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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM43018

Malfoyle - A Robust Implementation of Hash-Based Cryptographic Detection Systems and Yara Rule Integration

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM43018

Volume:

9 |

4 |

Apr 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM43018

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

GV

G. Vivekananda

MAK

Morupoju Akshith Kumar

PH

P. Hiranmayee

DPR

Dr. P Ramadevi

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Abstract

Malware remains a significant cybersecurity threat, highlighting the need for innovative detection methods to address limitations of existing approaches [7]. As organizations face devastating consequences due to sophisticated malware attacks and lack of effective fallback mechanisms [7], the development of robust detection tools becomes critical. The evolving nature of malware, driven by obfuscations, mutations, and modifications, dynamically alters feature distributions and renders static detection methods ineffective, necessitating adaptive approaches to combat these challenges [2]. MalFoyle is an open-source Command Line Interface (CLI) instrument formulated in Python that utilizes a hash-based malware detection paradigm. By computing the SHA256 hash of files and inquiring within a prominent malware repository, MalFoyle furnishes users with invaluable insights, encompassing vendor judgments and Yet Another Ridiculous Acronym (YARA) regulations, facilitating swift identification and alleviation of potential threats. While recognizing limitations such as database veracity, detection of polymorphic malware, and possible false positives or negatives, MalFoyle offers a pragmatic resolution for expeditious malware evaluation. The tool illustrates substantial potential for incorporation into extensive security architectures, including automated workflows, threat intelligence platforms, endpoint safeguarding, and incident response contexts, thereby all the augmenting overall malware detection competencies. MalFoyle contributes to the ongoing progression of malware detection methodologies and emphasizes the significance of open-source instruments in addressing the evolving challenges of cybersecurity.

KEYWORDS

Malware detection hash-based detection command-line interface(CLI) malware database YARA(Yet Another Ridiculous Acronym) rules limitations threat intelligence endpoint security incident response SHA-256 Algorithm MD-5 Algorithm

Cite This Article

G. Vivekananda, Morupoju Akshith Kumar, P. Hiranmayee, Dr. P Ramadevi, "Malfoyle - A Robust Implementation of Hash-Based Cryptographic Detection Systems and Yara Rule Integration," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 4, Apr 2025. https://doi.org/10.55041/IJSREM43018

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Publication Date

4/24/2025

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Double-Blind Peer Review

Review Rounds: 2

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