Imagen de Portada

Beyond Static Tools: Evaluating Large Language Models for Cryptographic Misuse Detection

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Masood, Zohaib, Martin, Miguel Vargas
Formato:	Preprint
Publicado:	2024
Materias:	Cryptography and Security Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Beyond Static Pattern Matching? Rethinking Automatic Cryptographic API Misuse Detection in the Era of LLMs
por: Xia, Yifan, et al.
Publicado: (2024)

Unelicitable Backdoors in Language Models via Cryptographic Transformer Circuits
por: Draguns, Andis, et al.
Publicado: (2024)

Mark Your LLM: Detecting the Misuse of Open-Source Large Language Models via Watermarking
por: Xu, Yijie, et al.
Publicado: (2025)

INTACT: Intent-Aware Representation Learning for Cryptographic Traffic Violation Detection
por: Ray, Rahul D
Publicado: (2026)

Model Inversion Attacks Meet Cryptographic Fuzzy Extractors
por: Prabhakar, Mallika, et al.
Publicado: (2025)

Evaluating Large Language Models in Vulnerability Detection Under Variable Context Windows
por: Lin, Jie, et al.
Publicado: (2025)

"MCP Does Not Stand for Misuse Cryptography Protocol": Uncovering Cryptographic Misuse in Model Context Protocol at Scale
por: Yan, Biwei, et al.
Publicado: (2025)

Adversaries Can Misuse Combinations of Safe Models
por: Jones, Erik, et al.
Publicado: (2024)

Mutation-based Evaluation of Cryptographic API Misuse Detectors
por: Ami, Amit Seal, et al.
Publicado: (2021)

Learning to Localize Leakage of Cryptographic Sensitive Variables
por: Gammell, Jimmy, et al.
Publicado: (2025)

Cryptographic Backdoor for Neural Networks: Boon and Bane
por: Ngo, Anh Tu, et al.
Publicado: (2025)

Evaluating Apple Intelligence's Writing Tools for Privacy Against Large Language Model-Based Inference Attacks: Insights from Early Datasets
por: Soumik, Mohd. Farhan Israk, et al.
Publicado: (2025)

Transfer Learning in Pre-Trained Large Language Models for Malware Detection Based on System Calls
por: Sánchez, Pedro Miguel Sánchez, et al.
Publicado: (2024)

Beyond the Wrapper: Identifying Artifact Reliance in Static Malware Classifiers using TRUSTEE
por: Mohammed, Riyazuddin, et al.
Publicado: (2026)

Improving IoT Intrusion Detection Through SMOTE-Based Oversampling and Extended Multi-Model Evaluation on Side-Channel Power Data
por: Shahzad, Muhammad Khuram, et al.
Publicado: (2026)

A Cryptographic Perspective on Mitigation vs. Detection in Machine Learning
por: Gluch, Greg, et al.
Publicado: (2025)

Black-Box Detection of Language Model Watermarks
por: Gloaguen, Thibaud, et al.
Publicado: (2024)

Evaluating Cryptographic API Misuse Detectors for Go
por: Andersson, Vivi, et al.
Publicado: (2026)

HIDBench: Benchmarking Large Language Models for Host-Based Intrusion Detection
por: Sun, Danyu, et al.
Publicado: (2026)

Adversarial Sample Generation for Anomaly Detection in Industrial Control Systems
por: Mustafa, Abdul, et al.
Publicado: (2025)

Command-line Obfuscation Detection using Small Language Models
por: Outrata, Vojtech, et al.
Publicado: (2024)

A Deep-Learning Technique to Locate Cryptographic Operations in Side-Channel Traces
por: Chiari, Giuseppe, et al.
Publicado: (2024)

Backdoor Channels Hidden in Latent Space: Cryptographic Undetectability in Modern Neural Networks
por: Eggen, Marte, et al.
Publicado: (2026)

PrivGNN: High-Performance Secure Inference for Cryptographic Graph Neural Networks
por: Wang, Fuyi, et al.
Publicado: (2025)

GETA: Generalized Encrypted Traffic Analysis
por: Gunasekara, Ransika, et al.
Publicado: (2026)

CYBERSECEVAL 3: Advancing the Evaluation of Cybersecurity Risks and Capabilities in Large Language Models
por: Wan, Shengye, et al.
Publicado: (2024)

Improved Large Language Model Jailbreak Detection via Pretrained Embeddings
por: Galinkin, Erick, et al.
Publicado: (2024)

Beyond Static Datasets: A Behavior-Driven Entity-Specific Simulation to Overcome Data Scarcity and Train Effective Crypto Anti-Money Laundering Models
por: P, Dinesh Srivasthav, et al.
Publicado: (2025)

A Machine Learning-Based Framework for Assessing Cryptographic Indistinguishability of Lightweight Block Ciphers
por: Dani, Jimmy, et al.
Publicado: (2024)

"Do Anything Now": Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language Models
por: Shen, Xinyue, et al.
Publicado: (2023)

Improving Network Threat Detection by Knowledge Graph, Large Language Model, and Imbalanced Learning
por: Zhang, Lili, et al.
Publicado: (2025)

Evaluating Large Language Models for Phishing Detection, Self-Consistency, Faithfulness, and Explainability
por: Kuikel, Shova, et al.
Publicado: (2025)

ChatGPT's Potential in Cryptography Misuse Detection: A Comparative Analysis with Static Analysis Tools
por: Firouzi, Ehsan, et al.
Publicado: (2024)

R+R: Revisiting Static Feature-Based Android Malware Detection using Machine Learning
por: Alam, Md Tanvirul, et al.
Publicado: (2024)

CyberSecEval 2: A Wide-Ranging Cybersecurity Evaluation Suite for Large Language Models
por: Bhatt, Manish, et al.
Publicado: (2024)

Adaptive and Robust Data Poisoning Detection and Sanitization in Wearable IoT Systems using Large Language Models
por: Mithsara, W. K. M, et al.
Publicado: (2025)

Prompt Obfuscation for Large Language Models
por: Pape, David, et al.
Publicado: (2024)

On Large Language Model Continual Unlearning
por: Gao, Chongyang, et al.
Publicado: (2024)

Signal Watermark on Large Language Models
por: Xu, Zhenyu, et al.
Publicado: (2024)

Scalable Fingerprinting of Large Language Models
por: Nasery, Anshul, et al.
Publicado: (2025)