# An LLM-based Quantitative Framework for Evaluating High-Stealthy Backdoor Risks in OSS Supply Chains

arXiv: https://arxiv.org/abs/2511.13341 · HTML: https://mlsanity.com/paper/2511.13341/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Placed in Backdoor and data poisoning attacks, one of 12 directions in LLM safety and security.
- Builds on 5 of its 25 references that are in the map.
- First posted on arXiv 17 Nov 2025.

## Placed in

- LLM safety and security / [Backdoor and data poisoning attacks](https://mlsanity.com/safety/backdoor-and-data-poisoning-attacks/)

## Builds on (most cited first, 5 of 5)

- [OpenSSF Scorecard: On the Path Toward Ecosystem-wide Automated Security Metrics](https://mlsanity.com/paper/2208.03412/) (2022)
- [Wolves in the Repository: A Software Engineering Analysis of the XZ Utils Supply Chain Attack](https://mlsanity.com/paper/2504.17473/) (2025)
- [Extension Decisions in Open Source Software Ecosystem](https://mlsanity.com/paper/2507.23168/) (2025)
- [Closing the Chain: How to reduce your risk of being SolarWinds, Log4j, or XZ Utils](https://mlsanity.com/paper/2503.12192/) (2025)
- [ARMS: A Vision for Actor Reputation Metric Systems in the Open-Source Software Supply Chain](https://mlsanity.com/paper/2505.18760/) (2025)

## Built on by (most cited first, 1 of 1)

- [ElasticBack: Stealthy Conditional Backdoor in LLM-Agent Skills via Coupled Trigger-Rule Optimization](https://mlsanity.com/paper/2608.09577/) (2026)

## Abstract (arXiv)

In modern software development workflows, the open-source software supply chain contributes significantly to efficient and convenient engineering practices. With increasing system complexity, using open-source software as third-party dependencies has become a common practice. However, the lack of maintenance for underlying dependencies and insufficient community auditing create challenges in ensuring source code security and the legitimacy of repository maintainers, especially under high-stealthy backdoor attacks exemplified by the XZ-Util incident. To address these problems, we propose a fine-grained project evaluation framework for backdoor risk assessment in open-source software. The framework models stealthy backdoor attacks from the viewpoint of the attacker and defines targeted metrics for each attack stage. In addition, to overcome the limitations of static analysis in assessing the reliability of repository maintenance activities such as irregular committer privilege escalation and limited participation in reviews, the framework uses large language models (LLMs) to conduct semantic evaluation of code repositories without relying on manually crafted patterns. The framework is evaluated on sixty six high-priority packages in the Debian ecosystem. The experimental results indicate that the current open-source software supply chain is exposed to various security risks.