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315 lines
11 KiB
315 lines
11 KiB
import queue
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import copy
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import re
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import threading
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#渗透测试树结构维护类
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class AttackTree:
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def __init__(self,root_node):
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#针对根节点处理
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self.root = root_node
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self.root.path = f"目标系统->{root_node.name}"
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def set_root(self,root_node):
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self.root = root_node
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def add_node(self,parent_name,new_node):
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"""根据父节点名称添加新节点"""
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parent_node = self.find_node_by_name(parent_name)
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if parent_node:
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parent_node.add_child(new_node)
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return True
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return False
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def traverse_bfs(self):
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"""广度优先遍历"""
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if not self.root:
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return []
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queue = [self.root]
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result = []
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while queue:
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current = queue.pop(0)
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result.append(current)
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queue.extend(current.children)
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return result
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def traverse_dfs(self, node=None, result=None):
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"""深度优先遍历（前序遍历）"""
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if result is None:
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result = []
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if node is None:
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node = self.root
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if not node:
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return []
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result.append(node)
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for child in node.children:
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self.traverse_dfs(child, result)
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return result
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#生成节点树字典数据
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def node_to_dict(self,node):
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return {
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"node_name":node.name,
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"node_path":node.path,
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"node_status":node.status,
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"node_bwork":node.bwork,
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"node_vultype":node.vul_type,
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"node_vulgrade":node.vul_grade,
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"node_workstatus":node.get_work_status(),
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"children":[self.node_to_dict(child) for child in node.children] if node.children else []
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}
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#树简化列表，用户传输到前端
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def get_node_dict(self):
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node_dict = self.node_to_dict(self.root) #递归生成
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return node_dict
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def find_node_by_name(self, name):
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"""根据名称查找节点（广度优先）"""
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nodes = self.traverse_bfs()
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for node in nodes:
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if node.name == name:
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return node
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return None
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def find_node_by_nodepath_parent(self,node_path,node):
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node_names = node_path.split('->')
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node_name = node_names[-1]
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if node_name == node.name:#当前节点
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return node
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else:
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if node_names[-2] == node.name: #父节点是当前节点
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for child_node in node.children:
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if child_node.name == node_name:
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return child_node
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#走到这说明没有匹配到-则新建一个节点
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newNode = TreeNode(node_name,node.task_id)
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node.add_child(newNode)
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return newNode
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else:
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return None #约束：不处理
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def find_node_by_nodepath(self,node_path):
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'''基于节点路径查找节点，只返回找到的第一个节点，若有节点名称路径重复的情况暂不处理'''
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current_node = self.root #从根节点开始
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node_names = node_path.split('->')
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layer_num = 0
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for node_name in node_names:
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if node_name == "目标系统":
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layer_num +=1
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continue
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if node_name == current_node.name:#根节点开始
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layer_num += 1
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continue
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else:
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bfound = False
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for child_node in current_node.children:
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if child_node.name == node_name: #约束同一父节点下的子节点名称不能相同
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current_node = child_node
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layer_num += 1
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bfound = True
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break
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if not bfound: #如果遍历子节点都没有符合的，说明路径有问题的，不处理中间一段路径情况
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return None
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return current_node
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#更新节点的bwork状态
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def update_node_bwork(self,node_path):
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node = self.find_node_by_nodepath(node_path)
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if not node:
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return False,False
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if node.bwork:
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node.bwork = False
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else:
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node.bwork = True
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return True,node.bwork
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def find_nodes_by_status(self, status):
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"""根据状态查找所有匹配节点"""
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return [node for node in self.traverse_bfs() if node.status == status]
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def find_nodes_by_vul_type(self, vul_type):
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"""根据漏洞类型查找所有匹配节点"""
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return [node for node in self.traverse_bfs() if node.vul_type == vul_type]
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#考虑要不要用tree封装节点的操作--待定
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def update_node_status(self, node_name, new_status):
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"""修改节点状态"""
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node = self.find_node_by_name(node_name)
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if node:
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node.status = new_status
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return True
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return False
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def update_node_vul_type(self,node_name,vul_type):
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"""修改节点漏洞类型"""
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node = self.find_node_by_name(node_name)
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if node:
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node.vul_type = vul_type
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return True
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return False
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def print_tree(self, node=None, level=0):
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"""可视化打印树结构"""
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if node is None:
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node = self.root
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prefix = " " * level + "|-- " if level > 0 else ""
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print(f"{prefix}{node.name} [{node.status}, {node.vul_type}]")
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for child in node.children:
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self.print_tree(child, level + 1)
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class TreeNode:
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def __init__(self, name,task_id,status="未完成", vul_type="未发现"):
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self.task_id = task_id #任务id
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self.name = name # 节点名称
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#self.node_lock = threading.Lock() #线程锁
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self.bwork = True # 当前节点是否工作，默认True --停止/启动
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self.status = status # 节点测试状态 -- 由llm返回指令触发更新
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#work_status需要跟两个list统一管理：初始0，入instr_queue为1，入instr_node_mq为2，入res_queue为3，入llm_node_mq为4，llm处理完0或1
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self._work_status = 0 #0-无任务，1-待执行测试指令，2-执行指令中，3-待提交Llm,4-提交llm中， 2025-4-6新增，用来动态显示节点的工作细节。
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self.vul_type = vul_type # 漏洞类型--目前赋值时没拆json
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self.vul_name = ""
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self.vul_grade = ""
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self.vul_info = ""
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self.children = [] # 子节点列表
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self.parent = None # 父节点引用
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self.path = "" #当前节点的路径
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self.messages = [] # 针对当前节点积累的messages -- 针对不同节点提交不同的messages
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self.llm_type = 0 #llm提交类型 0--初始状态无任务状态，1--指令结果反馈，2--llm错误反馈
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self.llm_sn = 0 #针对该节点llm提交次数
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self._llm_quere = [] #待提交llm的数据
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self.do_sn = 0 #针对该节点instr执行次数
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self._instr_queue = [] #针对当前节点的待执行指令----重要约束：一个节点只能有一个线程在执行指令
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self.his_instr = [] #保留执行指令的记录｛“instr”:***,"result":***｝
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#用户补充信息
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self.cookie = ""
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self.ext_info = ""
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#设置用户信息
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def set_user_info(self,cookie,ext_info):
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self.cookie = cookie
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self.ext_info = ext_info
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def copy_messages(self,childe_node):
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'''
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子节点继承父节点的messages，目前规则保留上两层节点的message信息
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:param childe_node:
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:return:
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'''
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tmp_messages = copy.deepcopy(self.messages)
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if not self.parent:
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childe_node.messages = tmp_messages
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else:
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parent_path = self.parent.path
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bfind = False
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for msg in tmp_messages:
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if msg["role"] == "system":
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childe_node.messages.append(msg)
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elif msg["role"] == "user":
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if not bfind:
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#获取user的node_path
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content = msg["content"]
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pattern = r"当前分支路径：(.+?)\n"
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match = re.search(pattern, content)
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if match:
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path = match.group(1)
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if parent_path in path:#当前节点的父节点路径在存入子节点messages
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childe_node.messages.append(msg)
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bfind = True #后续messages都保留
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else:
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print("提交的用户提示词结构有问题！")
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else:
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childe_node.messages.append(msg)
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elif msg["role"] == "assistant":
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if bfind:
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childe_node.messages.append(msg)
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else:
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print("非法的信息体类型！")
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#添加子节点
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def add_child(self, child_node):
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child_node.parent = self
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child_node.path = self.path + f"->{child_node.name}" #子节点的路径赋值
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#child_node.messages = copy.deepcopy(self.messages) #传递messages #给什么时候的messages待验证#？
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self.copy_messages(child_node) #传递messages--只保留两层
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self.children.append(child_node)
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#修改节点的执行状态--return bchange
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def update_work_status(self,work_status):
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if self._work_status == work_status:
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return False
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self._work_status = work_status
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return True
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def get_work_status(self):
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#加锁有没有意义--待定
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return self._work_status
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#-------后期扩充逻辑，目前wokr_status的修改交给上层类对象-------
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def add_instr(self,instr):
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self._instr_queue.append(instr)
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def get_instr(self):
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return self._instr_queue.pop(0) if self._instr_queue else None
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def get_instr_user(self):
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return self._instr_queue
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def del_instr(self,instr):
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if instr in self._instr_queue:
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self._instr_queue.remove(instr)
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#指令删除后要判断是否清空指令了
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if not self._instr_queue:
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self._work_status = 0 #状态调整为没有带执行指令
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return True,""
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else:
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return False,"该指令不在队列中！"
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def add_res(self,str_res): #结构化结果字串
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self._llm_quere.append(str_res)
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def get_res(self):
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return self._llm_quere.pop(0) if self._llm_quere else None
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def get_res_user(self):
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return self._llm_quere
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def get_work_status(self):
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return self._work_status
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def updatemsg(self,newtype,newcontent,index):
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newmsg = {"llm_type":int(newtype),"result":newcontent}
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if self._llm_quere:
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self._llm_quere[0] = newmsg
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else:#新增消息
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self._llm_quere.append(newmsg)
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#更新节点状态
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self._work_status = 3 #待提交
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return True,""
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def is_instr_empty(self):
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if self._instr_queue:
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return False
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return True
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def is_llm_empty(self):
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if self._llm_quere:
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return False
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return True
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def __repr__(self):
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return f"TreeNode({self.name}, {self.status}, {self.vul_type})"
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if __name__ == "__main__":
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pass
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