pdf-malware

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malice-plugins / pdf

Malice PDF Plugin

plugin docker pdf malware malware-analyzer malware-analysis malice pdf-parsing pdfid peepdf malice-plugin pdf-malware pdf-analyzer

Updated Jan 7, 2019
Python

La-Casette / malicious_pdf_detection

Star 8

This project compares the performance of K-Nearest Neighbors, Support Vector Machines, and Decision Trees models for detecting malicious PDF files, with an emphasis on optimizing model performance and analyzing evasion techniques. It provides a comprehensive overview of machine learning for malicious PDF detection and potential vulnerabilities.

pdf machine-learning random-forest svm decision-trees knn malicious adversarial-learning pdf-malware evasion-attack

Updated Jan 22, 2023
Jupyter Notebook

fouadtrad / Leveraging-Adversarial-Samples-for-Enhanced-Classification-of-Malicious-and-Evasive-PDF-Files

Star 6

Repository for the paper "Leveraging Adversarial Samples for Enhanced Classification of Malicious and Evasive PDF Files" published in Applied Sciences, MDPI

machine-learning malware evasion pdf-malware evasive-samples

Updated Jul 31, 2025
Jupyter Notebook

ridpath / pdfscapel

Star 1

PDFScalpel is a forensic PDF analysis and CTF toolkit for security researchers, digital forensics analysts, and penetration testers, providing deep insight into PDF structure, encryption, malware, steganography, metadata, revisions, and document authenticity.

pdf adobe pentesting watermark ctf-tools pdf-ocr-extraction pdf-malware pdf-password watermark-remover pdf-processing redteam-tools watermark-removal pdf-ocr pdf-password-remover watermark-tool pdf-forensic-tool

Updated Feb 3, 2026
Python

novynngsh / PDF-Malware-Anomaly-Detection-with-Decision-Tree-Algorithm

Star 1

machine-learning decision-tree-classifier smote anomaly-detection pdf-malware stratified-cross-validation

Updated Nov 4, 2023
Jupyter Notebook

priyank5548 / PDF-Malware-Analysis-Toolkit

Star 0

A Python-based static analysis tool that inspects PDF internal structure to detect malicious JavaScript, obfuscated streams, embedded payloads, and indicators of compromise using object & stream level parsing inspired by pdfid, pdf-parser, peepdf, and qpdf methodologies.

static-analysis cybersecurity threat-hunting malware-analysis digital-forensics python-security pdf-parser pdf-malware pdf-security ioc-detection