- set, get 이 빈번히 발생되는 데이터 저장시 최적의 성능을 보장하는 NoSQL DB
- 메모리 기반의 오픈소스 No SQL
- Install 링크: http://redis.googlecode.com/
취약점 원문: http://benmmurphy.github.io/blog/2015/06/04/redis-eval-lua-sandbox-escape/
Redis EVAL Lua Sandbox Escape
This shouldn’t pose a threat to users under the trusted Redis security model where only trusted users can connect to the database. However, in real deployments there could be databases that can be accessed by untrusted users. The main deployments that are vulnerable are developers machines, places where redis servers can be reached via SSRF attacks and cloud hosting.
Redis 2.8.21 and 3.0.2 have been released to fix this issue.
Developers machines may be vulnerable because they bind Redis to all interfaces which used to be the default listen directive in the Redis configuration.
Developers may also be vulnerable even if they bind to 127.0.0.1 because Redis is effectively a HTTP server. The first mention of attacking Redis via HTTP I could find is by Nicolas Grégoire where he documents attacking a Redis server on a Facebook property using a SSRF vulnerability.
Because Redis is a HTTP server the same origin policies of browsers will allow any website on the internet to send a POST request to it. When using XHR the body is completely controllable. For example if you run the following in the console of your webbrowser while running wireshark:
var x = new XMLHttpRequest(); x.open("POST", "http://127.0.0.1:6379"); x.send('eval "print(\\"hello\\")" 0\r\n');
In wireshark you will see:
POST / HTTP/1.1 Host: 127.0.0.1:6379 Connection: keep-alive Content-Length: 27 Pragma: no-cache Cache-Control: no-cache Origin: http://www.agarri.fr User-Agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_3) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/42.0.2311.135 Safari/537.36 Content-Type: text/plain;charset=UTF-8 Accept: */* Referer: http://www.agarri.fr/kom/archives/2014/09/11/trying_to_hack_redis_via_http_requests/index.html Accept-Encoding: gzip, deflate Accept-Language: en-US,en;q=0.8 eval "print(\"hello\")" 0 -ERR unknown command 'POST' -ERR unknown command 'Host:' -ERR unknown command 'Connection:' -ERR unknown command 'Content-Length:' -ERR unknown command 'Pragma:' -ERR unknown command 'Cache-Control:' -ERR unknown command 'Origin:' -ERR unknown command 'User-Agent:' -ERR unknown command 'Content-Type:' -ERR unknown command 'Accept:' -ERR unknown command 'Referer:' -ERR unknown command 'Accept-Encoding:' -ERR unknown command 'Accept-Language:' $-1
And in the stdout for Redis you will see:
The attacker is not able to read the response from the server because of the same origin policy. However, this might be worked around by using a DNS rebinding attack. Even with DNS rebinding it might not be possible to read the response because the response is not valid HTTP.
However, reading the response is not necessary because you can package a super generic exploit that checks the result of the redis.call(“INFO”) command and then launches a OS/architecture specific payload.
This is similar to attacking developers except a trusted server is tricked into making a request to the Redis server However, you need a lot of control over the body which might not often be possible depending on how the body is encoded.
Redis Cloud Hosting
This will only effect providers where people running arbitrary code from the Redis process is not part of their threat model. The major players in this area look like they are using sandboxing. For example the pids returned by ‘INFO’ on heroku are very low <10 which indicates they are running the Redis servers in containers. You can already run arbitrary code in containers via dynos on Heroku so running arbitrary code in a Redis container is probably not useful for an attacker. Amazon Elasticcache also looks like it uses linux containers.
Similarily, it looks like Microsoft’s hosted Redis solution runs in an isolated VM. Redis ‘INFO’ returns a virtual os string and it takes ~15 minutes to launch an instance. If MS aren’t running in an isolated VM then the 15 minute startup time is very weird.
This will be a problem if a hosting provider runs a whole bunch of redis processes on the same machine/same VM from different customers without any kind of isolation.
Peter Cawley has found that the loadstring function can be used to load bytecode that is unsafe. He has created three very useful lua exploit primitives that make exploitation easy.
First is a way of reading the Value contained in a TValue struct. This allows reading the pointer value from a lua tagged value. Some pointer values are already public (using tostring) but there doesn’t seem to be a way to get the pointer value for a lua string so this is useful.
Second is a way of reading 8 bytes from an arbitrary memory address.
Third is a way of writing 8 bytes to an arbitrary memory address.
Using the arbitrary memory read it is possible to leak the address of a known C function. From the address of this c-function it is possible to find the base address of the redis-server binary. From this base address it is possible to find pointers to libc/libsystem_c functions and to find the base address of the libc/libsystem_c libraries. From these libraries it is possible to find the addresses of useful exported functions (longjump/system) and ROP gadgets. This technique is similar to pwntools dynelf
The arbitrary memory read is also used to leak an address inside the stack. The lua_State object holds a long_jump variable that references a long_jump buffer that is allocated on the stack. This leaks the stack address which can be useful if you just want to corrupt the stack or the rsp and rip can be overwritten in the longjump buf to directly take control when longjump is called. OSX has no pointer mangling protections so this is quite easy to corrupt.
On linux the rip and rsp (and rbp) values are mangled. However, if you have full read access to the memory you can reverse the secret cookie value to corrupt the values. Also, linux prevents you from longjmp’ing to an invalid stack frame (ie: the heap) but you can longjump to point the stack inside the longjump buffer then pivot the stack into the heap. This is not really necessary if you don’t care about corrupting the stack and crashing the redis process but if you longjump and don’t corrupt the stack then you can resume normal execution of redis after the exploit has finished running.
I have exploits for Linux 64 bit and OSX 64 bit. Both exploits take care to not crash the redis server during successful execution. They will make a call to system() then go back to normal redis execution.
I have run the Linux exploit on the Amazon RHEL Image (PIE enabled) and the Amazon 14.04 Ubuntu Image (no PIE). I believe the exploit will work on most modern Linux 64 bit systems (I suspect it will not work if you compile libc with fomit-frame-pointer but this can be worked around). It does not use any hardcoded addresses from libc or the Redis binary.
The OSX version I have only tested on Yosemite but an earlier version was working on Mavericks and I believe the Yosemite version works on both. This has been tested with two different Redis versions and similarily does not depend on hardcoded address from libsystem_c or the Redis binary. However, it uses addresses from libsystem_c to speed up the exploit.
The best option is to set a strong password on Redis. Systems that are reachable via HTTP without a password are a problem waiting to happen.
It is also possible to rename the EVAL command. If you are not using EVAL this is a good option but you still might be at risk of someone modifying your Redis data via HTTP SSRF attacks.
Upgrading to Redis 2.8.21 and 3.0.2 will also fix this issue but I still strongly recommend using password authentication on Redis systems.