metadata
language: en
license: mit
library_name: transformers
pipeline_tag: text-classification
base_model: google/flan-t5-base
model_type: seq2seq
tags:
- security
- cve
- vulnerability
- explanation
- remediation
- devsecops
- lora
- peft
- education
datasets:
- synthetic
inference: true
CVE Human-Readable Explanation & Solution Generator
An open-source, fine-tuned language model that converts CVE (Common Vulnerabilities and Exposures) information into plain-English explanations, step-by-step remediation, and future prevention guidance.
This model is designed to educate developers and non-security users, not just classify vulnerabilities.
What This Model Does
Given a CVE description, the model explains:
- What the CVE ID means
- What the vulnerability is in simple terms
- Why it is dangerous in real life
- How to fix it step by step
- How to prevent similar issues in the future
The output is written in full sentences and paragraphs, avoiding security jargon whenever possible.
Model Architecture
- Base model: google/flan-t5-base
- Fine-tuning method: LoRA (Low-Rank Adaptation)
- Task: Text-to-Text Generation
- Weights in this repository: LoRA adapter only
The base model remains frozen; only lightweight LoRA parameters were trained.
Example
Input
Explain this vulnerability to a developer with no security background.
CVE ID: CVE-2021-44228
Software: Apache Log4j
Severity: CRITICAL
Description: Attackers can remotely execute code.