AI pipeline leakage audit for regulated data

No product checks whether gateway or router logs reveal sensitive topics, and none tests whether page-image or multi-vector document indexes (ColPali-style) can be rebuilt into pages. IronCore's VectorLens covers only a few text embedding models and does not reconstruct text. The big data-security and AI-security vendors (BigID, Varonis, Sentra, Cyera, Palo Alto, Wiz) find and classify these assets but do not run inversion attacks. A new entrant could win by (1) testing page-image and multi-vector indexes for reconstruction, (2) auditing router and gateway logs, and (3) mapping findings to fintech rules (GLBA, fair-lending protected attributes under ECOA, PCI, model risk management) for a lender's CISO or DPO. Risks: the router-leakage threat rests on one exploratory paper from 7 Oct 2026, so buyers don't know about it yet; and the incumbents already own the inventory step and could add inversion testing quickly. The vector-reconstruction scanner is the stronger lead product, with router-log leakage as an add-on.

• IronCore Labs VectorLens

  2026 CLI tool that scans exported embeddings for PII without needing the source data. It detects categories of sensitive data but does not release reconstruction (IronCore says it built inversion models and held them back). It supports only a few text embedding models and is mostly English. This is the closest direct competitor on the vector side.

• IronCore Labs Cloaked AI

  Searchable encryption for embeddings across Pinecone, Qdrant, pgvector, Milvus and others. It overlaps with the 'encrypt the index' fix.

• BigID (vector database DSPM)

  Says it is the first data-security platform to scan and secure sensitive data in vector databases. It classifies data; it does not test whether vectors can be inverted.

• Varonis (Cyral acquisition)

  Database activity monitoring framed around vector databases, plus monitoring of AI prompts and data access.

• Sentra

  Data-security platform that maps which AI agents and LLMs can reach sensitive data and classifies data flowing into AI pipelines. Runs inside the customer's own cloud.

• Palo Alto Networks Cortex Cloud AI-SPM

  Automatically finds AI assets, including AWS S3 Vector indexes, and classifies sensitive data used for embeddings and RAG. Covers the inventory step, not inversion or router-log leakage.

• Wiz AI-SPM

  Cloud AI security tool that inventories AI components and sensitive data. Overlaps on discovery.

• Repello AI

  AI red-teaming vendor that writes about LLM router security (a routing decision leaking credentials). Could extend into router-log audits.

• Assessing Vector and Embedding Weaknesses (community skill)

  Unofficial, community-written test checklist mapped to OWASP LLM08, covering inversion, membership inference and cross-tenant leakage across Pinecone, Qdrant, Chroma, pgvector and others. Unverified.

• Research: Sensitive-Topic Leakage Through LLM Routing Metadata

  Research paper, not a product. Submitted 7 Oct 2026, single author, results labelled exploratory. It describes exactly the router-log threat; the RouteLLM attack scored AUC 0.71 (below the author's pre-set 0.75 target), and a subject-based router reached 0.92 as an upper estimate. No commercial tool found.