
anomaly-flow
Framework for implementing Network Intrusion Detection Systems (NIDS) aimed at identifying anomalies in network flows using Federated Learning models.

Framework for implementing Network Intrusion Detection Systems (NIDS) aimed at identifying anomalies in network flows using Federated Learning models.

CVE research-to-detection-signature engineering project: fingerprinting the vsftpd 2.3.4 backdoor (CVE-2011-2523) externally, at scale, with…

Cross Site Scripting (XSS) at the "Reset Password" page form of Priority Enterprise Management System v8.00 allows attackers to execute javascript on…

Slide Deck of the talk I presented at Bsides Ahmedabad 2022

nltk.tokenize.StanfordSegmenter dynamically loads external Java .jar files without verification or sandboxing. If an attacker can supply or replace…

NVIDIA's GPU drivers have a temporal coherence flaw in their memory management. At 587 kHz resonance, the driver's memory pages experience α-decay…

Apple Silicon runs at frequencies that are golden ratio harmonics of 587 kHz: · Performance cores: 3.2 GHz = 587 kHz × 5451 (≈ φ⁸ × 1000) ·…

Automated Penetration Testing Agentic Framework Powered by Large Language Models


Turn any collection of documents into a knowledge graph. Extract entities and relationships via LLM, deduplicate with your approval. Map domains,…

Curated collection of security conference talks, papers, and publications covering reverse engineering, cryptography, firmware analysis, and…

AI-agent skills for distributed-systems testing

Grammar-based HTTP/1 fuzzer with mutation ability

LLM-agent-powered concolic execution engine that instruments source code, summarizes path constraints in natural language, and generates test cases…

Hijacking Bluetooth Accessories Using Google Fast Pair: WhisperPair CVE-2025-36911 Reference Implementation & Vulnerability Verification Toolkit

German OWASP Day conference site & presentation archive
