Search Results for "attacks"

Beelzebub is an open-source cybersecurity framework designed to create intelligent honeypot environments for detecting and studying cyber attacks. Honeypots are systems intentionally exposed to attackers in order to capture malicious behavior, and Beelzebub enhances this concept by incorporating artificial intelligence and virtualization techniques. The platform allows organizations and researchers to deploy decoy services that mimic real infrastructure while recording attacker interactions. ...

LLM Guard is an open-source security toolkit designed to protect large language model applications from various security risks and adversarial attacks. The library acts as a protective layer between users and language models by analyzing inputs and outputs before they reach or leave the model. It includes scanning mechanisms that detect malicious prompts, prompt injection attempts, toxic content, and other harmful inputs that could compromise AI systems. The toolkit also helps prevent sensitive information leaks by identifying secrets such as API keys or credentials before they are processed by the model. ...

In-The-Wild Jailbreak Prompts on LLMs is an open-source research repository that provides datasets and analytical tools for studying jailbreak prompts used to bypass safety restrictions in large language models. The project is part of a research effort to understand how users attempt to circumvent alignment and safety mechanisms built into modern AI systems. The repository includes a large collection of prompts gathered from real-world platforms such as Reddit, Discord, prompt-sharing...

...The repository emphasizes broad coverage, including test rules for prompt stealing, jailbreaks, harmful content generation, hate-related outputs, social bias, and distraction attacks. It also supports multiple providers such as OpenAI, Anthropic, Google, xAI, and open-source models through Ollama, making it flexible for both commercial and local deployments.