I’m publishing my pdf-parser tool featured in my last video. Details and download here.
Thursday 30 October 2008
Thursday 23 October 2008
Excel Exercises in Style
I developed another variant of my “Excel macro injects embedded DLL” script.
In stead of creating and loading a temporary DLL from VBScript, I inject and execute shellcode directly from the VBA application.
Some HIPS would prevent my previous script from running, because it loaded an unapproved DLL. But my new version doesn’t load a DLL.
Of course, writing shellcode is more difficult than developing a PE executable.
Tuesday 21 October 2008
The Case of the Corrupted Stream Object
A malicious PDF file I analyzed a couple of months ago (the one featured in this video) had a corrupted stream object. It uses a /FlateDecode filter, but I could not find a way to decompress it with the zlib library. Back then, I wrote it off as an error of the malware author.
Lately, I’ve been analyzing some shellcode, and while looking at the shellcode in said malicious PDF, I saw it! The second-stage shellcode, a egghunt shellcode, is searching through process memory for the 8 bytes at the beginning of the corrupted stream object.
The malware author knows that the PDF reader loads the PDF document in memory, so he just overwrote the stream object with his third-stage shellcode. This way, his third-stage shellcode is already in memory, waiting to be found by his second-stage shellcode. And the size of his third-stage shellcode is not limited by the buffer he is overflowing.
Monday 20 October 2008
Analyzing a Malicious PDF File
This starts a series of post leading up to my PDF talk at the next Belgian ISSA and OWASP chapter event. I’ll be publishing a couple of my PDF tools.
Next video shows how I use my PDF parser to analyze a malicious PDF file, and extract the shell code.
Searching for keyword javascript yields 2 indirect objects referencing /JavaScript objects. The JavaScript is executed through an automatic annotation (/AA) when the page is rendered (e.g. when the PDF document is opened, as it contains only one page). Decompressing the second /JavaScript object (34) displays the code.
collectEmailInfo is an undocument Adobe Acrobat JavaScript method with a vulnerability (fixed in Adobe Acrobat Reader 8.1.2). My Spidermonkey helps me to extract the shell code.
YouTube, Vimeo and hires Xvid.
Thursday 9 October 2008
Quickpost: Another E-card Malware Spam Campaign
Another e-card e-mail is being spammed right now
Subject: You have received an eCard
Spoofed sender: 123Greetings.com
MD5 51c2c1e82bc8c89dd831494689341147
Monday 6 October 2008
Forensic Time Dilatation
When you compile a forensic report, it’s crucial to report facts objectively and avoid potential misinterpretation.
Although this statement shouldn’t be a surprise to you, sometimes, the devil is in the details.
Take the electronic purse (EP) in use in many European countries (Proton, Chipknip, …). These EP systems are based on ATM smart cards and are used to pay small amounts. A main advantage of these cards is that terminals performing EP debit transactions don’t require a network connection to check the purse owner’s credit or credentials. The debit transactions are self-contained and protected by cryptographic protocols.
The EP also supports a couple of simple unencrypted commands to read the balance of the EP and list the last transactions. When you send the EP an APDU to get the last transaction (0xE1, 0xB6, 0x00, 0x01, 0x24), it will reply with a binary record of 36 bytes. 2 bytes in this record are used to encode the timestamp of the transaction using the following format:
4 bits I called M are used to encode the month (0-15).
5 bits D are used to encode the day (0-32).
The year the transaction took place is not documented.
7 bits T are used to encode the time the transaction occurred (0-127). 128 possible values is by no means enough to encode the time with a precision of 1 second (86400 possible values). The resolution of the EP timestamp is 675 seconds long (that’s 11 minutes and 15 seconds).
And herein lies the difficulty to print timestamps in a forensic report. I came across a forensic tool (TULP2G) that gets it wrong. TULP2G will print the above timestamp in its forensic report like this:
24/09 11:37:30
Can you spot the error? If the time is encoded with units covering a period of 675 seconds (i.e. an error margin of 675 seconds), you cannot print the time in a forensic report in HH:MM:SS format without any indication that the represented value is not precise up to the second! Because there will always be people reading your report that have no notion of the (in)accuracy of the EP timestamp, and they will interpret the timestamp like you wrote it: 11 hours, 37 minutes and 30 seconds precisely. According to the cash register ticket, I bought my lunch at 11:44, not at 11:37:30.
If you print timestamps in a forensic report, think about the resolution of the values you’re representing. If you use the HH:MM:SS time-format to represent a value that is measured in units longer than 1 second, add a qualification to each printed timestamp to indicate this.
You can add a footnote explaining the error margin, use the scientific error notation, …
For example, write 24/09 11:37:30 ± 675s.
Personally, I would write 24/09 11:37:30 + 675s – 1s (1), because I’ve observed only terminals that seem to perform an integer division: current time expressed in seconds / 675. (1) refers to a footnote explaining the resolution of the timestamp. But this is in all likelihood too confusing.
Your takeaway: if you compile or interpret forensic reports, take particular care to avoid the pitfalls of timestamps. Take into account desynchronized clocks, clock drift, time-zones and time unit resolution.
I contacted the author of the TULP2G software, but got no reply. If you’ve contacts inside the NFI, please inform them of my opinion.
Didier Stevens 