles/posts/reverse-engineering-source-code-of-the-biontech-pfizer-vaccine/), while the Moderna sequence [Figure 2] could not be checked against a published reference. RNA preparations lacking dsRNA are desirable in generating vaccine formulations as these will minimize an otherwise dramatic biological (and nonspecific) response that vertebrates have to double stranded character in RNA (https://www.nature.com/articles/nrd.2017.243). In the sequence data that we analyzed, we found that the vast majority of reads were from the expected sense strand. In addition, the minority of antisense reads appeared different from sense reads in lacking the characteristic extensions expected from the template switching protocol. Examining only the reads with an evident template switch (as an indicator for strand-of-origin), we observed that both vaccines overwhelmingly yielded sense reads (>99.99%). Independent sequencing assays and other experimental measurements are ongoing and will be needed to determine whether this template-switched sense read fraction in the SmarterSeq protocol indeed represents the actual dsRNA content in the original material. This work provides an initial assessment of two RNAs that are now a part of the human ecosystem and that are likely to appear in numerous other high throughput RNA-seq studies in which a fraction of the individuals may have previously been vaccinated. ProtoAcknowledgements: Thanks to our colleagues for help and suggestions (Nimit Jain, Emily Greenwald, Lamia Wahba, William Wang, Amisha Kumar, Sameer Sundrani, David Lipman, Bijoyita Roy). Figure 1: Spike-encoding contig assembled from BioNTech/Pfizer BNT-162b2 vaccine. Although the full coding region is included, the nature of the methodology used for sequencing and assembly is such that the assembled contig could lack some sequence from the ends of the RNA. Within the assembled sequence, this hypothetical sequence shows a perfect match to the corresponding sequence from documents available online derived from manufacturer communications with the World Health Organization [as reported by https://berthub.eu/articles/posts/reverse-engineering-source-code-of-the-biontech-pfizer-vaccine/]. The 5’ end for the assembly matches the start site noted in these documents, while the read-based assembly lacks an interrupted polyA tail (A30(GCATATGACT)A70) that is expected to be present in the mRNA.
easyrider/axiom
The dynamic infrastructure framework for everybody! Distribute the workload of many different scanning tools with ease, including nmap, ffuf, masscan, nuclei, meg and many more!
easyrider/Azure-Security-Center
Welcome to the Azure Security Center community repository
easyrider/benford_py
Python implementation of Benford's Law tests.
easyrider/Browser-Exploits
Some Generic Browser Exploits (For Educational Purposes Only)
easyrider/ccc
Companion Code for C++ Crash Course
easyrider/CISSP-Oreilly-SSE
System Security Engineering
easyrider/config-repo
Configuration files for the server sample
easyrider/crimson
Reconstruction and automation of the reconnaissance phase.
easyrider/DeTTECT
Detect Tactics, Techniques & Combat Threats
easyrider/DFIR_Resources_REvil_Kaseya
Resources for DFIR Professionals Responding to the REvil Ransomware Kaseya Supply Chain Attack
easyrider/eea.docker.haproxy
HAProxy Docker image with docker links and reload support
easyrider/gowitness
🔍 gowitness - a golang, web screenshot utility using Chrome Headless
easyrider/h4cker
This repository is primarily maintained by Omar Santos and includes thousands of resources related to ethical hacking / penetration testing, digital forensics and incident response (DFIR), vulnerability research, exploit development, reverse engineering, and more.
easyrider/LeetCode
My C++ Code for LeetCode OJ
easyrider/LiveLessons
This repository contains all the source code examples from my LiveLessons course on "Concurrent Programming with Android"
easyrider/nuclei-templates
Community curated list of templates for the nuclei engine to find security vulnerabilities.
easyrider/puppeteer-recaptcha-solver
Recaptcha solver for puppeteer
easyrider/safari-generics
easyrider/safari-threading
easyrider/slipstream
NAT Slipstreaming allows an attacker to remotely access any TCP/UDP services bound to a victim machine, bypassing the victim’s NAT/firewall, just by the victim visiting a website
easyrider/spring-cloud-workshops
easyrider/stock_cnn_blog_pub
This project is a loose implementation of paper "Algorithmic Financial Trading with Deep Convolutional Neural Networks: Time Series to Image Conversion Approach"
easyrider/Tiny-XSS-Payloads
A collection of tiny XSS Payloads that can be used in different contexts.
easyrider/trojan-source
Trojan Source: Invisible Vulnerabilities
easyrider/TypeScript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
easyrider/weird_proxies
Reverse proxies cheatsheet