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kitploitKitPloitKITPLOIT:4761268611976240701
HistoryOct 20, 2020 - 11:30 a.m.

PatchChecker - Web-based Check For Windows Privesc Vulnerabilities

2020-10-2011:30:00
www.kitploit.com
212

7.8 High

CVSS3

Attack Vector

LOCAL

Attack Complexity

LOW

Privileges Required

LOW

User Interaction

NONE

Scope

UNCHANGED

Confidentiality Impact

HIGH

Integrity Impact

HIGH

Availability Impact

HIGH

CVSS:3.0/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H

7.7 High

AI Score

Confidence

High

7.2 High

CVSS2

Access Vector

LOCAL

Access Complexity

LOW

Authentication

NONE

Confidentiality Impact

COMPLETE

Integrity Impact

COMPLETE

Availability Impact

COMPLETE

AV:L/AC:L/Au:N/C:C/I:C/A:C

0.888 High

EPSS

Percentile

98.7%

This is the code base for the service running on: <https://patchchecker.com>. In short, PatchChecker is a web application (running on flask) that provides output similar to that of Watson. However by using PatchChecker, one is not required to execute a binary on the target machine. Included in this project is also a web scraper that will automatically update the database for PatchChecker using information present on Microsoft sites, this allows for a more scalable and easier to use solution to the problem of finding CVEs to which a Windows system is (or is not) patched against. Additionally, any other CVEs can be added to the data collector input and checked for as long as they have an entry on <https://portal.msrc.microsoft.com>. You can also use this to get the data to update Watson.

Further information about this project can be found here or here (github.io mirror).

Using PatchChecker to check vulnerabilities:

To use the patchchecker, you can either go to the publicly hosted website here at patchchecker.com or you can git clone this repo, install the required libraries, makes sure patches.db is in the same directory as app.py and then start the application with python3 ./app.py. Once the application is started you can open the included “index.html” file in a browser to actually use the service and get the list of patches to which the system being tested is vulnerable.
Additional information can be found here.

Getting KB data:

Expected input:

Expected output from webpage:

Expected output from webpage when vulnerabilities are found:

Alternatively, you can use a curl command and do something like this: Request:
note: you can use any delimiter you wish, i’m using spaces here:

curl 'https://patchchecker.com/checkprivs/' --data-raw 'wmicinfo=KB1231411 KB1231441 KB1234141&build_num=17763'  

Response:
note: used some fake KBs so it’s showing vuln to everything, i.e. I have nothing installed
note: output is trunctated

{  
    "total_vuln": 9,  
    "kbs_parsed": [  
        "KB1231411",  
        "KB1231441",  
        "KB1234141"  
    ],  
    "total_kbs_parsed": 3,  
    "build": "17763",  
    "results": [  
        {  
            "refs": [  
                "https://exploit-db.com/exploits/46718",  
                "https://decoder.cloud/2019/04/29/combinig-luafv-postluafvpostreadwrite-race-condition-pe-with-diaghub-collector-exploit-from-standard-user-to-system/"  
            ],  
            "name": "CVE-2019-0836",  
            "vulnerable": true  
        }  
		]  
}  

To run the code in this repo yourself don’t forget to run: python3 -m pip install -r requirements.txt and run with python3. For reference, I used python 3.7.3.

Data Collection: patchdata_collector.py

The patchdata_collector.py script is the pyppeteer scraper that iterates through several Microsoft sites to get the desired data for the cves specified in the --cve-list arg file. For an example of the expected format see the cves.txt file within the samples directory. Basically it’s a line-separated file with each line containing the following CVE-XXXX-XXXX|https://website.com/resource-pertaining-to-CVE,http://second_resource.com you get the idea. An example of the resulting output can be found in the patches.db file included.
The code isn’t perfect but it gets the data and works for the time being. As refernce, with 9 CVEs, it should take about 11 minutes to complete, YMMV.

patchdata_collector.py usage:

usage: patchdata_collector.py [-h] --cve-list CVE_LIST [--db DB] [--new-db] [-v]  
                          [-vv] [--no-headless] [--json JSON]  
  
optional arguments:  
  -h, --help           show this help message and exit  
  --cve-list CVE_LIST  line and pipe separated list containing CVEs and  
                       related-URLs with information example: CVE-2020-1048|https://github.com/ionescu007/faxhell,https://github.com/ionescu007/PrintDemon  
  --db DB              sqlite database filename  
  --new-db             erases old database (if exists)  
  -v                   set output to debug (verbose)  
  -vv                  set output to annoying  
  --no-headless        run browser with headless mode disabled  
  --json JSON          json format output, argument should be json filename  

Example run:

Running time ./patchdata_collector.py --cve-list cves.txt --db antest.db --new-db yields the following output:

2020-06-05 20:38:49.292 | INFO     | __main__:main:181 - Loaded 10 CVEs  
2020-06-05 20:38:49.430 | INFO     | __main__:parsekb:33 - Parsing KBs for: CVE-2019-0836  
2020-06-05 20:40:27.183 | INFO     | __main__:parsekb:33 - Parsing KBs for: CVE-2019-1064  
2020-06-05 20:41:07.158 | INFO     | __main__:parsekb:33 - Parsing KBs for: CVE-2019-0841  
2020-06-05 20:41:31.675 | INFO     | __main__:parsekb:33 - Parsing KBs for: CVE-2019-1130  
2020-06-05 20:42:58.527 | INFO     | __main__:parsekb:33 - Parsing KBs for: CVE-2019-1253  
2020-06-05 20:43:25.069 | INFO     | __main__:parsekb:33 - Parsing KBs for: CVE-2019-1315  
2020-06-05 20:44:57.974 | INFO     | __main__:parsekb:33 - Parsing KBs for: CVE-2019-1385  
2020-06-05 20:45:22.026 | INFO     | __main__:parsekb:33 - Parsing KBs for: CVE-2019-1388  
2020-06-05 20:46:48.407 | INFO     | __main__:parsekb:33 - Parsing KBs for: CVE-2019-1405  
2020-06-05 20:48:07.026 | INFO     | __main__:parsekb:33 - Parsin   g KBs for: CVE-2020-1048  
finished  
  
real	11m27.793s  
user	1m21.632s  
sys	0m14.559s  

Download Patch-Checker

7.8 High

CVSS3

Attack Vector

LOCAL

Attack Complexity

LOW

Privileges Required

LOW

User Interaction

NONE

Scope

UNCHANGED

Confidentiality Impact

HIGH

Integrity Impact

HIGH

Availability Impact

HIGH

CVSS:3.0/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H

7.7 High

AI Score

Confidence

High

7.2 High

CVSS2

Access Vector

LOCAL

Access Complexity

LOW

Authentication

NONE

Confidentiality Impact

COMPLETE

Integrity Impact

COMPLETE

Availability Impact

COMPLETE

AV:L/AC:L/Au:N/C:C/I:C/A:C

0.888 High

EPSS

Percentile

98.7%