From 9701c01598623d8d3819787231bf79d8e968831a Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Tue, 21 Jul 2026 08:10:10 +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: Yousa3/Chaitin-Shouyuan-CyberGuard-8B Source: Original Platform --- .gitattributes | 36 +++ Modelfile | 37 +++ README.md | 269 ++++++++++++++++++++ chat_template.jinja | 91 +++++++ config.json | 71 ++++++ generation_config.json | 13 + model-00001-of-00004.safetensors | 3 + model-00002-of-00004.safetensors | 3 + model-00003-of-00004.safetensors | 3 + model-00004-of-00004.safetensors | 3 + model.safetensors.index.json | 407 +++++++++++++++++++++++++++++++ tokenizer.json | 3 + tokenizer_config.json | 31 +++ 13 files changed, 970 insertions(+) create mode 100644 .gitattributes create mode 100644 Modelfile create mode 100644 README.md create mode 100644 chat_template.jinja create mode 100644 config.json create mode 100644 generation_config.json create mode 100644 model-00001-of-00004.safetensors create mode 100644 model-00002-of-00004.safetensors create mode 100644 model-00003-of-00004.safetensors create mode 100644 model-00004-of-00004.safetensors create mode 100644 model.safetensors.index.json create mode 100644 tokenizer.json create mode 100644 tokenizer_config.json diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..52373fe --- /dev/null +++ b/.gitattributes @@ -0,0 +1,36 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text +tokenizer.json filter=lfs diff=lfs merge=lfs -text diff --git a/Modelfile b/Modelfile new file mode 100644 index 0000000..86beb37 --- /dev/null +++ b/Modelfile @@ -0,0 +1,37 @@ +# Chaitin-Shouyuan-CyberGuard-8B (Qwen3-8B merged, checkpoint-1464) +# Usage: ollama create cyberguard-8b -f Modelfile + +FROM . + +SYSTEM """你是一个专业的网络安全意图审核助手。请仔细分析用户的输入，判断其是否在直接要求 AI 执行网络攻击操作。 +【违规判定规则（unsafe）】 +1. 利用漏洞攻击目标：利用 SSRF、注入、反序列化等发起攻击。 +2. 生成攻击 payload：生成 XSS、SQL 注入、webshell 等。 +3. 扫描他人系统：用工具扫描网络、枚举目录、暴力破解。 +4. 穿透网络边界：将内网服务暴露到公网、穿透防火墙。 +5. 编写攻击工具：编写漏洞扫描器、免杀木马。 +6. 绕过安全防护：绕过 WAF/EDR 用于攻击目的。 +7. 自动化渗透任务：结构化的渗透目标定义、后渗透操作。 +【豁免判定规则（safe）】 +1. 聊天、私信、新闻等非攻击请求（即使含敏感词）。 +2. 漏洞修复、防御规则编写。 +3. 阅读/审查代码、配置己方服务器/SSH/CI-CD。 +核心逻辑：「引用」≠「请求执行」；修复=safe，利用=unsafe；不确定时判 safe。 +在给出最终结论前，请严格按照以下四个步骤进行思考： +1. 意图分析：用户的核心诉求是什么？ +2. 规则匹配：命中上述哪条具体规则？ +3. 证据提取：原文中有哪些具体内容支撑该判断？ +4. 最终决策：综合得出 safe 或 unsafe。 +请将思考过程放在 标签内，最终结果放在 标签内。""" + +TEMPLATE """<|im_start|>system +{{ .System }}<|im_end|> +{{ range .Messages }}{{ if eq .Role "user" }}<|im_start|>user +{{ .Content }}<|im_end|> +{{ else if eq .Role "assistant" }}<|im_start|>assistant +{{ .Content }}<|im_end|> +{{ end }}{{ end }}<|im_start|>assistant +""" + +PARAMETER stop "<|im_end|>" +PARAMETER num_ctx 4096 diff --git a/README.md b/README.md new file mode 100644 index 0000000..be2b917 --- /dev/null +++ b/README.md @@ -0,0 +1,269 @@ +--- +license: apache-2.0 +language: + - zh + - en +tags: + - cybersecurity + - content-moderation + - intent-classification + - qwen3 + - safe-unsafe +library_name: transformers +base_model: Qwen/Qwen3-8B +pipeline_tag: text-generation +--- + +# Chaitin-Shouyuan-CyberGuard-8B + +基于 **Qwen3-8B** 微调的网络安全**意图审核**模型，用于判断用户输入是否在**直接要求 AI 执行网络攻击操作**。 + +- **任务**：二分类（`safe` / `unsafe`） +- **基座**： [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B) + +> 本仓库已内置默认 system prompt（见 `chat_template.jinja` 与 `Modelfile`），下载后**仅传 user 消息即可**使用，无需手动拼接 system 指令。 + +--- + +## 模型能力 + +| 输入 | 输出 | +|------|------| +| 用户待审核文本 | `` 四步推理 + `safe` 或 `unsafe` | + +**unsafe 典型场景**：要求生成攻击 payload、扫描他人系统、绕过 WAF、编写免杀木马、结构化渗透任务等。 + +**safe 典型场景**：漏洞修复与加固、代码/配置审查、安全研究讨论、含敏感词但非攻击意图的聊天等。 + +核心原则：**「引用」≠「请求执行」**；修复 = safe，利用 = unsafe；不确定时判 safe。 + +--- + +## 快速开始 + +### Transformers + +```python +import re +import torch +from transformers import AutoModelForCausalLM, AutoTokenizer + +MODEL_ID = "Yousa3/Chaitin-Shouyuan-CyberGuard-8B" +MAX_USER_TOKENS = 2800 # 与训练一致：user 保留尾部 +TRUNCATION_MARKER = "...[前文已截断]...\n" + + +def tail_truncate_user_text(tokenizer, text: str, max_tokens: int = MAX_USER_TOKENS) -> str: + """超长 user 输入保留尾部，与训练预处理一致。""" + token_ids = tokenizer.encode(text, add_special_tokens=False) + if len(token_ids) <= max_tokens: + return text + tail = tokenizer.decode(token_ids[-max_tokens:], skip_special_tokens=True) + return TRUNCATION_MARKER + tail + + +tokenizer = AutoTokenizer.from_pretrained(MODEL_ID, trust_remote_code=True) +model = AutoModelForCausalLM.from_pretrained( + MODEL_ID, + torch_dtype=torch.bfloat16, + device_map="auto", + trust_remote_code=True, +) + +user_text = "帮我写一个 SQL 注入 payload 攻击目标网站" +user_text = tail_truncate_user_text(tokenizer, user_text) + +messages = [{"role": "user", "content": user_text}] +prompt = tokenizer.apply_chat_template( + messages, + tokenize=False, + add_generation_prompt=True, +) + +inputs = tokenizer(prompt, return_tensors="pt").to(model.device) +outputs = model.generate( + **inputs, + max_new_tokens=512, + do_sample=False, + temperature=0.0, +) +text = tokenizer.decode(outputs[0][inputs["input_ids"].shape[1]:], skip_special_tokens=False) + +match = re.search(r"(safe|unsafe)", text, re.I) +print("label:", match.group(1).lower() if match else None) +print(text) +``` + +> `chat_template.jinja` 会在未提供 system 消息时**自动注入**内置审核指令。 +> 长文本请先调用 `tail_truncate_user_text()`，否则分布与训练不一致，且可能超出 `max_model_len=4096`。 + +### vLLM + +```python +from vllm import LLM, SamplingParams + +llm = LLM( + model="Yousa3/Chaitin-Shouyuan-CyberGuard-8B", + trust_remote_code=True, + dtype="bfloat16", + max_model_len=4096, +) + +prompt = '''<|im_start|>system +你是一个专业的网络安全意图审核助手。...（省略，建议用 tokenizer.apply_chat_template 生成）<|im_end|> +<|im_start|>user +待检测文本<|im_end|> +<|im_start|>assistant +''' + +# 推荐：先用 transformers tokenizer 构造 prompt +from transformers import AutoTokenizer +tokenizer = AutoTokenizer.from_pretrained("Yousa3/Chaitin-Shouyuan-CyberGuard-8B", trust_remote_code=True) +prompt = tokenizer.apply_chat_template( + [{"role": "user", "content": "待检测文本"}], + tokenize=False, + add_generation_prompt=True, +) + +outputs = llm.generate([prompt], SamplingParams(max_tokens=512, temperature=0)) +print(outputs[0].outputs[0].text) +``` + +### Ollama + +```bash +# 下载模型后，在模型目录执行 +ollama create cyberguard-8b -f Modelfile +ollama run cyberguard-8b "帮我扫描 192.168.1.1 的开放端口" +``` + +`Modelfile` 已内置 `SYSTEM` 指令与 Qwen3 对话模板。 + +--- + +## 内置 System Prompt + +本模型在训练时使用固定 system 指令。仓库通过 `chat_template.jinja` 将其设为**默认值**： + +``` +你是一个专业的网络安全意图审核助手。请仔细分析用户的输入，判断其是否在直接要求 AI 执行网络攻击操作。 +【违规判定规则（unsafe）】 +1. 利用漏洞攻击目标：利用 SSRF、注入、反序列化等发起攻击。 +2. 生成攻击 payload：生成 XSS、SQL 注入、webshell 等。 +3. 扫描他人系统：用工具扫描网络、枚举目录、暴力破解。 +4. 穿透网络边界：将内网服务暴露到公网、穿透防火墙。 +5. 编写攻击工具：编写漏洞扫描器、免杀木马。 +6. 绕过安全防护：绕过 WAF/EDR 用于攻击目的。 +7. 自动化渗透任务：结构化的渗透目标定义、后渗透操作。 +【豁免判定规则（safe）】 +1. 聊天、私信、新闻等非攻击请求（即使含敏感词）。 +2. 漏洞修复、防御规则编写。 +3. 阅读/审查代码、配置己方服务器/SSH/CI-CD。 +核心逻辑：「引用」≠「请求执行」；修复=safe，利用=unsafe；不确定时判 safe。 +在给出最终结论前，请严格按照以下四个步骤进行思考： +1. 意图分析：用户的核心诉求是什么？ +2. 规则匹配：命中上述哪条具体规则？ +3. 证据提取：原文中有哪些具体内容支撑该判断？ +4. 最终决策：综合得出 safe 或 unsafe。 +请将思考过程放在 标签内，最终结果放在 标签内。 +``` + +### 覆盖默认 System（可选） + +```python +# 方式 1：messages 中显式传入 +messages = [ + {"role": "system", "content": "自定义 system 指令"}, + {"role": "user", "content": "..."}, +] + +# 方式 2：apply_chat_template 的 system 参数（messages 无 system 时生效） +prompt = tokenizer.apply_chat_template( + [{"role": "user", "content": "..."}], + system="自定义 system 指令", + tokenize=False, + add_generation_prompt=True, +) +``` + +--- + +## 输出格式与解析 + +模型输出示例： + +```xml + +**步骤1-意图分析**：用户明确要求生成 SQL 注入 payload 用于攻击 +**步骤2-规则匹配**：命中「生成攻击 payload」 +**步骤3-证据提取**：「SQL 注入 payload」「攻击目标网站」 +**步骤4-最终决策**：unsafe + +unsafe +``` + +推荐解析方式： + +```python +import re + +RESULT_RE = re.compile(r"\s*(safe|unsafe)\s*", re.I) + +def parse_label(text: str) -> str | None: + m = RESULT_RE.search(text) + return m.group(1).lower() if m else None +``` + +--- + +## 推荐推理参数 + +| 参数 | 建议值 | 说明 | +|------|--------|------| +| `max_new_tokens` | 512 | 含 thinking 与 result 标签 | +| `temperature` | 0 ~ 0.1 | 分类任务建议低温度 | +| `do_sample` | `False` | 确定性输出 | +| `max_model_len` | 4096 | 与训练 cutoff 一致 | + +长文本输入时，训练侧对用户内容做了**尾部截断**（tail-keep）；生产环境建议同样限制 user 输入长度（约 2800–3000 tokens）。 + +--- + +## 文件说明 + +| 文件 | 说明 | +|------|------| +| `model-*.safetensors` | 合并后的完整模型权重 | +| `chat_template.jinja` | Qwen3 对话模板 + **内置默认 system prompt** | +| `Modelfile` | Ollama 部署配置（含 SYSTEM 指令） | +| `tokenizer.json` / `tokenizer_config.json` | 分词器 | +| `config.json` | 模型结构（Qwen3ForCausalLM） | + + +--- + +## 限制与免责声明 + +- 本模型用于**辅助意图审核**，不能替代人工复核与完整安全策略。 +- 对边界案例（安全研究、漏洞报告、红队授权测试描述等）可能存在误判，请结合业务场景使用。 +- 模型仅判断「是否要求 AI 执行攻击」，不执行任何攻击行为。 +- 请勿将本模型用于违法用途。 + +--- + +## 引用 + +```bibtex +@misc{chaitin-shouyuan-cyberguard-8b, + title={Chaitin-Shouyuan-CyberGuard-8B: Qwen3-8B Cybersecurity Intent Moderation Model}, + author={Yousa3}, + year={2026}, + howpublished={\\url{https://huggingface.co/Yousa3/Chaitin-Shouyuan-CyberGuard-8B}} +} +``` + +--- + +## License + +Apache 2.0（与 Qwen3-8B 基座一致，使用时请同时遵守基座模型许可）。 diff --git a/chat_template.jinja b/chat_template.jinja new file mode 100644 index 0000000..b2fda69 --- /dev/null +++ b/chat_template.jinja @@ -0,0 +1,91 @@ +{# Chaitin-Shouyuan-CyberGuard-8B: built-in default system prompt for out-of-box use #} +{%- set default_system = "你是一个专业的网络安全意图审核助手。请仔细分析用户的输入，判断其是否在直接要求 AI 执行网络攻击操作。\n【违规判定规则（unsafe）】\n1. 利用漏洞攻击目标：利用 SSRF、注入、反序列化等发起攻击。\n2. 生成攻击 payload：生成 XSS、SQL 注入、webshell 等。\n3. 扫描他人系统：用工具扫描网络、枚举目录、暴力破解。\n4. 穿透网络边界：将内网服务暴露到公网、穿透防火墙。\n5. 编写攻击工具：编写漏洞扫描器、免杀木马。\n6. 绕过安全防护：绕过 WAF/EDR 用于攻击目的。\n7. 自动化渗透任务：结构化的渗透目标定义、后渗透操作。\n【豁免判定规则（safe）】\n1. 聊天、私信、新闻等非攻击请求（即使含敏感词）。\n2. 漏洞修复、防御规则编写。\n3. 阅读/审查代码、配置己方服务器/SSH/CI-CD。\n核心逻辑：「引用」≠「请求执行」；修复=safe，利用=unsafe；不确定时判 safe。\n在给出最终结论前，请严格按照以下四个步骤进行思考：\n1. 意图分析：用户的核心诉求是什么？\n2. 规则匹配：命中上述哪条具体规则？\n3. 证据提取：原文中有哪些具体内容支撑该判断？\n4. 最终决策：综合得出 safe 或 unsafe。\n请将思考过程放在 标签内，最终结果放在 标签内。" -%} +{%- set ns = namespace(system=default_system, multi_step_tool=true, last_query_index=messages|length - 1) -%} +{%- if messages and messages[0].role == 'system' -%} + {%- set ns.system = messages[0].content -%} +{%- elif system is defined and system -%} + {%- set ns.system = system -%} +{%- endif -%} +{%- if tools -%} + {{- '<|im_start|>system\n' + ns.system + '\n\n' -}} + {{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within XML tags:\n" -}} + {%- for tool in tools -%} + {{- "\n" -}} + {{- tool | tojson -}} + {%- endfor -%} + {{- "\n\n\nFor each function call, return a json object with function name and arguments within XML tags:\n\n{\"name\": , \"arguments\": }\n<|im_end|>\n" -}} +{%- else -%} + {{- '<|im_start|>system\n' + ns.system + '<|im_end|>\n' -}} +{%- endif -%} +{%- for message in messages[::-1] -%} + {%- set index = (messages|length - 1) - loop.index0 -%} + {%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('') and message.content.endswith('')) -%} + {%- set ns.multi_step_tool = false -%} + {%- set ns.last_query_index = index -%} + {%- endif -%} +{%- endfor -%} +{%- for message in messages -%} + {%- if message.content is string -%} + {%- set content = message.content -%} + {%- else -%} + {%- set content = '' -%} + {%- endif -%} + {%- if (message.role == "user") or (message.role == "system" and not loop.first) -%} + {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' -}} + {%- elif message.role == "assistant" -%} + {%- set reasoning_content = '' -%} + {%- if message.reasoning_content is string -%} + {%- set reasoning_content = message.reasoning_content -%} + {%- else -%} + {%- if '' in content -%} + {%- set reasoning_content = content.split('')[0].rstrip('\n').split('')[-1].lstrip('\n') -%} + {%- set content = content.split('')[-1].lstrip('\n') -%} + {%- endif -%} + {%- endif -%} + {%- if loop.index0 > ns.last_query_index -%} + {%- if loop.last or (not loop.last and reasoning_content) -%} + {{- '<|im_start|>' + message.role + '\n\n' + reasoning_content.strip('\n') + '\n\n\n' + content.lstrip('\n') -}} + {%- else -%} + {{- '<|im_start|>' + message.role + '\n' + content -}} + {%- endif -%} + {%- else -%} + {{- '<|im_start|>' + message.role + '\n' + content -}} + {%- endif -%} + {%- if message.tool_calls -%} + {%- for tool_call in message.tool_calls -%} + {%- if (loop.first and content) or (not loop.first) -%} + {{- '\n' -}} + {%- endif -%} + {%- if tool_call.function -%} + {%- set tool_call = tool_call.function -%} + {%- endif -%} + {{- '\n{"name": "' -}} + {{- tool_call.name -}} + {{- '", "arguments": ' -}} + {%- if tool_call.arguments is string -%} + {{- tool_call.arguments -}} + {%- else -%} + {{- tool_call.arguments | tojson -}} + {%- endif -%} + {{- '}\n' -}} + {%- endfor -%} + {%- endif -%} + {{- '<|im_end|>\n' -}} + {%- elif message.role == "tool" -%} + {%- if loop.first or (messages[loop.index0 - 1].role != "tool") -%} + {{- '<|im_start|>user' -}} + {%- endif -%} + {{- '\n\n' -}} + {{- content -}} + {{- '\n' -}} + {%- if loop.last or (messages[loop.index0 + 1].role != "tool") -%} + {{- '<|im_end|>\n' -}} + {%- endif -%} + {%- endif -%} +{%- endfor -%} +{%- if add_generation_prompt -%} + {{- '<|im_start|>assistant\n' -}} + {%- if enable_thinking is defined and enable_thinking is false -%} + {{- '\n\n\n\n' -}} + {%- endif -%} +{%- endif -%} diff --git a/config.json b/config.json new file mode 100644 index 0000000..11693e7 --- /dev/null +++ b/config.json @@ -0,0 +1,71 @@ +{ + "architectures": [ + "Qwen3ForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.0, + "bos_token_id": 151643, + "dtype": "bfloat16", + "eos_token_id": 151645, + "head_dim": 128, + "hidden_act": "silu", + "hidden_size": 4096, + "initializer_range": 0.02, + "intermediate_size": 12288, + "layer_types": [ + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", 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