Cover Image

Identifying the Supply Chain of AI for Trustworthiness and Risk Management in Critical Applications

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Sheh, Raymond K., Geappen, Karen
Format:	Preprint
Published:	2025
Subjects:	Artificial Intelligence Cryptography and Security Software Engineering
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Large Language Model Supply Chain: Open Problems From the Security Perspective
by: Hu, Qiang, et al.
Published: (2024)

Understanding the Supply Chain and Risks of Large Language Model Applications
by: Ma, Yujie, et al.
Published: (2025)

Reflection-Driven Control for Trustworthy Code Agents
by: Wang, Bin, et al.
Published: (2025)

Python Fuzzing for Trustworthy Machine Learning Frameworks
by: Yegorov, Ilya, et al.
Published: (2024)

Risks of ignoring uncertainty propagation in AI-augmented security pipelines
by: Mezzi, Emanuele, et al.
Published: (2024)

Securing the Software Package Supply Chain for Critical Systems
by: Murali, Ritwik, et al.
Published: (2025)

SOK: Exploring Hallucinations and Security Risks in AI-Assisted Software Development with Insights for LLM Deployment
by: Haque, Ariful, et al.
Published: (2025)

Securing the AI Supply Chain: What Can We Learn From Developer-Reported Security Issues and Solutions of AI Projects?
by: Nguyen, The Anh, et al.
Published: (2025)

Software Supply Chain Smells: Lightweight Analysis for Secure Dependency Management
by: Schmid, Larissa, et al.
Published: (2026)

An Empirically Grounded Reference Architecture for Software Supply Chain Metadata Management
by: Tran, Nguyen Khoi, et al.
Published: (2023)

Poisoned Identifiers Survive LLM Deobfuscation: A Case Study on Claude Opus 4.6
by: Lorenzo, Luis Guzmán
Published: (2026)

From Detection to Prevention: Explaining Security-Critical Code to Avoid Vulnerabilities
by: Krishnamurthy, Ranjith, et al.
Published: (2026)

On the Security Risks of ML-based Malware Detection Systems: A Survey
by: He, Ping, et al.
Published: (2025)

`Do as I say not as I do': A Semi-Automated Approach for Jailbreak Prompt Attack against Multimodal LLMs
by: Chiu, Chun Wai, et al.
Published: (2025)

Securing the Future of IVR: AI-Driven Innovation with Agile Security, Data Regulation, and Ethical AI Integration
by: Shaikh, Khushbu Mehboob, et al.
Published: (2025)

Operationalizing Research Software for Supply Chain Security
by: Kalu, Kelechi G., et al.
Published: (2026)

When Safe Skills Collide: Measuring Compositional Risk in Agent Skill Ecosystems
by: Wang, Su, et al.
Published: (2026)

A sketch of an AI control safety case
by: Korbak, Tomek, et al.
Published: (2025)

AI security and cyber risk in IoT systems
by: Radanliev, Petar, et al.
Published: (2024)

AI Code Generators for Security: Friend or Foe?
by: Natella, Roberto, et al.
Published: (2024)

Understanding Privacy Risks in Code Models Through Training Dynamics: A Causal Approach
by: Yang, Hua, et al.
Published: (2025)

Containment Verification: AI Safety Guarantees Independent of Alignment
by: Moon, Royce, et al.
Published: (2026)

LLM-enabled Applications Require System-Level Threat Monitoring
by: Zhang, Yedi, et al.
Published: (2026)

We Urgently Need Privilege Management in MCP: A Measurement of API Usage in MCP Ecosystems
by: Li, Zhihao, et al.
Published: (2025)

Leveraging Large Language Models for Cybersecurity Risk Assessment -- A Case from Forestry Cyber-Physical Systems
by: Gultekin, Fikret Mert, et al.
Published: (2025)

Data and Context Matter: Towards Generalizing AI-based Software Vulnerability Detection
by: Safdar, Rijha, et al.
Published: (2025)

DevOps-Gym: Benchmarking AI Agents in Software DevOps Cycle
by: Tang, Yuheng, et al.
Published: (2026)

Poisoning Programs by Un-Repairing Code: Security Concerns of AI-generated Code
by: Improta, Cristina
Published: (2024)

Testing Storage-System Correctness: Challenges, Fuzzing Limitations, and AI-Augmented Opportunities
by: Wang, Ying, et al.
Published: (2026)

Block MedCare: Advancing healthcare through blockchain integration with AI and IoT
by: Simonoski, Oliver, et al.
Published: (2024)

AutoEG: Exploiting Known Third-Party Vulnerabilities in Black-Box Web Applications
by: Yang, Ruozhao, et al.
Published: (2026)

AIBoMGen: Generating an AI Bill of Materials for Secure, Transparent, and Compliant Model Training
by: Vandendriessche, Wiebe, et al.
Published: (2026)

Broken by Default: A Formal Verification Study of Security Vulnerabilities in AI-Generated Code
by: Blain, Dominik, et al.
Published: (2026)

Zer0n: An AI-Assisted Vulnerability Discovery and Blockchain-Backed Integrity Framework
by: Parmar, Harshil, et al.
Published: (2026)

LinuxArena: A Control Setting for AI Agents in Live Production Software Environments
by: Tracy, Tyler, et al.
Published: (2026)

MalCodeAI: Autonomous Vulnerability Detection and Remediation via Language Agnostic Code Reasoning
by: Gajjar, Jugal, et al.
Published: (2025)

Investigating Detection and Obfuscation of Prompt Injection Attacks Against Software Reverse Engineering AI Agents
by: Crawford, Brian, et al.
Published: (2026)

Software Supply Chain Security of Web3
by: Monperrus, Martin
Published: (2025)

Safety and Performance, Why Not Both? Bi-Objective Optimized Model Compression against Heterogeneous Attacks Toward AI Software Deployment
by: Zhu, Jie, et al.
Published: (2024)

Evaluating Software Supply Chain Security in Research Software
by: Hegewald, Richard, et al.
Published: (2025)