Skip to main content

SQL Injection security flaw in OpenEMR medical records system.

I recently examined a popular open source medical records system named OpenEMR. A quick review of the app uncovered a SQL Injection vulnerability in the application, that would allow an attacker to execute their own SQL commands against the system. The attack is relatively textbook and its detection and exploitation are outlined below. Firstly, a description of the product:
Profile: OpenEMR is a medical practice management software which also supports Electronic Medical Records (EMR). It is ONC Complete Ambulatory EHR certified and it features fully integrated electronic medical records, practice management for a medical practice, scheduling and electronic billing.

The server side is written in PHP and can be employed in conjunction with a LAMP "stack", though any operating systems with PHP-support are also supported.
...
In the US, it has been estimated that there are more than 5,000 installations of OpenEMR in physician offices and other small healthcare facilities serving more than 30 million patients. Internationally, it has been estimated that OpenEMR is installed in over 15,000 healthcare facilities, translating into more than 45,000 practitioners using the system which are serving greater than 90 million patients.


Source: Wikipedia: http://en.wikipedia.org/wiki/OpenEMR
Affected versions: OpenEMR 4.1.2 Patch 5 (and likely previous patches & releases)
Fix in: OpenEMR 4.1.2 Patch 6 

As usual I reviewed the system as a user, browsing features and recording my actions in my intercepting proxy (BurpSuite). This gave me a good idea of the default system features and usage model. Combined with review through the online documentation, I gained a broad idea of how the system is used and its features or ‘claims’.

The latest/patched code was relatively well protected against SQL Injection, with widespread use of prepared statements, a good defence against 1st order SQL Injection. But, I noticed a few queries were not parameterised. While this is not necessarily a problem, if its possible to include custom inputs into the query, then vulnerabilities can creep in.

In this case, the affected query was a delete for ‘Patient Disclosures’. When the user opts to delete a Disclosure record via the user interface the system runs this query, inserting the record identifier sent via the browser.

Unfortunately, the Open EMR system does not filter out inappropriate characters for these requests, meaning SQL can be written unmodified into the request. As long as the SQL, when combined with the remainder of the query is valid syntactically, the query is then executed. If code had restricted the input to be, for example positive integers, then this vulnerability would be largely mitigated.

You can see the vulnerable code here:

File: openemr-4.1.2/library/log.inc
function deleteDisclosure($deletelid)

{

       $sql="delete from extended_log where id='$deletelid'";

       $ret = sqlInsertClean_audit($sql);

}

As you can see the ID string is just included directly into the string used for the query.

As a proof of concept, I wrote a simple SQL extract that when injected produces a valid but nefarious query. In this case, the query deletes all Patient Disclosures.

The malicious Request URL might look like this (the malicious characters in red):

http://youropenemrserver/openemr/interface/patient_file/summary/disclosure_full.php?deletelid=5%27%20OR%20%271%27=%271

The active code inserted is:
' OR '1'='1

This generates a SQL query like this:
delete from extended_log where id='5' OR '1'='1'

The addition ensures every item in the table is deleted. Not only those with an id of 5. Other injections are of course possible, this one was chosen because its a simple demonstration of SQL Injection. Typically an attacker would try to extract user credentials, or confidential information  - in this case possibly patient medical records.

One positive aspect of the flaw is that it is not pre-auth. So the attack only works when the attacker/exploit code has access to a valid logged-in session. This makes it slightly harder to exploit, but not overly so as an attacker can use methods such as Cross Site Request Forgery to initiate ‘blind’ attacks from another browser tab. But in summary, if OpenEMR is deployed only on a local network this issue is not severe.

Note: I reported this issue in a process of responsible disclosure on a 30 day embargo. (That expired 5 days before a patch was released and 9 days before this post.  

The patch was released on the 8th June 2014 and is meant to address this issue and others. (Look for the fixes from Brady Miller to log.inc). I have not tested this fix.

Comments

Popular posts from this blog

Can Gen-AI understand Payments?

When it comes to rolling out updates to large complex banking systems, things can get messy quickly. Of course, the holy grail is to have each subsystem work well independently and to do some form of Pact or contract testing – reducing the complex and painful integration work. But nonetheless – at some point you are going to need to see if the dog and the pony can do their show together – and its generally better to do that in a way that doesn’t make millions of pounds of transactions fail – in a highly public manner, in production.  (This post is based on my recent lightning talk at  PyData London ) For the last few years, I’ve worked in the world of high value, real time and cross border payments, And one of the sticking points in bank [software] integration is message generation. A lot of time is spent dreaming up and creating those messages, then maintaining what you have just built. The world of payments runs on messages, these days they are often XML messages – and they ...

What possible use could Gen AI be to me? (Part 1)

There’s a great scene in the Simpsons where the Monorail salesman comes to town and everyone (except Lisa of course) is quickly entranced by Monorail fever… He has an answer for every question and guess what? The Monorail will solve all the problems… somehow. The hype around Generative AI can seem a bit like that, and like Monorail-guy the sales-guy’s assure you Gen AI will solve all your problems - but can be pretty vague on the “how” part of the answer. So I’m going to provide a few short guides into how Generative (& other forms of AI) Artificial Intelligence can help you and your team. I’ll pitch the technical level differently for each one, and we’ll start with something fairly not technical: Custom Chatbots. ChatBots these days have evolved from the crude web sales tools of ten years ago, designed to hoover up leads for the sales team. They can now provide informative answers to questions based on documents or websites. If we take the most famous: Chat GPT 4. If we ignore the...

Manumation, the worst best practice.

There is a pattern I see with many clients, often enough that I sought out a word to describe it: Manumation, A sort of well-meaning automation that usually requires frequent, extensive and expensive intervention to keep it 'working'. You have probably seen it, the build server that needs a prod and a restart 'when things get a bit busy'. Or a deployment tool that, 'gets confused' and a 'test suite' that just needs another run or three. The cause can be any number of the usual suspects - a corporate standard tool warped 5 ways to make it fit what your team needs. A one-off script 'that manager' decided was an investment and needed to be re-used... A well-intended attempt to 'automate all the things' that achieved the opposite. They result in a manually intensive - automated process, where your team is like a character in the movie Metropolis, fighting with levers all day, just to keep the lights on upstairs. Manual-automation, manu...