Open Source · RAG
EmbedGuard
Cross-Layer Detection and Provenance Attestation for Adversarial Embedding Attacks in RAG Systems
Our verdict
We have not reviewed EmbedGuard yet
No one at Enterprise DNA has checked this listing against its sources. The description comes from public listings gathered automatically. Any fact below shows where it came from and when it was last checked.
From the listing
About EmbedGuard
EmbedGuard is a Python-based observability tool for RAG systems. It aims to detect adversarial embedding attacks and provide provenance attestation for retrieved content across multiple layers. The project is in an early community stage with no released version or star history.
Best for
Security researchers and RAG developers evaluating defenses against embedding-level attacks.
Use cases
- Detect poisoned or manipulated embeddings in RAG retrieval
- Verify the provenance of chunks before they reach the LLM
- Monitor RAG pipelines for cross-layer attack indicators
Notes
0 stars on GitHub. Last updated 2026-09-29. Licensed MIT.
Pros
- Addresses a specific and underexplored RAG security surface
- Open source under a community vendor with no vendor lock-in
- Python makes it easy to integrate with existing ML workflows
Cons
- No stars or release history to indicate maturity or adoption
- No documentation, benchmarks, or usage examples available
- Scope is limited to adversarial embedding attacks, not general observability
Key facts
What we have checked
- GitHub stars
- 0
Each value shows when we last confirmed it and where it came from. Values we have not confirmed are left out, never guessed.
Sources
Where this comes from
- github api via nightly crawl, recovered from git history a4692e327b8f3e9910b4a3a1a5a01e375baca892Registry
A source shows what was published when we checked it. It does not certify security, performance or a working installation. Read our method.
Changelog
What changed
No changes recorded yet. Releases, price changes and deprecations appear here, with their dates, once we track them for this record.
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