Starseer
Scans models for vulnerabilities before deployment and watches their internal activations at runtime.
Highlights
- Pre-deployment model vulnerability scanning and model fingerprinting
- Runtime activation monitoring with session containment
- An AI gateway that classifies requests and enforces custom policies with low latency
- Defenses against prompt injection, backdoors, and data poisoning
- Case-file investigations linking prompts, tool calls, and application traces
- Fully air-gapped, offline deployment with no external dependencies
- Model-agnostic operation across providers
- A focus on high-security and regulated environments
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About Starseer
What it is
Starseer is an AI security and interpretability platform for establishing trust in models you did not train. It fingerprints and scans models for vulnerabilities before deployment, then monitors activations at runtime to detect malicious behaviour as it forms rather than after it appears in output.
Why it's different
Watching activations rather than output is the technically distinctive part, and the reasoning is sound: filtering output catches what a model says, which is late, while an attack manipulating a model's behaviour is visible internally first. Applying interpretability research to security is an unusual and promising direction. The caution is that interpretability is an active research area rather than a settled one, and claims about detecting intent from internal states deserve scrutiny proportionate to how strong they sound. The underlying problem is real though: teams download weights from public hubs and deploy them with less scrutiny than any other third-party binary.
How people use it
It is used by organisations running open-weight models from public sources, where supply chain risk is genuine and currently mostly unmanaged. The pre-deployment scanning is the more immediately practical half, since it addresses a question most teams have never asked about the weights they downloaded. Runtime monitoring is more experimental and worth evaluating on what it actually catches in your own deployment.
Written by the n3os team. We are not affiliated with Starseer.
This listing was written from public information, without Starseer’s involvement. If you own it and something here is wrong — or you would rather not be listed at all — email us and we will correct or remove it.
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