Detecting hard-coded user names in ABAP


Hello everybody!

A few months passed since my last post, so it’s about time for new one! 💡

User names in conditional expressions

Lock your backdoor

The system field SY-UNAME contains the name of the currently logged-on user and is quite frequently used by developers to facilitate tests by adding special conditions to their code. The block of code that is executed depending on the current user’s name is usually only intended for the developer him-/herself.

Although developer guidelines almost always include the obligation to make use of AUTHORITY-CHECKs, these checks might interfere with functional tests – and people might want to circumvent them (just for the tests, of course). No matter what the intention was, this approach leads to programs that do authorization checks for all users – except for the developer of the code… bad thing!
The following code snippet is probably one of the most prominent examples:

IF sy-uname NE 'DEVELOPER'.
    AUTHORITY-CHECK ...
ENDIF.

Right after the successful test phase, the code is transported to production and the conditional code might never be made universal…
If we consider malicious behavior, such code is called a backdoor and/or hidden function and this means that there is a need for action (at least to protect your developer colleagues)!

How to detect it

To find affected code, the SAP standard report RS_ABAP_SOURCE_SCAN is of great help — you can use it to search for plain strings or expressions in reports, classes, etc.
Since we’re interested in IF conditions that check the value of SY-UNAME, I’d suggest to search using “IF .*sy-uname” as the expression and tick the checkbox “String is standard expression“.
In the sample below, I limited the search to programs with name Z*, but you might probably want to adjust this according to your needs (e.g. your registered namespaces).

Search for hard-coded user names in ABAP

The result shows two different conditions that use SY-UNAME in a possibly evil way:

Sample result showing hard-coded user name checks

Detection gaps

The search expression above is rather straight forward…
Unfortunately, it can be tricked easily by a developer, who knows it:

DATA: foobar TYPE syuname.
foobar = sy-uname.
 
* Obfuscated condition
IF foobar NE 'MYSELF'.
    AUTHORITY-CHECK ...
ENDIF.

So – when you establish controls to prevent the usage of user-based conditions, this is something to keep in mind.
Humans are usually better at detecting fuzzy patterns that computers are… 😎

Countermeasures

Code that is bypassed based on the value of SY-UNAME should never be used!

➡ All instances of hard-coded user names in customer code used on productive systems should be corrected.
➡ Controls should be established to prevent such code from being transported.
You might want to integrate the use of the SAP code inspector into your transport process.

See ya!

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Mastering S_RFC authorizations // Part 2


Hello again.

After a relaxing summer holiday, it’s time to fulfill the promise I made in my last post and provide the evaluation report for our log of RFC calls.
If you don’t know what I’m talking about, please read the first part of this article.

Evaluation report

This report basically parses the RFC log and shows the function groups that would’ve been required to execute the called modules.
In addition, it finds out, whether the respective users currently have the required S_RFC authorization — therefore, it allows you to focus on those entries, where the authorization is missing.

Installation:

  • Create a new program in SE38 and copy-paste this source code.
  • Set a program authorization group in the attributes section.
  • Activate the program & execute it.

Usage

The selection screen should be rather self-explanatory:

Selection screen of report ZS_STAD_EXTRACT_RFC_CALLS

There is only one noteworthy feature: the “Client” field is pre-filled with all clients, for which no RFC connection could be determined automatically. The report checks the logical systems for all local SAP clients and tries to reach them via the assigned RFC connection (that should normally work in a well-configured system :wink:). If this attempt fails, the respective client is excluded from the evaluation. Just log on to the excluded client(s) and run the report locally – this will always work!

The screenshot below shows an exemplary result. All lines with function groups, for which authorizations exist, are hidden per default; to unhide them, just remove the filter (marked in red below).

Result list of report ZS_STAD_EXTRACT_RFC_CALLS

The icons in the “Auth. check” column have the following meaning:

Icon: User is authorized » User has the required authorization — filtered out per default
Icon: User is not authorized » S_RFC authorization is missing — this is what we’re interested in
Icon: User is locked » User is locked
Icon: User does not exist » User does not currently exist

Ciao!

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Mastering S_RFC authorizations // Part 1


Hi!

Mastering S_RFC authorizations

In this article, I’ll show you a handy way of identifying the S_RFC authorizations your users need; this method helped me a lot recently.

Generally, you might be interested in this topic, because…

  • … you were asked to raise the value of profile parameter
    auth/rfc_authority_check from zero to a greater value
  • … you need a practical approach to improve your S_RFC authorizations
  • … you updated your SAP kernel to a patch level ≥ 7.20-400
    or ≥ 7.21-041 (see SAP Note 1785761)

The challenge

The authorization object S_RFC consists of three fields, but only one of them is of interest for us: RFC_NAME – which is checked against the called function module’s group (the other two fields have only one possible value each, so we’ll ignore them here).

I opted for a heuristic approach to determine values for that field… so first we’ll collect a list of function module calls that occur on a productive system. In part 2 of this series, we’ll use that list to determine the affected function groups and derive the required S_RFC values from that.

Unfortunately, this approach assumes that all required RFC calls succeed – so during the analysis phase, S_RFC authorizations have to be (or stay?) oversized to ensure no authorization problems distort the result. I’ll leave it to you, how you deal with that…, but you might want to think about setting the profile parameter auth/rfc_authority_check to zero… danger, Will Robinson! → this has security implementations! 😕

Your options

Obtaining a list of called function modules per user is possible in various ways:

  • the Security Audit Log (tcode SM19/20 » audit class “RFC call”)
  • the Business Transaction Analysis (tcode STAD)
  • if you have another good idea, please leave a comment

Using the Security Audit Log would imply some nasty problems: the log size per day is limited (parameters rsau/max_diskspace/*); all logs generated after that limitation is reached are lost.
The functionality of tcode STAD on the contrary quite exactly matches what we need. Furthermore, there is no need to configure anything, as the statistics are recorded anyway (in fact the profile parameter stat/level has to be set to 1… but that’s the system default). The structure which is used to record the statistics contains a field that holds the called function modules — so another benefit of the latter method is that we don’t have to split a text string (like the one stored in an Audit Log message text, e.g. “Successful RFC Call RFCPING (Function Group = SYST)”).

Solution

I chose the second solution — evaluating statistics from STAD —, because it seems to be smarter, more reliable… and allows me to code a bit! 😉

The next step is to create a new report called ZS_STAD_EXTRACT_RFC_CALLS and copy-paste this source code.

Then you need to set up two new customer tables that hold the data we want to collect.
Go to SE11 and create the tables ZSSTAD_RFC_DATA and ZSSTAD_LASTRUN.
I’d suggest using the following settings in the subsequent steps:

  • Delivery class “A” = application table,
  • Data class “APPL1” = transaction data, transparent tables (in: Technical settings),
  • Size category “0” = up to 100.000 entries (in: Technical settings) and
  • Enhancement category “Can be enhanced (deep)” (menu: ExtrasEnhancement category)
Creation of table ZSSTAD_RFC_DATA

The field definitions can be found in the top comment of the report source code; use them as shown below:

Then please repeat these steps for the second table.

Last but not least you should schedule the report to run every hour — that’s a good value because the runtime of the report stays rather short and there’s no danger of losing data (the retention period for STAD data is usually 48 hours, because the statistics files are written every hour and the parameter stat/max_files determines the number of files kept – 48 per default).

Update 1:
You also might want to increase the profile parameter stat/rfcrec, which determines the maximum number of RFC calls in a session that will be recorded in STAD. The default value of 5 is probably not sufficient for all cases!

Update 2:
Please check SAP Note 1964997 for information on the parameters stat/rfc/distinct and stat/rfc/distinct_depth, which are also relevant. Thanks to Christian Wippermann for pointing me to this!

Functionality

So, what does it do?
The report reads all statistics records since the time it was last started (which is saved in table ZSSTAD_LASTRUN) or — if that table contains no values — the ones in the last hour. The records are filtered for RFC calls (all other record types are discarded) and the called function modules’ groups are determined.
As the last step, this information is saved to table ZSSTAD_RFC_DATA.
It contains:

  • the date (DATUM),
  • SAP client (MANDT),
  • calling user (UNAME),
  • called function module (FUMOD),
  • the respective function group (FUGRP) and
  • the number of calls (NCALL) per line.
Sample contents of table ZSSTAD_RFC_DATA

In the below example, the user SAPJSF called RFCPING 22 times on the 4th of May 2013 in client 000:

The information in this table will later be used to determine the values for S_RFC.

What’s next?

In part 2 of this series, I’ll post a nice evaluation report for the above log…

See you then!

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