FOR SAAS TEAMS
Your churn risk is a breach you learned about last.
SaaS teams usually hear about credential stuffing and leaked documents from their customers. Canaries give you a signal of your own: decoys sit where attackers work, and when one is touched, the alert arrives with evidence.
FIVE USE CASES
Where SaaS products actually leak.
Watch the lists attackers harvest
CanaryVaults seeds decoy credentials onto paste sites inside fake combo lists, a day or two after it mints them. A decoy belongs to no real person, so when one is used, someone harvested it from one of the places it was seeded, and the attempt's source infrastructure is captured as evidence.
Decoy identities →Trap-fact the docs behind your AI features
If you ship an AI assistant over customer or internal documents, trap facts prove when that content surfaces somewhere it should not, such as a competitor's bot or a leaked knowledge base, even after paraphrase.
RAG trap facts →Put a firewall in front of your LLM endpoints
Your users paste untrusted content into your AI features every day. CanaryShield inspects each request through rules, a semantic analyzer, and a sanitizer, and you adopt it by changing one base URL in your OpenAI-compatible client.
Prompt-injection firewall →Let attackers rehearse on a decoy
Deploy a honeypot assistant that looks like your production support bot. Probes get classified by intent (jailbreak, extraction, probing) and fingerprinted, so you see the playbook an attacker tries on the decoy.
Decoy assistants →A week of decoy hits in one summary
In a week when your decoys fire, CanaryVaults sends one summary, by email and on Telegram if you linked it: how many hits, from how many IP addresses, the kinds of attacker, the platforms they went after and the week's highest risk score.
How decoys alert →NOTHING TO INSTALL
Nothing runs on your servers.
There is no agent to run on your infrastructure. Decoy credentials go where leaked lists circulate, trap facts go into the documents you choose, and audit records seal what your agents do, so the same patterns work whichever database, auth provider or host your product runs on.
IS THIS FOR YOU
A fit if any of these sound familiar.
GO DEEPER
Field notes from the team.
Why AI security alerts need evidence attached from the start
The design principle behind every alert on this page.
Proof beats suspicion when private documents leak through AI
What happens when your docs feed someone else's model.
Why prompt injection needs its own firewall
Why moderation-after-the-fact fails for SaaS AI features.
Plant your first canary today.
Free tier, no credit card.