From 70b0661ce92819e6e04e59e70b80a8292d7eada2 Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Fri, 19 Jun 2026 06:26:16 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=9D=E5=A7=8B=E5=8C=96=E9=A1=B9=E7=9B=AE?= =?UTF-8?q?=EF=BC=8C=E7=94=B1ModelHub=20XC=E7=A4=BE=E5=8C=BA=E6=8F=90?= =?UTF-8?q?=E4=BE=9B=E6=A8=A1=E5=9E=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Model: Mungert/VulnLLM-R-7B-GGUF Source: Original Platform --- .gitattributes | 62 ++++++++++++ README.md | 202 ++++++++++++++++++++++++++++++++++++++ VulnLLM-R-7B-bf16.gguf | 3 + VulnLLM-R-7B-imatrix.gguf | 3 + VulnLLM-R-7B-iq2_m.gguf | 3 + VulnLLM-R-7B-iq2_s.gguf | 3 + VulnLLM-R-7B-iq3_m.gguf | 3 + VulnLLM-R-7B-iq3_s.gguf | 3 + VulnLLM-R-7B-iq4_nl.gguf | 3 + VulnLLM-R-7B-iq4_xs.gguf | 3 + VulnLLM-R-7B-q2_k_l.gguf | 3 + VulnLLM-R-7B-q2_k_m.gguf | 3 + VulnLLM-R-7B-q2_k_s.gguf | 3 + VulnLLM-R-7B-q3_k_l.gguf | 3 + VulnLLM-R-7B-q3_k_m.gguf | 3 + VulnLLM-R-7B-q3_k_s.gguf | 3 + 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+VulnLLM-R-7B-q4_k_s.gguf filter=lfs diff=lfs merge=lfs -text +VulnLLM-R-7B-q5_k_m.gguf filter=lfs diff=lfs merge=lfs -text +VulnLLM-R-7B-q5_k_s.gguf filter=lfs diff=lfs merge=lfs -text +VulnLLM-R-7B-q6_k_m.gguf filter=lfs diff=lfs merge=lfs -text +VulnLLM-R-7B-q8_0.gguf filter=lfs diff=lfs merge=lfs -text +VulnLLM-R-7B-q4_0.gguf filter=lfs diff=lfs merge=lfs -text +VulnLLM-R-7B-q4_1.gguf filter=lfs diff=lfs merge=lfs -text +VulnLLM-R-7B-q5_0.gguf filter=lfs diff=lfs merge=lfs -text +VulnLLM-R-7B-q5_1.gguf filter=lfs diff=lfs merge=lfs -text +VulnLLM-R-7B-iq2_s.gguf filter=lfs diff=lfs merge=lfs -text +VulnLLM-R-7B-iq2_m.gguf filter=lfs diff=lfs merge=lfs -text +VulnLLM-R-7B-iq3_s.gguf filter=lfs diff=lfs merge=lfs -text +VulnLLM-R-7B-iq3_m.gguf filter=lfs diff=lfs merge=lfs -text +VulnLLM-R-7B-iq4_xs.gguf filter=lfs diff=lfs merge=lfs -text +VulnLLM-R-7B-iq4_nl.gguf filter=lfs diff=lfs merge=lfs -text +VulnLLM-R-7B-imatrix.gguf filter=lfs diff=lfs merge=lfs -text +VulnLLM-R-7B-bf16.gguf filter=lfs diff=lfs merge=lfs -text diff --git a/README.md b/README.md new file mode 100644 index 0000000..56a3b30 --- /dev/null +++ b/README.md @@ -0,0 +1,202 @@ +--- +language: +- en +- code +license: apache-2.0 +tags: +- security +- vulnerability-detection +- code-analysis +- reasoning +- llm +pipeline_tag: text-generation +base_model: Qwen/Qwen2.5-7B-Instruct +--- + +# VulnLLM-R-7B GGUF Models + + +## Model Generation Details + +This model was generated using [llama.cpp](https://github.com/ggerganov/llama.cpp) at commit [`05fa625ea`](https://github.com/ggerganov/llama.cpp/commit/05fa625eac5bbdbe88b43f857156c35501421d6e). + + + + + +--- + +## Quantization Beyond the IMatrix + +I've been experimenting with a new quantization approach that selectively elevates the precision of key layers beyond what the default IMatrix configuration provides. + +In my testing, standard IMatrix quantization underperforms at lower bit depths, especially with Mixture of Experts (MoE) models. To address this, I'm using the `--tensor-type` option in `llama.cpp` to manually "bump" important layers to higher precision. You can see the implementation here: +πŸ‘‰ [Layer bumping with llama.cpp](https://github.com/Mungert69/GGUFModelBuilder/blob/main/model-converter/tensor_list_builder.py) + +While this does increase model file size, it significantly improves precision for a given quantization level. + +### **I'd love your feedbackβ€”have you tried this? How does it perform for you?** + + + + +--- + + + Click here to get info on choosing the right GGUF model format + + +--- + + + + + + +# VulnLLM-R-7B: Specialized Reasoning LLM for Vulnerability Detection + +**VulnLLM-R** is the first specialized **reasoning** Large Language Model designed specifically for software vulnerability detection. + +Unlike traditional static analysis tools (like CodeQL) or small LLMs that rely on simple pattern matching, VulnLLM-R is trained to **reason step-by-step** about data flow, control flow, and security context. It mimics the thought process of a human security auditor to identify complex logic vulnerabilities with high accuracy. + +## πŸ”— Quick Links +* **Paper:** [arXiv:2512.07533](https://arxiv.org/abs/2512.07533) +* **Code & Data:** [GitHub](https://github.com/ucsb-mlsec/VulnLLM-R) +* **Demo:** [Web demo](https://huggingface.co/spaces/UCSB-SURFI/VulnLLM-R) + +## πŸ’‘ Key Features +* **Reasoning-Based Detection:** Does not just classify code; it generates a "Chain-of-Thought" to analyze *why* a vulnerability exists. +* **Superior Accuracy:** Outperforms commercial giants (like Claude-3.7-Sonnet, o3-mini) and industry-standard tools (CodeQL, AFL++) on key benchmarks. +* **Efficiency:** Achieves SOTA performance with only **7B parameters**, making it 30x smaller and significantly faster than general-purpose reasoning models. +* **Broad Coverage:** Trained and tested on C, C++, Python, and Java (zero-shot generalization). + +## πŸš€ Quick Start + +```python +from transformers import AutoModelForCausalLM, AutoTokenizer +import torch + +model_name = "UCSB-SURFI/VulnLLM-R-7B" + +tokenizer = AutoTokenizer.from_pretrained(model_name) +model = AutoModelForCausalLM.from_pretrained( + model_name, + torch_dtype=torch.bfloat16, + device_map="auto" +) + +# Example Code Snippet +code_snippet = """ +void vulnerable_function(char *input) { + char buffer[50]; + strcpy(buffer, input); // Potential buffer overflow +} +""" + +# Prompt Template (Triggering Reasoning) +prompt = f"""You are an advanced vulnerability detection model. +Please analyze the following code step-by-step to determine if it contains a vulnerability. + +Code: +{code_snippet} + +Please provide your reasoning followed by the final answer. +""" + +messages = [ + {"role": "user", "content": prompt} +] +text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) +model_inputs = tokenizer([text], return_tensors="pt").to(model.device) + +generated_ids = model.generate( + model_inputs.input_ids, + max_new_tokens=512 +) +generated_ids = [ + output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids) +] + +response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0] +print(response) +``` + +## πŸ“Š Performance + +VulnLLM-R-7B achieves state-of-the-art results on benchmarks including PrimeVul, Juliet 1.3, and ARVO. + +model_size_vs_f1_scatter_01 + +(Refer to Figure 1 and Table 4 in the paper for detailed metrics) + +## πŸ“š Citation + +If you use this model in your research, please cite our paper: + +```Bibtex +@article{nie2025vulnllmr, + title={VulnLLM-R: Specialized Reasoning LLM with Agent Scaffold for Vulnerability Detection}, + author={Nie, Yuzhou and Li, Hongwei and Guo, Chengquan and Jiang, Ruizhe and Wang, Zhun and Li, Bo and Song, Dawn and Guo, Wenbo}, + journal={arXiv preprint arXiv:2512.07533}, + year={2025} +} +``` + + + +--- + +# πŸš€ If you find these models useful + +Help me test my **AI-Powered Quantum Network Monitor Assistant** with **quantum-ready security checks**: + +πŸ‘‰ [Quantum Network Monitor](https://readyforquantum.com/?assistant=open&utm_source=huggingface&utm_medium=referral&utm_campaign=huggingface_repo_readme) + + +The full Open Source Code for the Quantum Network Monitor Service available at my github repos ( repos with NetworkMonitor in the name) : [Source Code Quantum Network Monitor](https://github.com/Mungert69). You will also find the code I use to quantize the models if you want to do it yourself [GGUFModelBuilder](https://github.com/Mungert69/GGUFModelBuilder) + +πŸ’¬ **How to test**: + Choose an **AI assistant type**: + - `TurboLLM` (GPT-4.1-mini) + - `HugLLM` (Hugginface Open-source models) + - `TestLLM` (Experimental CPU-only) + +### **What I’m Testing** +I’m pushing the limits of **small open-source models for AI network monitoring**, specifically: +- **Function calling** against live network services +- **How small can a model go** while still handling: + - Automated **Nmap security scans** + - **Quantum-readiness checks** + - **Network Monitoring tasks** + +🟑 **TestLLM** – Current experimental model (llama.cpp on 2 CPU threads on huggingface docker space): +- βœ… **Zero-configuration setup** +- ⏳ 30s load time (slow inference but **no API costs**) . No token limited as the cost is low. +- πŸ”§ **Help wanted!** If you’re into **edge-device AI**, let’s collaborate! + +### **Other Assistants** +🟒 **TurboLLM** – Uses **gpt-4.1-mini** : +- **It performs very well but unfortunatly OpenAI charges per token. For this reason tokens usage is limited. +- **Create custom cmd processors to run .net code on Quantum Network Monitor Agents** +- **Real-time network diagnostics and monitoring** +- **Security Audits** +- **Penetration testing** (Nmap/Metasploit) + +πŸ”΅ **HugLLM** – Latest Open-source models: +- 🌐 Runs on Hugging Face Inference API. Performs pretty well using the lastest models hosted on Novita. + +### πŸ’‘ **Example commands you could test**: +1. `"Give me info on my websites SSL certificate"` +2. `"Check if my server is using quantum safe encyption for communication"` +3. `"Run a comprehensive security audit on my server"` +4. '"Create a cmd processor to .. (what ever you want)" Note you need to install a [Quantum Network Monitor Agent](https://readyforquantum.com/Download/?utm_source=huggingface&utm_medium=referral&utm_campaign=huggingface_repo_readme) to run the .net code on. This is a very flexible and powerful feature. Use with caution! + +### Final Word + +I fund the servers used to create these model files, run the Quantum Network Monitor service, and pay for inference from Novita and OpenAIβ€”all out of my own pocket. All the code behind the model creation and the Quantum Network Monitor project is [open source](https://github.com/Mungert69). Feel free to use whatever you find helpful. + +If you appreciate the work, please consider [buying me a coffee](https://www.buymeacoffee.com/mahadeva) β˜•. Your support helps cover service costs and allows me to raise token limits for everyone. + +I'm also open to job opportunities or sponsorship. + +Thank you! 😊 diff --git a/VulnLLM-R-7B-bf16.gguf b/VulnLLM-R-7B-bf16.gguf new file mode 100644 index 0000000..a0f5a31 --- /dev/null +++ b/VulnLLM-R-7B-bf16.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b26c39bd4830774cb5e2b667c0d7a2c071d51f182e7011ebfe65ee6a0f3f350c +size 15237853888 diff --git a/VulnLLM-R-7B-imatrix.gguf b/VulnLLM-R-7B-imatrix.gguf new file mode 100644 index 0000000..86cbcf4 --- /dev/null +++ b/VulnLLM-R-7B-imatrix.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:124725b8fc895624a834fa47ba2679eb2384e3a593d594c1d348771877e2ee83 +size 4560416 diff --git a/VulnLLM-R-7B-iq2_m.gguf b/VulnLLM-R-7B-iq2_m.gguf new file mode 100644 index 0000000..567dae0 --- /dev/null +++ b/VulnLLM-R-7B-iq2_m.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid 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