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Automatic extraction of relevant features from time series:

Automatic extraction of relevant features from time series:

The AI that really does things. Any OS. Any Platform. The lobster way. 🦞

A curated list of useful resources that cover Offensive AI.

Self-hostable AI SOC that fuses security alerts, auto-triages via agentic AI, runs MITRE ATT&CK investigations, and logs every agent decision in a…

A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX

Automated behavioral evaluation framework for LLMs that generates diverse test scenarios to probe for sycophancy, bias, and other safety-relevant…

Open-source email filtering framework that detects spam and phishing using content analysis, header checks, Bayesian scoring, and DNS blocklists.

Automated security analysis pipeline that runs CodeQL queries on GitHub repositories and uses LLMs to classify and filter true vulnerabilities from…

Research implementation of an LLM jailbreak agent that bypasses commercial model guardrails using harmless prompt weaving and adaptive tree search.

I replicated Ng's RYS method and found that duplicating 3 specific layers in Qwen2.5-32B boosts reasoning by 17% and duplicating layers 12-14 in…

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

Evolutionary LLM jailbreak and guardrail framework that grows a reusable strategy pool via genetic mutation, Markov selection, and online adversarial…

Automated framework for frontier AI safety evaluation that synthesizes executable, pressure-rich test environments to uncover latent risks in…

Serverless AWS security automation framework that ingests threat intelligence, applies ML-based anomaly detection (RCF, IP Insights), and enriches…

ML-assisted forensic analysis tool that automates memory, disk, and live system triage on Windows using Volatility 3, autorunsc, and sigcheck to…

Plugin for Binary Ninja that integrates local Ollama models to rename functions and variables in decompiled HLIL code, preserving privacy by keeping…

Small language model that names and describes functions in stripped x86-64 binaries, with an open dataset, baselines, and LoRA fine-tuning…

Fine-tuning framework that applies first-order optimal safety calibration and periodic recalibration to LLMs, preserving safety-compatible updates…