Nmap Recall: Persistent, Searchable Memory for Your Network Scans
The scan was complete, but the truth hid in the noise. Nmap Recall strips that noise away. It takes raw Nmap output and reconstructs it into clean, queryable data you can trust. No missed ports. No stale results. Every scan is archived, indexed, and resurrected in seconds.
Nmap Recall is not another wrapper. It’s a memory layer for your network scans. It captures every result from Nmap’s powerful probing—open ports, service banners, version fingerprints—and stores them in a format you can recall with precision. Throw a regex at past scans. Compare today’s network to last month’s. Find the gap before it becomes an incident.
When security teams run Nmap across large IP ranges, the data is often disposable—lost after the terminal closes. Nmap Recall changes that. It creates a persistent dataset. You don’t re-run scans unless you want fresh data. You recall previous ones instantly. It saves time, cuts bandwidth, and keeps you ahead of unknown drift.
Integrating Nmap Recall into your workflow is simple. Feed your Nmap command output—whether standard text, XML, or JSON—into the Recall store. The engine parses and tags each element. From there, you can search, filter, export, or script against the results. The stored scans become a living record of your network’s footprint.
Version tracking is built in. Every run gets a timestamp, source, and hash. Nmap Recall lets you trace changes across deployments, cloud migrations, or firewall updates. For audit, compliance, or forensic analysis, this historical view is invaluable.
Performance is key. Nmap Recall is optimized for fast lookup and minimal resource cost. You can work across millions of results without the slowdown of traditional file parsing. Whether scanning subnets or entire data centers, retrieval speed stays constant.
If you rely on Nmap for discovery or security, you need more than a snapshot. You need recall. See Nmap Recall in action at hoop.dev and build your first persistent scan index in minutes.