Ofuscación de código utilizando generadores de números pseudoaleatorios

Se describe un nuevo método para la ofuscación de códigos maliciosos que utiliza códigos ya presentes en los sistemas: un generador de números pseudo-aleatorios. Esto también puede verse como una técnica anti-desmontaje y anti-depuración, dependiendo de su despliegue, debido a que el código real no existe hasta su ejecución - que se genera de forma dinámica por el generador de números pseudo-aleatorios. Se han usado xperimentos de todo un año para demostrar que esta técnica de ofuscación es viable para un adversario malicioso con acceso a una gran potencia computacional. 

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Aycock, J. & Friess, N. (2006). Spam zombies from outer space. 15th Annual EICAR Conference, pp. 164–179.
Tiu, V. (2009). Confounded Conficker. Virus Bulletin, March, pp. 7–11.
F-Secure (2009). Calculating the size of the Downadup outbreak. Weblog: News from the Lab, 16 January 2009. Available: http://www.f-secure.com/weblog/archives/00001584.html
Finjan (2009). How a cybergang operates a network of 1.9 million infected computers. Available: http://www.finjan.com/MCRCblog.aspx?EntryId=2237
Porras, P., Saidi, H. & Yegneswaran, V. (2009). An analysis of Conficker’s logic and rendezvous points. SRI International Technical Report. Available: http://mtc.sri.com/Conficker
Riordan, J. & Schneier, B. (1998). Environmental key generation towards clueless agents. Mobile Agents and Security, 1419, pp. 15–24.
EICAR (2006). The anti-virus or anti-malware test file. Available: http://www.eicar.org/anti_virus_test_file.htm
Ferrie, P. (2010). Anti-unpacker tricks. Virus Bulletin, May, pp. 4–9.
Oreans Technology (2009). Code Virtualizer. Available: http://www.oreans.com/codevirtualizer.php
VMPsoft (2009). VMProtect. Available: http://vmpsoft.com/
Debaere, E. & Van Campenhout, J. (1990). Intrepretation and Instruction Path Coprocessing. ACM SIGPLAN Notices, 25(9), pp. 7-9.
Klint, P. (1981). Interpretation techniques. Software – Practice and Experience, 11(9), pp. 963–973.
Kuenning, G. (2007). Mersenne Twist pseudorandom number generator package, version 1.20. Available: http://www.cs.hmc.edu/∼geoff/mtwist.html
Toyofuku, T., Tabata, T. & Sakurai, K. (2005). Program obfuscation scheme using random numbers to complicate control flow. 1st International Workshop on Security in Ubiquitous Computing Systems, 3823, pp. 916-925.
Friess, N., Aycock, J. & Vogt, R. (2008). Black market botnets. Department of Computer Science, University of Calgary 2500 University Drive N.W., Calgary, Alberta, Canada.
Larkin, E. (2007). Storm worm’s virulence may change tactics. Network World, 2. Available: http://www.networkworld.com/news/2007/080207-black-hat-storm-worms-virulence.html
Aycock, J., De Graaf, R. & Jacobson, M. (2006). Anti-disassembly using cryptographic hash functions. Journal in Computer Virology, 2(1), pp. 79–85.
Hemmingsen, R., Aycock, J. & Jacobson, M. (2007). Spam, phishing, and the looming challenge of big botnets. EU Spam Symposium.
White, S. (1989). Covert distributed processing with computer viruses. Advances in Cryptology – CRYPTO ’89 Proceedings, pp. 616– 619, LNCS 435.
Shoch, J. & Hupp, J. (1982). The “worm” programs – early experience with a distributed computation. Communications of the ACM, 25(3), pp. 172–180.
Anderson, D., Cobb, J., Korpela, E., Lebofsky, M. & Werthimer, D. (2002). SETI@home: An experiment in public-resource computing. Communications of the ACM, 45(11), pp. 56–61.
Sharif, M., Lanzi, A., Giffin, J. & Lee, W. (2009). Automatic reverse engineering of malware emulators. IEEE Symposium on Security and Privacy. Georgia Institute of Technology, USA.
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Holz, T., Steiner, M., Dahl, F., Biersack, E. & Freiling, F. (2008). Measurements and mitigation of peer-to-peer-based botnets: A case study on Storm Worm. 1st USENIX Workshop on Large-Scale Exploits and Emergent Threats. Available: https://www.usenix.org/legacy/events/leet08/tech/full_papers/holz/holz.pdf
Sterling, T. (2005). Prosecutors say Dutch suspects hacked 1.5 million computers worldwide. Associated Press. Available: http://www.foxnews.com/story/2005/10/20/dutch-hackers-infected-15-million-computers/
Publication
1
Artículo de revista
Rajab, M., Zarfoss, J., Monrose, F. & Terzis, A. (2007). My botnet is bigger than yours (maybe, better than yours): why size estimates remain challenging. 1st Workshop on Hot Topics in Understanding Botnets (HotBots ’07). Available: https://www.usenix.org/legacy/event/hotbots07/tech/full_papers/rajab/rajab.pdf
application/pdf
Universidad San Ignacio de Loyola
Saber y Hacer
Nunes, Daniel M.
Gutiérrez, Juan M.
https://revistas.usil.edu.pe/index.php/syh/article/view/25
Aycock, John
Español
https://creativecommons.org/licenses/by-nc-sa/4.0/
Saber y Hacer - 2014
Se describe un nuevo método para la ofuscación de códigos maliciosos que utiliza códigos ya presentes en los sistemas: un generador de números pseudo-aleatorios. Esto también puede verse como una técnica anti-desmontaje y anti-depuración, dependiendo de su despliegue, debido a que el código real no existe hasta su ejecución - que se genera de forma dinámica por el generador de números pseudo-aleatorios. Se han usado xperimentos de todo un año para demostrar que esta técnica de ofuscación es viable para un adversario malicioso con acceso a una gran potencia computacional. 
Franklin, J., Paxson, V., Perrig, A. & Savage, S. (2007). An inquiry into the nature and causes of the wealth of Internet miscreants. 14th ACM Conference on Computer and Communications Security (pp. 375-388). New York, New York, United States of America. doi:10.1145/1315245.1315292
Szappanos, G. (2007). Exepacker blacklisting. Virus Bulletin. Available: http://www.virusbtn.com/virusbulletin/archive/2007/10/vb200710-exepacker-blacklisting
Collberg, C., Thomborson, C. & Low, D. (1997). A taxonomy of obfuscating transformations. Technical Report 148. Available: https://researchspace.auckland.ac.nz/bitstream/handle/2292/3491/TR148.pdf
1
We describe a novel method for malicious code obfuscation that uses code already present in systems: a pseudo-random number generator. This can also be seen as an antidisassembly and anti-debugging technique, depending on deploy- ment, because the actual code does not exist until run – it is generated dynamically by the pseudo-random number generator. A year’s worth of experiments are used to demonstrate that this technique is a viable code obfuscation option for a malicious adversary with access to large amounts of computing power.
Obfuscation
pseudo-random
generator
Code obfuscation using pseudo-random number generators
Journal article
https://revistas.usil.edu.pe/index.php/syh/article/download/25/26
2014-12-06T00:00:00Z
2014-12-06T00:00:00Z
2311-7915
2311-7613
https://revistas.usil.edu.pe/index.php/syh/article/view/25
41
54
2014-12-06
institution UNIVERSIDAD SAN IGNACIO DE LOYOLA
thumbnail https://nuevo.metarevistas.org/USIL/logo.png
country_str Perú
collection Saber y Hacer
title Ofuscación de código utilizando generadores de números pseudoaleatorios
spellingShingle Ofuscación de código utilizando generadores de números pseudoaleatorios
Nunes, Daniel M.
Gutiérrez, Juan M.
Aycock, John
Obfuscation
pseudo-random
generator
title_short Ofuscación de código utilizando generadores de números pseudoaleatorios
title_full Ofuscación de código utilizando generadores de números pseudoaleatorios
title_fullStr Ofuscación de código utilizando generadores de números pseudoaleatorios
title_full_unstemmed Ofuscación de código utilizando generadores de números pseudoaleatorios
title_sort ofuscación de código utilizando generadores de números pseudoaleatorios
title_eng Code obfuscation using pseudo-random number generators
description Se describe un nuevo método para la ofuscación de códigos maliciosos que utiliza códigos ya presentes en los sistemas: un generador de números pseudo-aleatorios. Esto también puede verse como una técnica anti-desmontaje y anti-depuración, dependiendo de su despliegue, debido a que el código real no existe hasta su ejecución - que se genera de forma dinámica por el generador de números pseudo-aleatorios. Se han usado xperimentos de todo un año para demostrar que esta técnica de ofuscación es viable para un adversario malicioso con acceso a una gran potencia computacional. 
description_eng We describe a novel method for malicious code obfuscation that uses code already present in systems: a pseudo-random number generator. This can also be seen as an antidisassembly and anti-debugging technique, depending on deploy- ment, because the actual code does not exist until run – it is generated dynamically by the pseudo-random number generator. A year’s worth of experiments are used to demonstrate that this technique is a viable code obfuscation option for a malicious adversary with access to large amounts of computing power.
author Nunes, Daniel M.
Gutiérrez, Juan M.
Aycock, John
author_facet Nunes, Daniel M.
Gutiérrez, Juan M.
Aycock, John
topic Obfuscation
pseudo-random
generator
topic_facet Obfuscation
pseudo-random
generator
citationvolume 1
citationissue 1
publisher Universidad San Ignacio de Loyola
ispartofjournal Saber y Hacer
source https://revistas.usil.edu.pe/index.php/syh/article/view/25
language Español
format Article
rights info:eu-repo/semantics/openAccess
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Saber y Hacer - 2014
references Aycock, J. & Friess, N. (2006). Spam zombies from outer space. 15th Annual EICAR Conference, pp. 164–179.
Tiu, V. (2009). Confounded Conficker. Virus Bulletin, March, pp. 7–11.
F-Secure (2009). Calculating the size of the Downadup outbreak. Weblog: News from the Lab, 16 January 2009. Available: http://www.f-secure.com/weblog/archives/00001584.html
Finjan (2009). How a cybergang operates a network of 1.9 million infected computers. Available: http://www.finjan.com/MCRCblog.aspx?EntryId=2237
Porras, P., Saidi, H. & Yegneswaran, V. (2009). An analysis of Conficker’s logic and rendezvous points. SRI International Technical Report. Available: http://mtc.sri.com/Conficker
Riordan, J. & Schneier, B. (1998). Environmental key generation towards clueless agents. Mobile Agents and Security, 1419, pp. 15–24.
EICAR (2006). The anti-virus or anti-malware test file. Available: http://www.eicar.org/anti_virus_test_file.htm
Ferrie, P. (2010). Anti-unpacker tricks. Virus Bulletin, May, pp. 4–9.
Oreans Technology (2009). Code Virtualizer. Available: http://www.oreans.com/codevirtualizer.php
VMPsoft (2009). VMProtect. Available: http://vmpsoft.com/
Debaere, E. & Van Campenhout, J. (1990). Intrepretation and Instruction Path Coprocessing. ACM SIGPLAN Notices, 25(9), pp. 7-9.
Klint, P. (1981). Interpretation techniques. Software – Practice and Experience, 11(9), pp. 963–973.
Kuenning, G. (2007). Mersenne Twist pseudorandom number generator package, version 1.20. Available: http://www.cs.hmc.edu/∼geoff/mtwist.html
Toyofuku, T., Tabata, T. & Sakurai, K. (2005). Program obfuscation scheme using random numbers to complicate control flow. 1st International Workshop on Security in Ubiquitous Computing Systems, 3823, pp. 916-925.
Friess, N., Aycock, J. & Vogt, R. (2008). Black market botnets. Department of Computer Science, University of Calgary 2500 University Drive N.W., Calgary, Alberta, Canada.
Larkin, E. (2007). Storm worm’s virulence may change tactics. Network World, 2. Available: http://www.networkworld.com/news/2007/080207-black-hat-storm-worms-virulence.html
Aycock, J., De Graaf, R. & Jacobson, M. (2006). Anti-disassembly using cryptographic hash functions. Journal in Computer Virology, 2(1), pp. 79–85.
Hemmingsen, R., Aycock, J. & Jacobson, M. (2007). Spam, phishing, and the looming challenge of big botnets. EU Spam Symposium.
White, S. (1989). Covert distributed processing with computer viruses. Advances in Cryptology – CRYPTO ’89 Proceedings, pp. 616– 619, LNCS 435.
Shoch, J. & Hupp, J. (1982). The “worm” programs – early experience with a distributed computation. Communications of the ACM, 25(3), pp. 172–180.
Anderson, D., Cobb, J., Korpela, E., Lebofsky, M. & Werthimer, D. (2002). SETI@home: An experiment in public-resource computing. Communications of the ACM, 45(11), pp. 56–61.
Sharif, M., Lanzi, A., Giffin, J. & Lee, W. (2009). Automatic reverse engineering of malware emulators. IEEE Symposium on Security and Privacy. Georgia Institute of Technology, USA.
Holz, T., Steiner, M., Dahl, F., Biersack, E. & Freiling, F. (2008). Measurements and mitigation of peer-to-peer-based botnets: A case study on Storm Worm. 1st USENIX Workshop on Large-Scale Exploits and Emergent Threats. Available: https://www.usenix.org/legacy/events/leet08/tech/full_papers/holz/holz.pdf
Sterling, T. (2005). Prosecutors say Dutch suspects hacked 1.5 million computers worldwide. Associated Press. Available: http://www.foxnews.com/story/2005/10/20/dutch-hackers-infected-15-million-computers/
Rajab, M., Zarfoss, J., Monrose, F. & Terzis, A. (2007). My botnet is bigger than yours (maybe, better than yours): why size estimates remain challenging. 1st Workshop on Hot Topics in Understanding Botnets (HotBots ’07). Available: https://www.usenix.org/legacy/event/hotbots07/tech/full_papers/rajab/rajab.pdf
Franklin, J., Paxson, V., Perrig, A. & Savage, S. (2007). An inquiry into the nature and causes of the wealth of Internet miscreants. 14th ACM Conference on Computer and Communications Security (pp. 375-388). New York, New York, United States of America. doi:10.1145/1315245.1315292
Szappanos, G. (2007). Exepacker blacklisting. Virus Bulletin. Available: http://www.virusbtn.com/virusbulletin/archive/2007/10/vb200710-exepacker-blacklisting
Collberg, C., Thomborson, C. & Low, D. (1997). A taxonomy of obfuscating transformations. Technical Report 148. Available: https://researchspace.auckland.ac.nz/bitstream/handle/2292/3491/TR148.pdf
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