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Founder's Pitch
"HubScan detects and mitigates hubness poisoning attacks in retrieval-augmented generation systems for secure AI data access."
Commercial Viability Breakdown
0-10 scaleHigh Potential
2/4 signals
Quick Build
4/4 signals
Series A Potential
4/4 signals
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Why It Matters
RAG systems are vulnerable to hubness poisoning attacks that can lead to misleading data retrieval and compromised AI output, which can have severe security implications.
Product Angle
Transform HubScan into a plug-in or standalone security tool for AI-driven applications that utilize RAG systems, with integration options for common vector databases like FAISS and Weaviate.
Disruption
Replaces manual oversight and traditional security protocols in AI systems which are ineffective in real-time detection of hubness attacks, offering automated, proactive threat detection.
Product Opportunity
The need to secure RAG systems in enterprises using AI for decision support creates a large market valued in the cybersecurity sector, where companies will pay to ensure data integrity and system reliability.
Use Case Idea
Commercial cybersecurity software for companies using RAG systems to prevent data poisoning attacks, ensuring reliable AI outputs.
Science
HubScan uses robust statistical methods such as median/MAD-based z-scores to detect anomalous hubs in vector indices, which act as attractors in high-dimensional spaces, often used maliciously to insert misleading or harmful content.
Method & Eval
Tested on adversarial datasets (Food-101, MS-COCO) and real-world data (MS MARCO) with strong performance metrics reaching 100% recall for targeted detection scenarios.
Caveats
The system might encounter challenges with evolving adversarial tactics or new attack forms that bypass current detection methods. Continuous update and adaptation will be necessary.
Author Intelligence
Idan Habler
LEAD Cisco
ihabler@cisco.com
Vineeth Sai Narajala
Cisco
vineeth.sai@owasp.org
Stav Koren
Tel Aviv University
stavk@mail.tau.ac.il
Amy Chang
Cisco
changamy@cisco.com
Tiffany Saade
Cisco
tsaade@cisco.com