Malware Analysis

Benchmarks archive 2025-07-28

No benchmark for this task in the archive.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

3 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Most implemented papers archive 2025-07-28

27 shown of 27 papers with code (89 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• SAFE: Self-Attentive Function Embeddings for Binary Similarity
  13 Nov 2018 3 repositories listed Syntology ran 0 of 4 samples · 4 unverified · 1 pointer-only (licence)
  We report the results from a quantitative and qualitative analysis that show how SAFE provides a noticeable performance improvement with respect to previous solutions.
• EMBER2024 -- A Benchmark Dataset for Holistic Evaluation of Malware Classifiers
  5 Jun 2025 2 repositories listed
  A lack of accessible data has historically restricted malware analysis research, and practitioners have relied heavily on datasets provided by industry sources to advance.
• Evading Malware Classifiers via Monte Carlo Mutant Feature Discovery
  15 Jun 2021 2 repositories listed
  The use of Machine Learning has become a significant part of malware detection efforts due to the influx of new malware, an ever changing threat landscape, and the ability of Machine Learning methods to discover…
• Dynamic Malware Analysis with Feature Engineering and Feature Learning
  17 Jul 2019 2 repositories listed
  In this paper, we propose a novel and low-cost feature extraction approach, and an effective deep neural network architecture for accurate and fast malware detection.
• DecompileBench: A Comprehensive Benchmark for Evaluating Decompilers in Real-World Scenarios
  16 May 2025 1 repository listed
  Decompilers are fundamental tools for critical security tasks, from vulnerability discovery to malware analysis, yet their evaluation remains fragmented.
• CyberLLMInstruct: A New Dataset for Analysing Safety of Fine-Tuned LLMs Using Cyber Security Data
  12 Mar 2025 1 repository listed
  In our primary example, we rigorously assess the safety of fine-tuned models using the OWASP top 10 framework, finding that fine-tuning reduces safety resilience across all tested LLMs and every adversarial attack (e.
• Is Function Similarity Over-Engineered? Building a Benchmark
  30 Oct 2024 1 repository listed Syntology ran 1 of 1 samples · 0 unverified
  Binary analysis is a core component of many critical security tasks, including reverse engineering, malware analysis, and vulnerability detection.
• Magika: AI-Powered Content-Type Detection
  18 Sep 2024 1 repository listed
  In order to foster adoption and improvements, we open source Magika under an Apache 2 license on GitHub and make our model and training pipeline publicly available.
• Know Your Neighborhood: General and Zero-Shot Capable Binary Function Search Powered by Call Graphlets
  2 Jun 2024 1 repository listed
  Binary code similarity detection is an important problem with applications in areas such as malware analysis, vulnerability research and license violation detection.
• Large Language Models for Cyber Security: A Systematic Literature Review
  8 May 2024 1 repository listed Syntology ran 3 of 3 samples · 0 unverified
  Overall, our survey provides a comprehensive overview of the current state-of-the-art in LLM4Security and identifies several promising directions for future research.
• Threat Behavior Textual Search by Attention Graph Isomorphism
  16 Apr 2024 1 repository listed
  As such, analysts often resort to text search techniques to identify existing malware reports based on the symptoms they observe, exploiting the fact that malware samples share a lot of similarity, especially those from…
• Nebula: Self-Attention for Dynamic Malware Analysis
  19 Sep 2023 1 repository listed
  Dynamic analysis enables detecting Windows malware by executing programs in a controlled environment and logging their actions.
• FINER: Enhancing State-of-the-art Classifiers with Feature Attribution to Facilitate Security Analysis
  10 Aug 2023 1 repository listed
  Although feature attribution (FA) methods can be used to explain deep learning, the underlying classifier is still blind to what behavior is suspicious, and the generated explanation cannot adapt to downstream tasks,…
• Revisiting Deep Learning for Variable Type Recovery
  7 Apr 2023 1 repository listed
  Unfortunately, the lack of semantic information like variable types makes comprehending binaries difficult.
• Reliable Malware Analysis and Detection using Topology Data Analysis
  3 Nov 2022 1 repository listed
  Next, we compare the different TDA techniques (i.
• Avast-CTU Public CAPE Dataset
  6 Sep 2022 1 repository listed
  The benefit of using dynamic sandboxes is the realistic simulation of file execution in the target machine and obtaining a log of such execution.
• Quo Vadis: Hybrid Machine Learning Meta-Model based on Contextual and Behavioral Malware Representations
  20 Aug 2022 1 repository listed
  The detection heuristic in contemporary machine learning Windows malware classifiers is typically based on the static properties of the sample since dynamic analysis through virtualization is challenging for vast…
• SCRUTINIZER: Detecting Code Reuse in Malware via Decompilation and Machine Learning
  9 Jul 2021 1 repository listed
  In response to such attacks, both academia and industry have investigated techniques to model and reconstruct these attacks and to defend against them.
• On Ensemble Learning
  7 Mar 2021 1 repository listed
  Our common framework and empirical results are an effort to bring some sense of order to the chaos that is evident in the evolving field of ensemble learning -- both within the narrow confines of the malware analysis…
• Binary Black-box Evasion Attacks Against Deep Learning-based Static Malware Detectors with Adversarial Byte-Level Language Model
  14 Dec 2020 1 repository listed
  Recently, deep learning-based static anti-malware detectors have achieved success in identifying unseen attacks without requiring feature engineering and dynamic analysis.
• Interpreting Machine Learning Malware Detectors Which Leverage N-gram Analysis
  27 Jan 2020 1 repository listed
  This is because the models are complex, and most of them work as a black-box.
• Integration of Static and Dynamic Analysis for Malware Family Classification with Composite Neural Network
  24 Dec 2019 1 repository listed
  In this paper, we combine static and dynamic analysis features with deep neural networks for Windows malware classification.
• Malware Classification using Deep Learning based Feature Extraction and Wrapper based Feature Selection Technique
  24 Oct 2019 1 repository listed
  The proposed DLMD technique uses both the byte and ASM files for feature engineering, thus classifying malware families.
• KiloGrams: Very Large N-Grams for Malware Classification
  1 Aug 2019 1 repository listed
  N-grams have been a common tool for information retrieval and machine learning applications for decades.
• AndrODet: An Adaptive Android Obfuscation Detector
  1 Jan 2019 1 repository listed
  This is typically applied to protect intellectual property in benign apps, or to hinder the process of extracting actionable information in the case malware.
• A Cross-Architecture Instruction Embedding Model for Natural Language Processing-Inspired Binary Code Analysis
  23 Dec 2018 1 repository listed
  As a showcase, we apply the model to resolving one of the most fundamental problems for binary code similarity comparison---semantics-based basic block comparison, and the solution outperforms the code statistics based…
• Malware triage for early identification of Advanced Persistent Threat activities
  16 Oct 2018 1 repository listed
  In order to early identify APT related malware, a semi-automatic approach for malware samples analysis is needed.

Syntology lines on 3 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.