Web Vulnerability Advisory Comprehensive QA Dataset

#security question answering #vulnerability applicability analysis #evidence-based reasoning #web vulnerability assessment #cybersecurity advisory analysis #vulnerability mitigation guidance

5000
0.3GB
JSON
CATL
MOBIUSI INC

Updated:2026-10-19

AI Analysis & Value Prop

This dataset is built around Web application vulnerability advisories and includes original advisory text, affected products and versions, technical background, and protection recommendations, paired with questions that require synthesis of the materials and expert reference answers. Fields for impact scope, applicability conditions, protection points, and evidence basis help models learn to integrate vulnerability knowledge and produce accurate, source-grounded security answers. It is suitable for supervised fine-tuning in Web security, QA evaluation, and the development of security knowledge assistants.

Dataset Insights

Sample Examples

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Technical Specifications

Field	Type	Description
file_name	string	File name
question	string	A question that requires synthesizing the advisory materials, such as assessing vulnerability impact, applicability, or protection guidance.
impact_scope	string	A source-grounded summary of affected products, versions, components, or vulnerability consequences.
expert_answer	string	The original expert-provided reference answer to the question.
evidence_basis	string	An account of the advisory details that support the answer and its conclusions.
protection_points	string	Key mitigation, remediation, or defensive guidance supported by the source materials.
advisory_materials	string	Original vulnerability advisory text, affected-version information, technical background, and protection recommendations.
applicability_conditions	string	Conditions under which the vulnerability applies, such as configuration, deployment, or feature prerequisites.

Compliance Statement

Authorization Type	Proprietary - Commercial AI Training License (No Redistribution)
Commercial Use	Requires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and Anonymization	No PII, no real company names, simulated scenarios follow industry standards
Compliance System	Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Frequently Asked Questions

What does the dataset contain?: It includes original vulnerability advisories, affected-version information, technical background, and protection recommendations, along with related questions and expert reference answers. Structured fields also capture impact scope, applicability conditions, protection points, and the evidence supporting conclusions.

Which model capabilities can it support?: It can support training models to read long-form vulnerability materials, synthesize impact and applicability details, extract mitigation guidance, and answer security questions using source evidence. It can also be used to evaluate these capabilities.

What are the dataset size and quality specifications?: The sample count, product coverage, and detailed quality metrics should be confirmed in the delivery documentation. Expert reference answers and evidence-related fields support answer verification and training-data review.

How can I obtain the dataset, and what are the licensing terms?: Contact the dataset provider or consult the product page for availability, delivery format, and licensing terms. Before use, verify the permitted scope and comply with applicable copyright, information security, and vulnerability disclosure requirements.

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Cite this Work

@dataset{Mobiusi2026,
  title={Web Vulnerability Advisory Comprehensive QA Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/38650d301ce4838deec683014560b9b8?dataset_scene_id=10},
  urldate={2026-10-17},
  keywords={Web vulnerability dataset,Vulnerability advisory QA,Web application security,Security question answering,Security LLM training,Vulnerability impact analysis,Mitigation guidance,Domain SFT data},
  version={1.0}
}

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