ACM Home Page
Please provide us with feedback. Feedback
Pointless tainting?: evaluating the practicality of pointer tainting
Full text PdfPdf (646 KB)
Source
European Conference on Computer Systems archive
Proceedings of the 4th ACM European conference on Computer systems table of contents
Nuremberg, Germany
SESSION: Defending against bad things table of contents
Pages 61-74  
Year of Publication: 2009
ISBN:978-1-60558-482-9
Authors
Asia Slowinska  Vrije Universiteit Amsterdam, Amsterdam, Netherlands
Herbert Bos  Vrije Universiteit Amsterdam and NICTA, Amsterdam, Netherlands
Sponsor
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 24,   Downloads (12 Months): 143,   Citation Count: 0
Additional Information:

abstract   references   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1519065.1519073
What is a DOI?

ABSTRACT

This paper evaluates pointer tainting, an incarnation of Dynamic Information Flow Tracking (DIFT), which has recently become an important technique in system security. Pointer tainting has been used for two main purposes: detection of privacy-breaching malware (e.g., trojan keyloggers obtaining the characters typed by a user), and detection of memory corruption attacks against non-control data (e.g., a buffer overflow that modifies a user's privilege level). In both of these cases the attacker does not modify control data such as stored branch targets, so the control flow of the target program does not change. Phrased differently, in terms of instructions executed, the program behaves 'normally'. As a result, these attacks are exceedingly difficult to detect. Pointer tainting is considered one of the onlymethods for detecting them in unmodified binaries. Unfortunately, almost all of the incarnations of pointer tainting are flawed. In particular, we demonstrate that the application of pointer tainting to the detection of keyloggers and other privacybreaching malware is problematic. We also discuss whether pointer tainting is able to reliably detect memory corruption attacks against non-control data. Pointer tainting generates itself the conditions for false positives. We analyse the problems in detail and investigate various ways to improve the technique. Most have serious drawbacks in that they are either impractical (and incur many false positives still), and/or cripple the technique's ability to detect attacks. In conclusion, we argue that depending on architecture and operating system, pointer tainting may have some value in detecting memory orruption attacks (albeit with false negatives and not on the popular x86 architecture), but it is fundamentally not suitable for automated detecting of privacy-breaching malware such as keyloggers.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
 
2
 
3
 
4
 
5
 
6
S. Chen, K. Pattabiraman, Z. Kalbarczyk, and R. K. Iyer. Formal reasoning of various categories of widely exploited security vulnerabilities using pointer taintedness semantics. In Proc. of IFIP SEC, 2004.
 
7
 
8
9
 
10
 
11
 
12
M. Dalton, H. Kannan, and C. Kozyrakis. Deconstructing hardware architectures for security. In WDDD'06: 5th Annual Workshop on Duplicating, Deconstructing, and Debunking, 2006.
13
 
14
15
 
16
 
17
 
18
J. Giffin, S. Jha, and B. Miller. Efficient context-sensitive intrusion detection. In The 11th Annual Network and Distributed System Security Symposium (NDSS), 2004.
19
 
20
 
21
 
22
J. Newsome and D. Song. Dynamic taint analysis for automatic detection, analysis, and signature generation of exploits on commodity software. In 12th Annual Network and Distributed System Security Symposium (NDSS), 2005.
23
 
24
ProcessLibrary.com. zango.exe. http://www.processlibrary.com/directory/files/zango/.
 
25
 
26
Dan Raywood. Sinowal trojan steals data from around 500,000 cards and accounts. SC Magazine, Oct 2008.
 
27
E. Suh, J. Lee, D. Zhang, and S. Devadas. Secure program execution via dynamic information flow tracking. SIGARCH Comput. Archit. News, 32 (5): 85--96, 2004.
 
28
G. Venkataramani, I. Doudalis, Y. Solihin, and M. Prvulovic. Flexitaint: A programmable accelerator for dynamic taint propagation. In HPCA'08, 2008.
 
29
 
30
H. Yin, Z. Liang, and D. Song. HookFinder: Identifying and understanding malware hooking behaviors. In 15th Annual Network and Distributed System Security Symposium (NDSS'08), 2008.
31

Collaborative Colleagues:
Asia Slowinska: colleagues
Herbert Bos: colleagues