Catch attackers touching your AI first.
STACK Decoy deploys realistic decoy agents, synthetic prompts, and trap embeddings across your environment — surfacing threat actors before they reach production systems.
Decoys that look like the real thing
Static honeypots get fingerprinted. STACK Decoy decoys behave like real agents.
Decoy Agents
LLM-driven decoy agents indistinguishable from production. Chat, hold context, and respond to social engineering.
Trap Embeddings
Marked vectors seeded into stores. Any retrieval triggers high-fidelity threat alerts.
Honey Credentials
Synthetic API keys, OAuth tokens, and service principals scattered across realistic locations. Use-and-alert wired in.
Document Bait
Realistic but synthetic confidential docs in shared drives, S3 buckets, and SharePoint sites.
Persona Library
Decoy employee personas with email, calendar, and Slack presence. Phishing campaigns get caught here first.
Threat Intel Feed
Every interaction enriched, attributed where possible, and pushed into your SIEM as high-confidence signal.
Questions teams ask before deploying
Straightforward answers about scope, integration, data handling, and rollout.
Won't legitimate users hit the decoys?
Decoys live outside legitimate user paths. We've run 3,400+ deployments with a sub-0.01% accidental-touch rate.
How do you avoid burning the decoys?
Adaptive rotation, behavioral mimicry of real assets, and decoys that update their content on the same cadence as production.
What about insider threats?
Decoys are intentionally tempting to insiders. We surface internal recon patterns alongside external attackers.
How does it integrate with our SIEM?
Webhook, Splunk HEC, Sentinel, Chronicle, and S3-bucket export. Decoy hits arrive pre-enriched as high-confidence incidents.