标签：日志 编号 阶段 技术 集中 ems main exp 代码
dataset = [[‘my‘, ‘dog‘, ‘has‘, ‘flea‘, ‘problems‘, ‘help‘, ‘please‘], [‘maybe‘, ‘not‘, ‘take‘, ‘him‘, ‘to‘, ‘dog‘, ‘park‘, ‘stupid‘], [‘my‘, ‘dalmation‘, ‘is‘, ‘so‘, ‘cute‘, ‘I‘, ‘love‘, ‘him‘], [‘stop‘, ‘posting‘, ‘stupid‘, ‘worthless‘, ‘garbage‘], [‘mr‘, ‘licks‘, ‘ate‘, ‘my‘, ‘steak‘, ‘how‘, ‘to‘, ‘stop‘, ‘him‘], [‘quit‘, ‘buying‘, ‘worthless‘, ‘dog‘, ‘food‘, ‘stupid‘]]
1 vocabSet = set() 2 for doc in dataset: 3 vocabSet |= set(doc) 4 vocabList = list(vocabSet)
1 # 词集模型 2 SOW = [] 3 for doc in dataset: 4 vec = [0]*len(vocabList) 5 for i, word in enumerate(vocabList): 6 if word in doc: 7 vec[i] = 1 8 SOW.append(doc)
1 fredist = nltk.FreqDist(tokens_list) # 单文件词频 2 keys=fredist.keys() 3 keys=keys[:max] #只提取前N个频发使用的单词 其余泛化成0 4 for localkey in keys: # 获取统计后的不重复词集 5 if localkey in wordbag.keys(): # 判断该词是否已在词集中 6 continue 7 else: 8 wordbag[localkey] = index_wordbag 9 index_wordbag += 1
<script>alert(‘XSS‘)</script> %3cscript%3ealert(‘XSS‘)%3c/script%3e %22%3e%3cscript%3ealert(‘XSS‘)%3c/script%3e <IMG SRC="javascript:alert(‘XSS‘);"> <IMG SRC=javascript:alert("XSS")> <IMG SRC=javascript:alert(‘XSS‘)> <img src=xss onerror=alert(1)> <IMG """><SCRIPT>alert("XSS")</SCRIPT>"> <IMG SRC=javascript:alert(String.fromCharCode(88,83,83))> <IMG SRC="jav ascript:alert(‘XSS‘);"> <IMG SRC="jav ascript:alert(‘XSS‘);"> <BODY BACKGROUND="javascript:alert(‘XSS‘)"> <BODY ONLOAD=alert(‘XSS‘)>
● 单双引号包含的内容 ‘XSS‘ ● http/https链接 http://xi.baidu.com/xss.js ● <>标签 <script> ● <>标签开头 <BODY ● 属性标签 ONLOAD= ● <>标签结尾 > ● 函数体 "javascript:alert(‘XSS‘);" ● 字符数字标量
1 tokens_pattern = r‘‘‘(?x) 2 "[^"]+" 3 |http://\S+ 4 |</\w+> 5 |<\w+> 6 |<\w+ 7 |\w+= 8 |> 9 |\w+\([^<]+\) #函数 比如alert(String.fromCharCode(88,83,83)) 10 |\w+ 11 ‘‘‘ 12 words=nltk.regexp_tokenize(line, tokens_pattern)
#数字常量替换成8 line, number = re.subn(r‘\d+‘, "8", line) #ulr日换成http://u line, number = re.subn(r‘(http|https)://[a-zA-Z0-9\.@&/#!#\?]+‘, "http://u", line) #干掉注释 line, number = re.subn(r‘\/\*.?\*\/‘, "", line)
#原始参数值："><img src=x onerror=prompt(0)>) #分词后： [‘>‘, ‘<img‘, ‘src=‘, ‘x‘, ‘onerror=‘, ‘prompt(8)‘, ‘>‘] #原始参数值：<iframe src="x-javascript:alert(document.domain);"></iframe>) #分词后： [‘<iframe‘, ‘src=‘, ‘"x-javascript:alert(document.domain);"‘, ‘>‘, ‘</iframe>‘] #原始参数值：<marquee><h1>XSS by xss</h1></marquee> ) #分词后： [‘<marquee>‘, ‘<h8>‘, ‘XSS‘, ‘by‘, ‘xss‘, ‘</h8>‘, ‘</marquee>‘] #原始参数值：<script>-=alert;-(1)</script> "onmouseover="confirm(document.domain);"" </script>) #分词后： [‘<script>‘, ‘alert‘, ‘8‘, ‘</script>‘, ‘"onmouseover="‘, ‘confirm(document.domain)‘, ‘</script>‘] #原始参数值：<script>alert(2)</script> "><img src=x onerror=prompt(document.domain)>) #分词后： [‘<script>‘, ‘alert(8)‘, ‘</script>‘, ‘>‘, ‘<img‘, ‘src=‘, ‘x‘, ‘onerror=‘, ‘prompt(document.domain)‘, ‘>‘]
1 remodel = hmm.GaussianHMM(n_components=3, covariance_type="full", n_iter=100) 2 remodel.fit(X,X_lens)
1 with open(filename) as f: 2 for line in f: 3 line = line.strip(‘\n‘) 4 line = urllib.unquote(line) 5 h = HTMLParser.HTMLParser() 6 line = h.unescape(line) 7 if len(line) >= MIN_LEN: 8 line, number = re.subn(r‘\d+‘, "8", line) 9 line, number = re.subn(r‘(http|https)://[a-zA-Z0-9\.@&/#!#\?:]+‘, "http://u", line) 10 line, number = re.subn(r‘\/\*.?\*\/‘, "", line) 11 words = do_str(line) 12 vers = [] 13 for word in words: 14 if word in wordbag.keys(): 15 vers.append([wordbag[word]]) 16 else: 17 vers.append([-1]) 18 np_vers = np.array(vers) 19 pro = remodel.score(np_vers) 20 if pro >= T: 21 print "SCORE:(%d) XSS_URL:(%s) " % (pro,line)
标签：日志 编号 阶段 技术 集中 ems main exp 代码
原文地址：http://www.cnblogs.com/hustercn/p/6854595.html
