import socketserver
import re
from dateutil import parser
import os
import sqlite3
# facility与ID的对应关系的字典，方便后续分词时提取对应的信息
facility_dict = {0: 'KERN',
1: 'USER',
2: 'MAIL',
3: 'DAEMON',
4: 'AUTH',
5: 'SYSLOG',
6: 'LPR',
7: 'NEWS',
8: 'UUCP',
9: 'CRON',
10: 'AUTHPRIV',
11: 'FTP',
16: 'LOCAL0',
17: 'LOCAL1',
18: 'LOCAL2',
19: 'LOCAL3',
20: 'LOCAL4',
21: 'LOCAL5',
22: 'LOCAL6',
23: 'LOCAL7'}
# severity_level与ID的对应关系的字典，方便后续分词时提取对应的信息
severity_level_dict = {0: 'EMERG',
1: 'ALERT',
2: 'CRIT',
3: 'ERR',
4: 'WARNING',
5: 'NOTICE',
6: 'INFO',
7: 'DEBUG'}
# 分词处理的类
class SyslogUDPHandler(socketserver.BaseRequestHandler):
def handle(self):
data = bytes.decode(self.request[0].strip()) # 读取数据
# print(data)
syslog_info_dict = {'device_ip': self.client_address[0]}
try:
# syslog信息如下：187>83: *Apr 4 00:03:12.969: %LINK-3-UPDOWN: Interface GigabitEthernet2,
# changed state to up，我们需要对此进行提炼分词，并将分词结果记入到一个字典里面；具体的分词过程简单了解即可
syslog_info = re.match(r'^(\d*)>(\d*): \*(.*): %(\w+)-(\d)-(\w+): (.*)', str(data)).groups()
# print(syslog_info[0]) 提取为整数 例如 185
# 185 二进制为 1011 1001
# 前5位为facility >> 3 获取前5位
# 后3位为severity_level 0b111 获取后3位
syslog_info_dict['facility'] = (int(syslog_info[0]) >> 3)
syslog_info_dict['facility_name'] = facility_dict[int(syslog_info[0]) >> 3]
syslog_info_dict['logid'] = int(syslog_info[1])
syslog_info_dict['time'] = parser.parse(syslog_info[2])
syslog_info_dict['log_source'] = syslog_info[3]
syslog_info_dict['severity_level'] = int(syslog_info[4])
syslog_info_dict['severity_level_name'] = severity_level_dict[int(syslog_info[4])]
syslog_info_dict['description'] = syslog_info[5]
syslog_info_dict['text'] = syslog_info[6]
except AttributeError:
# 有些日志会缺失%SYS-5-CONFIG_I, 造成第一个正则表达式无法匹配 , 也无法提取severity_level
# 下面的icmp的debug就是示例
# 191>91: *Apr 4 00:12:29.616: ICMP: echo reply rcvd, src 10.1.1.80, dst 10.1.1.253, topology BASE, dscp 0 topoid 0
syslog_info = re.match(r'^(\d*)>(\d*): \*(.*): (\w+): (.*)', str(data)).groups()
print(syslog_info[0])
syslog_info_dict['facility'] = (int(syslog_info[0]) >> 3)
syslog_info_dict['facility_name'] = facility_dict[int(syslog_info[0]) >> 3]
syslog_info_dict['logid'] = int(syslog_info[1])
syslog_info_dict['time'] = parser.parse(syslog_info[2])
syslog_info_dict['log_source'] = syslog_info[3]
# 如果在文本部分解析不了severity_level, 切换到syslog_info[0]去获取
# 185 二进制为 1011 1001
# 前5位为facility >> 3 获取前5位
# 后3位为severity_level 0b111 获取后3位
syslog_info_dict['severity_level'] = (int(syslog_info[0]) 0b111)
syslog_info_dict['severity_level_name'] = severity_level_dict[(int(syslog_info[0]) 0b111)]
syslog_info_dict['description'] = 'N/A'
syslog_info_dict['text'] = syslog_info[4]
# print(syslog_info_dict)
# 根据分词后的字典进行分析，如果用正则表达式匹配到了OSPF状态有了改变，则打印告警信息
if syslog_info_dict['log_source'] == 'OSPF':
result_ospf = re.findall('(Process \d+), Nbr ([0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3}).+to (\w+)', syslog_info_dict['text'])[0]
if result_ospf:
print('OSPF '+result_ospf[0]+' Neighbor '+result_ospf[1]+' status '+result_ospf[2])
# 将字典信息写入sqlite数据库中
conn = sqlite3.connect(gl_dbname)
cursor = conn.cursor()
cursor.execute("insert into syslogdb (time, \
device_ip, \
facility, \
facility_name, \
severity_level, \
severity_level_name, \
logid, \
log_source, \
description, \
text) values ('%s', '%s', %d, '%s', %d, '%s', %d, '%s', '%s', '%s')" % (
syslog_info_dict['time'].strftime("%Y-%m-%d %H:%M:%S"),
syslog_info_dict['device_ip'],
syslog_info_dict['facility'],
syslog_info_dict['facility_name'],
syslog_info_dict['severity_level'],
syslog_info_dict['severity_level_name'],
syslog_info_dict['logid'],
syslog_info_dict['log_source'],
syslog_info_dict['description'],
syslog_info_dict['text'],
))
conn.commit()
if __name__ == "__main__":
# 使用Linux解释器 WIN解释器
global gl_dbname
gl_dbname = 'syslog.sqlite'
if os.path.exists(gl_dbname):
os.remove(gl_dbname)
# 连接数据库
conn = sqlite3.connect(gl_dbname)
cursor = conn.cursor()
# 创建数据库
cursor.execute("create table syslogdb(id INTEGER PRIMARY KEY AUTOINCREMENT,\
time varchar(64), \
device_ip varchar(32),\
facility int,\
facility_name varchar(32),\
severity_level int,\
severity_level_name varchar(32),\
logid int,\
log_source varchar(32), \
description varchar(128), \
text varchar(1024)\
)")
conn.commit()
try:
HOST, PORT = "0.0.0.0", 514 # 本地地址与端口
server = socketserver.UDPServer((HOST, PORT), SyslogUDPHandler) # 绑定本地地址，端口和syslog处理方法
print("Syslog 服务已启用, 写入日志到数据库!!!")
server.serve_forever(poll_interval=0.5) # 运行服务器，和轮询间隔
except (IOError, SystemExit):
raise
except KeyboardInterrupt: # 捕获Ctrl+C，打印信息并退出
print("Crtl+C Pressed. Shutting down.")
finally:
conn.commit()
import sqlite3
from matplotlib import pyplot as plt
from syslog_server_to_db import severity_level_dict
# 绘制严重等级的饼图
def syslog_show_error_level_pie(dbname):
# 连接数据库
conn = sqlite3.connect(dbname)
cursor = conn.cursor()
# 提取安全级别和数量信息
cursor.execute("select severity_level as level,COUNT(*) as count from syslogdb group by severity_level")
yourresults = cursor.fetchall()
level_list = []
count_list = []
# 把结果写入leve_list和count_list的列表
for level_info in yourresults:
level_list.append(severity_level_dict[level_info[0]])
count_list.append(level_info[1])
print(level_list)
print([float(count) for count in count_list])
plt.rcParams['font.sans-serif'] = ['SimHei'] # 设置中文
# 调节图形大小，宽，高
plt.figure(figsize=(6, 6))
# 使用count_list的比例来绘制饼图
# 使用level_list作为注释
patches, l_text, p_text = plt.pie(count_list,
labels=level_list,
labeldistance=1.1,
autopct='%3.1f%%',
shadow=False,
startangle=90,
pctdistance=0.6)
# 改变文本的大小
# 方法是把每一个text遍历。调用set_size方法设置它的属性
for t in l_text:
t.set_size = 30
for t in p_text:
t.set_size = 20
# 设置x，y轴刻度一致，这样饼图才能是圆的
plt.axis('equal')
plt.title('SYSLOG严重级别分布图') # 主题
plt.legend()
plt.show()
# 绘制Syslog来源的饼图
def syslog_show_source_pie(dbname):
# 连接数据库
conn = sqlite3.connect(dbname)
cursor = conn.cursor()
# 提取log源与其对应的数量
cursor.execute("select log_source,COUNT(*) as count from syslogdb group by log_source")
yourresults = cursor.fetchall()
source_list = []
count_list = []
# 将数据库的信息，依次写入两个列表
for source_info in yourresults:
source_list.append(source_info[0])
count_list.append(source_info[1])
print(source_list)
print([float(count) for count in count_list])
plt.rcParams['font.sans-serif'] = ['SimHei'] # 设置中文
# 调节图形大小，宽，高
plt.figure(figsize=(6, 6))
# 使用count_list的比例来绘制饼图
# 使用level_list作为注释
patches, l_text, p_text = plt.pie(count_list,
labels=source_list,
labeldistance=1.1,
autopct='%3.1f%%',
shadow=False,
startangle=90,
pctdistance=0.6)
# 改变文本的大小
# 方法是把每一个text遍历。调用set_size方法设置它的属性
for t in l_text:
t.set_size = 30
for t in p_text:
t.set_size = 20
# 设置x，y轴刻度一致，这样饼图才能是圆的
plt.axis('equal')
plt.title('日志源分布图') # 主题
plt.legend()
plt.show()
if __name__ == '__main__':
syslog_show_error_level_pie("syslog.sqlite")
syslog_show_source_pie("syslog.sqlite")
到此这篇关于使用Python对Syslog信息进行分析并绘图的实现的文章就介绍到这了,更多相关Python Syslog分析 内容请搜索脚本之家以前的文章或继续浏览下面的相关文章希望大家以后多多支持脚本之家！
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