import socketserver
import re
from dateutil import parser
import os
import sqlite3
# facility與ID的對應關系的字典，方便后續分詞時提取對應的信息
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與ID的對應關系的字典，方便后續分詞時提取對應的信息
severity_level_dict = {0: 'EMERG',
1: 'ALERT',
2: 'CRIT',
3: 'ERR',
4: 'WARNING',
5: 'NOTICE',
6: 'INFO',
7: 'DEBUG'}
# 分詞處理的類
class SyslogUDPHandler(socketserver.BaseRequestHandler):
def handle(self):
data = bytes.decode(self.request[0].strip()) # 讀取數據
# 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，我們需要對此進行提煉分詞，并將分詞結果記入到一個字典里面；具體的分詞過程簡單了解即可
syslog_info = re.match(r'^(\d*)>(\d*): \*(.*): %(\w+)-(\d)-(\w+): (.*)', str(data)).groups()
# print(syslog_info[0]) 提取為整數 例如 185
# 185 二進制為 1011 1001
# 前5位為facility >> 3 獲取前5位
# 后3位為severity_level 0b111 獲取后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:
# 有些日志會缺失%SYS-5-CONFIG_I, 造成第一個正則表達式無法匹配 , 也無法提取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, 切換到syslog_info[0]去獲取
# 185 二進制為 1011 1001
# 前5位為facility >> 3 獲取前5位
# 后3位為severity_level 0b111 獲取后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)
# 根據分詞后的字典進行分析，如果用正則表達式匹配到了OSPF狀態有了改變，則打印告警信息
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])
# 將字典信息寫入sqlite數據庫中
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解釋器 WIN解釋器
global gl_dbname
gl_dbname = 'syslog.sqlite'
if os.path.exists(gl_dbname):
os.remove(gl_dbname)
# 連接數據庫
conn = sqlite3.connect(gl_dbname)
cursor = conn.cursor()
# 創建數據庫
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 # 本地地址與端口
server = socketserver.UDPServer((HOST, PORT), SyslogUDPHandler) # 綁定本地地址，端口和syslog處理方法
print("Syslog 服務已啟用, 寫入日志到數據庫!!!")
server.serve_forever(poll_interval=0.5) # 運行服務器，和輪詢間隔
except (IOError, SystemExit):
raise
except KeyboardInterrupt: # 捕獲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
# 繪制嚴重等級的餅圖
def syslog_show_error_level_pie(dbname):
# 連接數據庫
conn = sqlite3.connect(dbname)
cursor = conn.cursor()
# 提取安全級別和數量信息
cursor.execute("select severity_level as level,COUNT(*) as count from syslogdb group by severity_level")
yourresults = cursor.fetchall()
level_list = []
count_list = []
# 把結果寫入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'] # 設置中文
# 調節圖形大小，寬，高
plt.figure(figsize=(6, 6))
# 使用count_list的比例來繪制餅圖
# 使用level_list作為注釋
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)
# 改變文本的大小
# 方法是把每一個text遍歷。調用set_size方法設置它的屬性
for t in l_text:
t.set_size = 30
for t in p_text:
t.set_size = 20
# 設置x，y軸刻度一致，這樣餅圖才能是圓的
plt.axis('equal')
plt.title('SYSLOG嚴重級別分布圖') # 主題
plt.legend()
plt.show()
# 繪制Syslog來源的餅圖
def syslog_show_source_pie(dbname):
# 連接數據庫
conn = sqlite3.connect(dbname)
cursor = conn.cursor()
# 提取log源與其對應的數量
cursor.execute("select log_source,COUNT(*) as count from syslogdb group by log_source")
yourresults = cursor.fetchall()
source_list = []
count_list = []
# 將數據庫的信息，依次寫入兩個列表
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'] # 設置中文
# 調節圖形大小，寬，高
plt.figure(figsize=(6, 6))
# 使用count_list的比例來繪制餅圖
# 使用level_list作為注釋
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)
# 改變文本的大小
# 方法是把每一個text遍歷。調用set_size方法設置它的屬性
for t in l_text:
t.set_size = 30
for t in p_text:
t.set_size = 20
# 設置x，y軸刻度一致，這樣餅圖才能是圓的
plt.axis('equal')
plt.title('日志源分布圖') # 主題
plt.legend()
plt.show()
if __name__ == '__main__':
syslog_show_error_level_pie("syslog.sqlite")
syslog_show_source_pie("syslog.sqlite")
到此這篇關于使用Python對Syslog信息進行分析并繪圖的實現的文章就介紹到這了,更多相關Python Syslog分析 內容請搜索腳本之家以前的文章或繼續瀏覽下面的相關文章希望大家以后多多支持腳本之家！
