Init commit.

ai_analysis.py

@@ -0,0 +1,129 @@
+import os
+import json
+import glob
+from openai import OpenAI
+from typing import Dict, List, Any
+
+
+class ContentParser:
+    def __init__(
+        self,
+        target_keys: str,
+        api_key: str,
+        base_url: str = "https://dashscope.aliyuncs.com/compatible-mode/v1",
+        model: str = "gpt-3.5-turbo",
+    ):
+        """
+        初始化解析器
+        :param target_keys: 需要提取的目标键列表
+        :param api_key: 大模型API密钥
+        :param model: 使用的大模型名称
+        """
+        self.client = OpenAI(
+            api_key=api_key,
+            base_url=base_url,
+        )
+        self.target_keys = target_keys
+        self.log = open("name.log", "w", encoding="utf-8")
+
+    def process_directory(self, directory: str, recursive: bool = True):
+        """
+        处理目录中的所有文件
+        :param directory: 要处理的目录路径
+        :param recursive: 是否递归处理子目录
+        """
+        results = []
+
+        # 遍历目录
+        pattern = "**/*" if recursive else "*"
+        for filepath in glob.glob(
+            os.path.join(directory, pattern), recursive=recursive
+        ):
+            if os.path.isfile(filepath):
+                _, ext = os.path.splitext(filepath)
+                if ext == ".json":
+                    try:
+                        result = self._process_json(filepath)
+                        if result:
+                            results.append({"file": filepath, "description": result})
+                            if self._check_related(result):
+                                self.log.write(f"{filepath}\n")
+                                # self._analyze_with_ai(result)
+                    except Exception as e:
+                        print(f"处理文件 {filepath} 时出错: {str(e)}")
+        return
+
+    def _process_json(self, filepath: str) -> str:
+        """处理JSON文件"""
+        with open(filepath, "r", encoding="utf-8") as f:
+            data = json.load(f)
+        return self._extract_values(data)
+
+    def _extract_values(self, data: Dict) -> str:
+        """从数据中提取目标值，支持嵌套查询"""
+        parts = self.target_keys.split(".")
+        value = data
+        try:
+            for part in parts:
+                if isinstance(value, list):
+                    value = value[int(part)]
+                else:
+                    value = value.get(part, None)
+                if value is None:
+                    break
+            return value.__str__()
+        except (KeyError, IndexError, TypeError):
+            return ""
+        return ""
+
+    def _check_related(self, text: str) -> bool:
+        keywords = ["docker", "namespace", "cgroup"]
+        text = text.lower()
+        return any(keyword in text for keyword in keywords)
+
+    def _analyze_with_ai(self, data: str):
+        prompt = """
+        请分析下面用户从文件中提取的数据，给出总结报告：
+        分析要求：
+        1. 分析这个CVE信息是否与Linux、Kernel相关
+        2. 如果满足与Linux、Kernel相关，分析是否与namespace、cgroup、container或者容器、隔离相关
+        3. 如果不满足1、2两个条件，直接输出“非相关CVE”，不需要附带任何其他内容
+        4. 如果满足1、2两个条件，直接输出“可疑CVE”，不需要附带任何其他内容
+        """
+
+        try:
+            completion = self.client.chat.completions.create(
+                # 模型列表：https://help.aliyun.com/zh/model-studio/getting-started/models
+                model="qwen-plus",
+                messages=[
+                    {"role": "system", "content": prompt},
+                    {
+                        "role": "user",
+                        "content": data,
+                    },
+                ],
+                # Qwen3模型通过enable_thinking参数控制思考过程（开源版默认True，商业版默认False）
+                # 使用Qwen3开源版模型时，若未启用流式输出，请将下行取消注释，否则会报错
+                # extra_body={"enable_thinking": False},
+            )
+            print(completion.model_dump_json())
+        except Exception as e:
+            print(f"调用大模型失败: {str(e)}")
+
+
+if __name__ == "__main__":
+    # 配置参数
+    CONFIG = {
+        "target_keys": "containers.cna.descriptions.0.value",
+        "api_key": "sk-5ec7751941974a9cb5855f746fe45a62",
+        "directory": "./data",
+        "recursive": True,
+    }
+
+    # 创建解析器实例
+    parser = ContentParser(target_keys=CONFIG["target_keys"], api_key=CONFIG["api_key"])
+
+    # 开始处理
+    parser.process_directory(
+        directory=CONFIG["directory"], recursive=CONFIG["recursive"]
+    )