dylib injector for mach-o binaries

interprocess code injection for Mac OS X

Easily inject arbitrary read-only resources into executable formats (Mach-O, PE, ELF) and use it at runtime.

like mach_inject

OS X command line tool to inject Frameworks and dylibs on mach-o binaries (iOS & Mac Apps).

This repository includes the dataset and the Rapid Miner processes used in some machine learning experiments for quality prediction in plastic injection molding.

Inject a DyLib to an existing Mach-O file

Detect Sql Injection by Machine Learning

Inject libraries into 32 processes on macOS Mojave

A binary packer for ELF (32/64-bit) and Mach-O executables. Encrypts the .text section with RC4 and injects a self-decrypting shellcode payload.

inject dylib into Mach-o file on MacOS

No description available

A CLI tool for injecting dependent dylibs into the Mach-O file.

creating dataset

dylib injector for mach-o binaries

No description available

In this proposed project, machine learning technology is used to detect attacks occurring for web applications and determine the severity levels experienced by web applications of the type of SQL injection attack. Attack types are divided into five levels: High, medium, low, unknown vulnerability, and no vulnerability.

Inject dylib to mach-o excutable

No description available

Inject a shared object into the address space of a running process (OSX)

SQL Injection is one of the top 10 vulnerabilities in web-based systems. This attack essentially penetrates the logical section of the database. If the database has a logical flaw, the attackers send a new type of logical payload and get all of the user's credentials. Despite the fact that technology has advanced significantly in recent years, SQL injections can still be carried out by taking advantage of security flaws. On the Kaggle SQL Injection Dataset, I used multiple machine learning methods to identify and detect SQL Injection assaults, including Logistic Regression, AdaBoost (Adaptive Boosting), Random Forest, Naive Bayes, and XGBoost (Extreme Gradient Boosting) Classifier. According to this research, the best strategy for detecting SQL inject is Naive Bayes, which has an accuracy of 98.33, which is 2% better than previous work.

This project aims to develop a text classification model based on the BERT Language Model to detect SQL Injection on Apache Web Server. The research involves data collection and preprocessing, system design, implementation, and evaluation of deep learning model performance.

A Python-based application designed to proactively identify and mitigate false data injection attacks in real-time systems. Leveraging advanced machine learning algorithms, this system analyzes historical data patterns to detect anomalies indicative of malicious tampering.

ELF/Mach-O Executable patcher. Injects arbitrary code and encrypts the base code then decrypts it at runtime.

like mach_inject

No description available

Machine code can be inserted in real time over TCP

No description available

No description available

Machine Learning project to predict Injectivity Rate in water injection wells and analyze key factors affecting well performance in the oil & gas industry