Search Results for "attacks"

A self-hardening prompt injection detector. Rebuff is designed to protect AI applications from prompt injection (PI) attacks through a multi-layered defense. Rebuff is still a prototype and cannot provide 100% protection against prompt injection attacks. Add canary tokens to prompts to detect leakages, allowing the framework to store embeddings about the incoming prompt in the vector database and prevent future attacks.

Generating adversarial examples for NLP models. TextAttack is a Python framework for adversarial attacks, data augmentation, and model training in NLP.

Foolbox: Fast adversarial attacks to benchmark the robustness of machine learning models in PyTorch, TensorFlow, and JAX. Foolbox 3 is built on top of EagerPy and runs natively in PyTorch, TensorFlow, and JAX. Foolbox provides a large collection of state-of-the-art gradient-based and decision-based adversarial attacks. Catch bugs before running your code thanks to extensive type annotations in Foolbox.

The open-source Agentic LLM Vulnerability Scanner.

...Visually track events such as LLM calls, tools, and multi-agent interactions. Rewind and replay agent runs with point-in-time precision. Keep a full data trail of logs, errors, and prompt injection attacks from prototype to production. Native integrations with the top agent frameworks.

FLEXible (Federated Learning Experiments) is a Python framework offering tools to simulate FL with deep learning. It includes built-in datasets (MNIST, CIFAR10, Shakespeare), supports TensorFlow/PyTorch, and has extensions for adversarial attacks, anomaly detection, and decision trees.

Hack Instagram Password - AI-Powered Tool This application was made using the API of PASS REVELATOR, for more information about Instagram hacking account and security, please visit their website: https://www.passwordrevelator.net/en/passdecryptor Advanced machine learning tool for Instagram password security assessment. Features AI-driven brute force attacks, pattern recognition, and neural network prediction. KEY FEATURES: • AI-Powered Password Generation - Machine learning instead of wordlists • Neural Network Prediction - Simulated neural networks for smart guessing • Context-Aware Attacks - Analyzes usernames for intelligent variations • Multi-Phase AI Strategy - Progressive techniques from simple to complex • Advanced Anonymity - Tor integration and proxy rotation • Real-time Monitoring - Performance metrics and success rates TECHNICAL SPECIFICATIONS: • Python 3.8+ required • Advanced machine learning algorithms

...The library focuses on providing a reference implementation of attacks against machine learning models to help with benchmarking models against adversarial examples.

Pwnagotchi is an A2C-based “AI” powered by bettercap and running on a Raspberry Pi Zero W that learns from its surrounding WiFi environment in order to maximize the crackable WPA key material it captures (either through passive sniffing or by performing deauthentication and association attacks). This material is collected on disk as PCAP files containing any form of handshake supported by hashcat, including full and half WPA handshakes as well as PMKIDs. Instead of merely playing Super Mario or Atari games like most reinforcement learning based “AI” (yawn), Pwnagotchi tunes its own parameters over time to get better at pwning WiFi things in the real world environments you expose it to. ...

This application assists in generating pre-compositional material based on a computational interpretation of the 'Schillinger System of Musical Composition' (Schillinger 1946).

META is a decision making software which aims are to track computer attackers, computer attacks and to help investigators finding useful elements.