arXiv (All)
open access
Autonomous OSS Threat Detection via Taxonomy-Aligned LLMs
Open source software (OSS) ecosystems face growing threats from sophisticated supply chain attacks including typosquatting, dependency confusion, Trojan Source obfuscation, malicious build injection, and CI/CD pipeline poisoning. Existing detection approaches rely on signature-based tools and rule-b
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Autonomous OSS Threat Detection via Taxonomy-Aligned LLMs#1160948
- Understanding and Mitigating Prompt Leaking Attacks in Real-World LLM-Based Applications#287061
- Towards Behavior Tree-Guided Vulnerability Detection with Lightweight LLMs#632795
- Kill-Chain Canaries: Stage-Level Tracking of Prompt Injection Across Attack Surfaces and Five Production LLMs#1144778
- OllamaDrama: Designing and Deploying a Honeypot to Measure Attacks on Exposed LLM Infrastructure#1077684
Record · ID 1156535
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive