MODEL PROFILE

Qwen2.5-3B-CyberSecurity-Instruct

Mohamedabul · Qwen2.5-3B-CyberSecurity-Instruct

A fine-tuned version of `Qwen2.5-3B-Instruct` specifically designed for advanced cybersecurity analysis. This model is built to bridge the gap between high-level vulnerability descriptions and low-level exploit code execution. 1. **Vulnerability Triage**: Automatically generating structured severity, attack vector, and mitigation reports for any CVE. 2. **Exploit Reverse-Engineering**: Analyzing raw exploit code (C, Python, Bash) to provide an immediate technical breakdown of *how* the exploit works and what vulnerabilities it targets. 3. **Attack Chain Reasoning**: Combining a CVE with raw exploit code to generate a step-by-step kill-chain analysis, from initial access to system compromise. To achieve maximum accuracy, the model was fine-tuned on an expansive historical corpus of modern vulnerabilities and exploits, completely uncapped and unfiltered: - **NVD CVE Database**: Vulnerabilities published between 2020 through 2025. - **Exploit-DB**: Over 45,000+ real-world exploits directly from Offensive Security. - **MITRE CWE**: Full weakness classifications, likelihood of exploit, and abstractions. - **Total Dataset Size**: ~187,700 structured instruction samples.

Text generationlicense:apache-2.0
Context windowNot disclosed
Input → OutputText → Text
Model weightsNot verified
Profile updated2026/10/30 21:47:03
OVERVIEW

Model overview

A fine-tuned version of `Qwen2.5-3B-Instruct` specifically designed for advanced cybersecurity analysis. This model is built to bridge the gap between high-level vulnerability descriptions and low-level exploit code execution. 1. **Vulnerability Triage**: Automatically generating structured severity, attack vector, and mitigation reports for any CVE. 2. **Exploit Reverse-Engineering**: Analyzing raw exploit code (C, Python, Bash) to provide an immediate technical breakdown of *how* the exploit works and what vulnerabilities it targets. 3. **Attack Chain Reasoning**: Combining a CVE with raw exploit code to generate a step-by-step kill-chain analysis, from initial access to system compromise. To achieve maximum accuracy, the model was fine-tuned on an expansive historical corpus of modern vulnerabilities and exploits, completely uncapped and unfiltered: - **NVD CVE Database**: Vulnerabilities published between 2020 through 2025. - **Exploit-DB**: Over 45,000+ real-world exploits directly from Offensive Security. - **MITRE CWE**: Full weakness classifications, likelihood of exploit, and abstractions. - **Total Dataset Size**: ~187,700 structured instruction samples.

Key features

特点摘要待依据来源补齐,不凭模型名称推断能力。

Limitations & considerations

Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.

PRICING & COST

Source prices & cost analysis

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Estimate monthly base token costs

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INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

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Frequently asked questions

Do open weights permit free commercial use?

Not necessarily. Check the version license, commercial conditions and usage policies. Self-hosting incurs compute and maintenance costs.

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Sources & traceability

许可证:apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。