arXiv CS
open access
DarKnight: Retrieval-Guided Agentic Framework for Breaking Dark Web CAPTCHA Gates
Cyber Threat Intelligence (CTI) investigators who monitor dark web marketplaces for leaked credentials and breach listings must pass the diverse CAPTCHAs that operators deploy to block automated collection. Existing solvers either need unscalable per-site fine-tuning or rely on commercial Vision-Lan
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
- DarKnight: Retrieval-Guided Agentic Framework for Breaking Dark Web CAPTCHA Gates#1354513
- XAI for Cybersecurity: State of the Art, Challenges, Open Issues and Future Directions#437425
- Cyber security training tool that uses a large language model — Darktrace Holdings Limited (US20240406210A1)#607518
- ParanoiaEval: Benchmarking Unnecessary Defensive Work in Agentic Coding#1218454
- ParanoiaEval: Benchmarking Unnecessary Defensive Work in Agentic Coding#1210336
Record · ID 1335927
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