腳本一：監(jiān)控CSR1000v發(fā)送的Syslog Trap信息，并對信息進(jìn)行分詞處理，寫入數(shù)據(jù)庫。同時監(jiān)控OSPF鄰居狀態(tài)是否改變。
import socketserver
import re
from dateutil import parser
import os
import sqlite3
# facility與ID的對應(yīng)關(guān)系的字典，方便后續(xù)分詞時提取對應(yīng)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(yīng)關(guān)系的字典，方便后續(xù)分詞時提取對應(yīng)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(shù)據(jù)
# 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(jìn)行提煉分詞，并將分詞結(jié)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(shù) 例如 185
# 185 二進(jìn)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(dá)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(jìn)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(jù)分詞后的字典進(jìn)行分析，如果用正則表達(dá)式匹配到了OSPF狀態(tài)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(shù)據(jù)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(shù)據(jù)庫
conn = sqlite3.connect(gl_dbname)
cursor = conn.cursor()
# 創(chuàng)建數(shù)據(jù)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(wù)已啟用, 寫入日志到數(shù)據(jù)庫!!!")
server.serve_forever(poll_interval=0.5) # 運(yùn)行服務(wù)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(yán)重等級的餅圖
def syslog_show_error_level_pie(dbname):
# 連接數(shù)據(jù)庫
conn = sqlite3.connect(dbname)
cursor = conn.cursor()
# 提取安全級別和數(shù)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(jié)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(shè)置中文
# 調(diào)節(jié)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(diào)用set_size方法設(shè)置它的屬性
for t in l_text:
t.set_size = 30
for t in p_text:
t.set_size = 20
# 設(shè)置x，y軸刻度一致，這樣餅圖才能是圓的
plt.axis('equal')
plt.title('SYSLOG嚴(yán)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(shù)據(jù)庫
conn = sqlite3.connect(dbname)
cursor = conn.cursor()
# 提取log源與其對應(yīng)的數(shù)量
cursor.execute("select log_source,COUNT(*) as count from syslogdb group by log_source")
yourresults = cursor.fetchall()
source_list = []
count_list = []
# 將數(shù)據(jù)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(shè)置中文
# 調(diào)節(jié)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(diào)用set_size方法設(shè)置它的屬性
for t in l_text:
t.set_size = 30
for t in p_text:
t.set_size = 20
# 設(shè)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(guān)于使用Python對Syslog信息進(jìn)行分析并繪圖的實(shí)現(xiàn)的文章就介紹到這了,更多相關(guān)Python Syslog分析 內(nèi)容請搜索腳本之家以前的文章或繼續(xù)瀏覽下面的相關(guān)文章希望大家以后多多支持腳本之家！
