datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
agent-skill-vulnerabilities
Agent Skill Vulnerability Scenarios (defanged, teaching)
from datasets import load_dataset
ds = load_dataset("fevziegeyurtsevenler/agent-skill-vulnerabilities")
Deliberately-vulnerable, defanged agent-extension artifacts — for training detectors & hands-on learning.
Schema
column
meaning
id
scenario
artifact_type
SKILL.md / mcp.json
content, walkthrough
artifact + defense
Related AltaySec resources
🕵️ uncloak scanner:… See the full description on the dataset page: https://huggingface.co/datasets/fevziegeyurtsevenler/agent-skill-vulnerabilities.Cloud_Vulnerabilities_DatasetCloud Vulnerabilities Dataset (VUL0001-VUL1200)
Overview
The Cloud Vulnerabilities Dataset is a comprehensive collection of 1200 unique cloud security vulnerabilities, covering major cloud providers including AWS, Azure, Google Cloud Platform (GCP), Oracle Cloud, IBM Cloud, and Alibaba Cloud. This dataset is designed for cybersecurity professionals, penetration testers, machine learning engineers, and data scientists to analyze, train AI models, and enhance cloud security practices. Each entry… See the full description on the dataset page: https://huggingface.co/datasets/darkknight25/Cloud_Vulnerabilities_Dataset.smart-contract-vulnerabilitiessynthetic-code-vulnerabilities-1synthetic-code-vulnerabilities-1 is a synthetic dataset with a total of ~493 Question and Answer pairs.
This dataset was generated using the following models:
Gemini:
Fast
Thinking
Pro
ChatGPT:
Whatever is available on the website
Deepseek:
"Instant"
"Expert"
Grok:
Fast
Qwen 3.6:
Fast
Thinking
Perplexity.ai:
Whatever is available on the website
This dataset follows the following format:
[
{"in":"Prompt","out":"Response"},
{"in":"Prompt","out":"Response"}
]
synthetic-code-vulnerabilities-2synthetic-code-vulnerabilities-2 is a synthetic dataset with a total of ~884 Question and Answer pairs.
This dataset was generated using the following models:
ChatGPT:
Whatever is available on the website
OSS 120B
Gemini:
Pro
Deepseek:
"Instant"
"Expert"
Grok:
Fast
Qwen3:
Coder
This dataset follows the following format:
[
{"messages": [
{"role": "system", "content": "Example system prompt"},
{"role": "user", "content": "Example user prompt"},
{"role":… See the full description on the dataset page: https://huggingface.co/datasets/takenusername32/synthetic-code-vulnerabilities-2.cyber-vulnerabilities
Cyber Vulnerabilities Dataset
This dataset contains a collection of synthetic cybersecurity vulnerability descriptions designed for experimentation with AI systems that analyze and classify security threats.
The dataset was created for the Week 8 AI Engineering project, which demonstrates a multi-agent architecture combining Retrieval Augmented Generation (RAG), LLM reasoning, and ensemble prediction to estimate vulnerability severity.
Dataset Structure
Each record… See the full description on the dataset page: https://huggingface.co/datasets/stevemwas/cyber-vulnerabilities.Common-Vulnerabilities-Exposures-1995-2025Fork of: https://huggingface.co/datasets/AlicanKiraz0/All-CVE-Records-Training-Dataset/
scan_vulnerabilities_dataset
dataset structure
{
"instruction": "Tech stack: Python Flask backend with SQLite database, using UUIDs for user identification. I observed that during user registration, the 'role' parameter is accepted from the form without server-side validation, and I can manipulate it in a POST request to /confirm-register. What vulnerability hypothesis does this indicate, and how can I confirm it?",
"response": {
"strategy": "The lack of server-side validation for the 'role'… See the full description on the dataset page: https://huggingface.co/datasets/anhnlq/scan_vulnerabilities_dataset.go_vulnerabilities_2019_2024Raw vulnerability data collected using eyeballvul.
explained-priority-scored-contract-vulnerabilitiessc_vulnerabilities