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Survey of Techniques to Detect Cwes in Program Binaries

https://doi.org/10.2139/ssrn.4637378
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Outgoing claims: the papers this work cites, builds on, or argues with.

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A Decision Procedure for Bit-Vectors and Arrays
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A New Algorithm for Identifying Loops in Decompilation
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BAP: A Binary Analysis Platform
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A unit-based symbolic execution method for detecting memory corruption vulnerabilities in executable codes
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On the capability of static code analysis to detect security vulnerabilities
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Machine Learning-Based Analysis of Program Binaries: A Comprehensive Study
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Scalable Static Detection of Use-After-Free Vulnerabilities in Binary Code
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NPDHunter: Efficient Null Pointer Dereference Vulnerability Detection in Binary
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Automatically assessing crashes from heap overflows
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Practical memory checking with Dr. Memory
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Auditing Buffer Overflow Vulnerabilities Using Hybrid Static-Dynamic Analysis
inferredcites →https://doi.org/10.1109/compsac.2015.78openalex-extracted
Buffer Overflow Vulnerability Prediction from x86 Executables Using Static Analysis and Machine Learning
inferredcites →https://doi.org/10.1109/cscs52396.2021.00027openalex-extracted
CWE Pattern Identification using Semantical Clustering of Programming Language Keywords
inferredcites →https://doi.org/10.1109/dasc-picom-cbdcom-cyberscitech49142.2020.00095openalex-extracted
A Neural Embedding for Source Code: Security Analysis and CWE Lists
inferredcites →https://doi.org/10.1109/dsc.2018.00017openalex-extracted
The Coming Era of AlphaHacking?: A Survey of Automatic Software Vulnerability Detection, Exploitation and Patching Techniques
inferredcites →https://doi.org/10.1109/edcc51268.2020.00025openalex-extracted
On the Use of Open-Source C/C++ Static Analysis Tools in Large Projects
inferredcites →https://doi.org/10.1109/electronica52725.2021.9513723openalex-extracted
Predicting Vulnerability Type in Common Vulnerabilities and Exposures (CVE) Database with Machine Learning Classifiers
inferredcites →https://doi.org/10.1109/iccais48893.2020.9096731openalex-extracted
Machine Learning Approach to Predict Computer Operating Systems Vulnerabilities
inferredcites →https://doi.org/10.1109/iccitm56309.2022.10031734openalex-extracted
Machine Learning for Software Vulnerability Detection: A Survey
inferredcites →https://doi.org/10.1109/icdsba51020.2020.00015openalex-extracted
Buffer Overflow Vulnerability Location in Binaries Based on Abnormal Execution
inferredcites →https://doi.org/10.1109/icse43902.2021.00054openalex-extracted
Why Don’t Developers Detect Improper Input Validation? '; DROP TABLE Papers; --
inferredcites →https://doi.org/10.1109/ispras57371.2022.10076861openalex-extracted
Sydr-Fuzz: Continuous Hybrid Fuzzing and Dynamic Analysis for Security Development Lifecycle
inferredcites →https://doi.org/10.1109/issrew.2017.72openalex-extracted
Detection of Memory Leaks in C/C++ Code via Machine Learning
inferredcites →https://doi.org/10.1109/jproc.2020.2993293openalex-extracted
Software Vulnerability Detection Using Deep Neural Networks: A Survey
inferredcites →https://doi.org/10.1109/snpd.2016.7515929openalex-extracted
Detecting integer overflow in Windows binary executables based on symbolic execution
inferredcites →https://doi.org/10.1109/sp.2010.26openalex-extracted
All You Ever Wanted to Know about Dynamic Taint Analysis and Forward Symbolic Execution (but Might Have Been Afraid to Ask)
inferredcites →https://doi.org/10.1109/sp.2013.13openalex-extracted
SoK: Eternal War in Memory
inferredcites →https://doi.org/10.1109/sp.2016.17openalex-extracted
SOK: (State of) The Art of War: Offensive Techniques in Binary Analysis
inferredcites →https://doi.org/10.1109/trustcom53373.2021.00087openalex-extracted
Multi-level Directed Fuzzing for Detecting Use-after-Free Vulnerabilities
inferredcites →https://doi.org/10.1109/tse.2019.2946148openalex-extracted
IntRepair: Informed Repairing of Integer Overflows
inferredcites →https://doi.org/10.1145/1024393.1024412openalex-extracted
Low-overhead memory leak detection using adaptive statistical profiling
inferredcites →https://doi.org/10.1145/1037187.1024412openalex-extracted
Low-overhead memory leak detection using adaptive statistical profiling
inferredcites →https://doi.org/10.1145/1065010.1065034openalex-extracted
Pin
inferredcites →https://doi.org/10.1145/1273442.1250746openalex-extracted
Valgrind
inferredcites →https://doi.org/10.1145/3092566openalex-extracted
Software Vulnerability Analysis and Discovery Using Machine-Learning and Data-Mining Techniques
inferredcites →https://doi.org/10.1145/3134600.3134620openalex-extracted
Machine-Learning-Guided Typestate Analysis for Static Use-After-Free Detection
inferredcites →https://doi.org/10.1145/3192366.3192388openalex-extracted
EffectiveSan: type and memory error detection using dynamically typed C/C++
inferredcites →https://doi.org/10.1145/3363824openalex-extracted
Fuzzing
inferredcites →https://doi.org/10.1145/3465481.3465771openalex-extracted
Integer Overflow Detection with Delayed Runtime Test
inferredcites →https://doi.org/10.1145/3486592openalex-extracted
Static analysis
inferredcites →https://doi.org/10.1145/3494521openalex-extracted
Survey of Approaches for Postprocessing of Static Analysis Alarms
inferredcites →https://doi.org/10.1145/3508398.3511511openalex-extracted
Security Analysis of IoT Frameworks using Static Taint Analysis
inferredcites →https://doi.org/10.1145/3512345openalex-extracted
Fuzzing: A Survey for Roadmap
inferredcites →https://doi.org/10.1145/3529836.3529926openalex-extracted
Learning-based Vulnerability Detection in Binary Code
inferredcites →https://doi.org/10.1145/3587135.3592205openalex-extracted
Accelerating Type Confusion Detection by Identifying Harmless Type Castings
inferredcites →https://doi.org/10.1145/360248.360252openalex-extracted
Symbolic execution and program testing
inferredcites →https://doi.org/10.14722/bar.2018.23019openalex-extracted
Saluki: Finding Taint-style Vulnerabilities with Static Property Checking
inferredcites →https://doi.org/10.23919/icact48636.2020.9061281openalex-extracted
Analysis of software weakness detection of CBMC based on CWE
inferredcites →https://doi.org/10.4018/ijsssp.2018070101openalex-extracted
What Do We Know About Buffer Overflow Detection?
inferredcites →https://doi.org/10.48550/arxiv.1805.11001openalex-extracted
inferredcites →https://doi.org/10.48550/arxiv.2002.10751openalex-extracted
Binary-level Directed Fuzzing for Use-After-Free Vulnerabilities
inferredcites →https://doi.org/10.48550/arxiv.2007.07586openalex-extracted
TeeRex: Discovery and Exploitation of Memory Corruption Vulnerabilities in SGX Enclaves
inferredcites →https://doi.org/10.48550/arxiv.2012.15116openalex-extracted
Stack-based Buffer Overflow Detection using Recurrent Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.2306.11673openalex-extracted
A Survey on Automated Software Vulnerability Detection Using Machine Learning and Deep Learning
inferredcites →https://doi.org/10.48550/arxiv.cs/0004015openalex-extracted
inferredcites →https://doi.org/10.5167/uzh-207978openalex-extracted
Why Don’t Developers Detect Improper Input Validation?
inferredcites →https://doi.org/10.70675/925cbaa4zcf94z42a9z8e19z54d8c586211eopenalex-extracted
Finding the needle in the heap : combining binary analysis techniques to trigger use-after-free
inferredcites →https://doi.org/10.1006/jsco.2001.0494openalex-snapshot
Introduction to the GiNaC Framework for Symbolic Computation within the C++ Programming Language
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