Executable Packing
759 items from dhondta/awesome-executable-packing ★1,628
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Squishy logicoma.io
Modern packer developed for 64kb demoscene productions, targets 32bit and 64bit executables.
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Wavelet decomposition of software entropy reveals symptoms of malicious code linkinghub.elsevier.com
(December 2016)
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Performance evaluation of filter-based feature selection techniques in classifying portable executable files linkinghub.elsevier.com
(January 2018) :star:
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Conceptual and empirical comparison of dimensionality reduction algorithms (PCA, KPCA, LDA, MDS, SVD, LLE, ISOMAP, LE… linkinghub.elsevier.com
(May 2021)
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API-MalDetect: Automated malware detection framework for windows based on API calls and deep learning techniques linkinghub.elsevier.com
(September 2023) :star:
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G3MD: Mining frequent opcode sub-graphs for metamorphic malware detection of existing families linkinghub.elsevier.com
(December 2018)
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Metamorphic malware identification using engine-specific patterns based on co-opcode graphs linkinghub.elsevier.com
(August 2020) :star:
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Benchmark for filter methods for feature selection in high-dimensional classification data linkinghub.elsevier.com
(March 2020) :star:
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Resurrecting anti-virtualization and anti-debugging: Unhooking your hooks linkinghub.elsevier.com
(March 2021) :star:
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Beyond the sandbox: Leveraging symbolic execution for evasive malware classification linkinghub.elsevier.com
(February 2025) :star:
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Adversarial attacks against Windows PE malware detection: A survey of the state-of-the-art linkinghub.elsevier.com
(May 2023) :star:
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A systematical and longitudinal study of evasive behaviors in windows malware linkinghub.elsevier.com
(February 2022) :star:
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A novel framework for image-based malware detection with a deep neural network linkinghub.elsevier.com
(October 2021) :star:
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Auditing static machine learning anti-Malware tools against metamorphic attacks linkinghub.elsevier.com
(March 2021) :star:
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A framework for metamorphic malware analysis and real-time detection linkinghub.elsevier.com
(February 2015)
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Opcode sequences as representation of executables for data-mining-based unknown malware detection linkinghub.elsevier.com
(May 2013) :star:
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Research of software information hiding algorithm based on packing technology link.springer.com
(September 2020)
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Generic unpacking method based on detecting original entry point link.springer.com
(November 2013)
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Detecting traditional packers, decisively link.springer.com
(October 2013)
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A static, packer-agnostic filter to detect similar malware samples link.springer.com
(July 2012)
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A fine-grained classification approach for the packed malicious code link.springer.com
(October 2012)
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OPEM: A static-dynamic approach for machine-learning-based malware detection link.springer.com
(September 2012)
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PEAL - Packed executable analysis link.springer.com
(January 2012)
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Semi-supervised learning for unknown malware detection link.springer.com
(April 2011)
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Pattern recognition techniques for the classification of malware packers link.springer.com
(July 2010)
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Denial-of-service attacks on host-based generic unpackers link.springer.com
(December 2009)
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PE-Miner: Mining structural information to detect malicious executables in realtime link.springer.com
(September 2009)
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Efficient and automatic instrumentation for packed binaries link.springer.com
(June 2009)
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BitBlaze: A new approach to computer security via binary analysis link.springer.com
(December 2008)
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A study of the packer problem and its solutions link.springer.com
(September 2008)
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Symbolic deobfuscation: From virtualized code back to the original link.springer.com
(July 2018)
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Packer identification using hidden Markov model link.springer.com
(November 2017)
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RAMBO: Run-Time packer analysis with multiple branch observation link.springer.com
(July 2016)
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AppSpear: Bytecode decrypting and DEX reassembling for packed Android malware link.springer.com
(November 2015)
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DexHunter: Toward extracting hidden code from packed Android applications link.springer.com
(September 2015)
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Highlighting the impact of packed executable alterations with unsupervised learning link.springer.com
(April 2025) :star:
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Assessing static and dynamic features for packing detection link.springer.com
(October 2024) :star:
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Unpacking malware in the real world: A step-by step guide link.springer.com
(July 2024) :star:
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Evading packing detection: Breaking heuristic-based static detectors link.springer.com
(July 2024) :star:
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Experimental toolkit for manipulating executable packing link.springer.com
(June 2024) :star: :star:
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Original entry point detection based on graph similarity link.springer.com
(April 2024) :star:
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A machine-learning-based framework for supporting malware detection and analysis link.springer.com
(September 2021) :star:
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VABox: A virtualization-based analysis framework of virtualization-obfuscated packed executables link.springer.com
(June 2021) :star:
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Generic black-box end-to-end attack against state of the art API call based malware classifiers link.springer.com
(September 2018) :star:
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On the (Im)possibility of obfuscating programs link.springer.com
(August 2001)
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Boosting scalability in anomaly-based packed executable filtering link.springer.com
(November 2011)
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Structural feature based anomaly detection for packed executable identification link.springer.com
(June 2011)
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Eureka: A framework for enabling static malware analysis link.springer.com
(October 2008)
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Challenging anti-virus through evolutionary malware obfuscation link.springer.com
(April 2016)
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PEzoNG: Advanced packer for automated evasion on Windows link.springer.com
(December 2022) :star:
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