
AGAS
LLM-driven agentic group shilling attack framework that manipulates black-box collaborative-filtering recommender rankings using adaptive multi-role…

LLM-driven agentic group shilling attack framework that manipulates black-box collaborative-filtering recommender rankings using adaptive multi-role…

Robust audio watermarking framework embedding binary messages into magnitude spectrograms, with differentiable attack simulation, Q-Former pooling,…

Research code for poisoning attacks on the PGM-index, demonstrating how to craft adversarial data to degrade learned index performance.

Algorithms for outlier, adversarial and drift detection

List of tools & datasets for anomaly detection on time-series data.

Automatic extraction of relevant features from time series:

A machine learning tool that ranks strings based on their relevance for malware analysis.

Streaming machine learning library for incremental learning on data streams, providing online estimators, drift and anomaly detection, pipelines,…

A python library for user-friendly forecasting and anomaly detection on time series.

Detects LLM context-leakage attacks by training lightweight behavior probes on log-probabilities, with vLLM offline/server detection pipelines.

A curated portfolio showcasing my SOC investigations, threat hunting projects, DFIR labs, detection engineering, technical blogs, and cybersecurity…

Android Antivirus which doesn't require root, adb, ca install and cloud with many features and ways to detect more zero-day malware

The community's most comprehensive, continuously-updated index of research on Large Language Models for software vulnerability detection — papers…

Collection of CVE(work) on tenserflow binary pwning it

Human-evaluated benchmark for assessing LLM performance on real-world vulnerability identification, explanation, and remediation across 15+ languages…

Research code and dataset (WSD) for evaluating audio watermarking impact on anti-spoofing, using wav2vec2 XLS-R and knowledge-preserving learning.

Implements machine and deep learning methods for indoor UWB jammer localization, including hyperparameter optimization, classification, and…

Official code for the ISSTA 2026 paper: Is "Knowing It’s Malicious" Enough? Evaluating LLMs for Fine-Grained Malware Behavior Auditing