Honeypot Detection: Commercial Threat Intel Mapping (ONYPHE)

Systematic scan on 9770/TCP with banner grab and controlled RST

9770/TCP

Target Port

AS213412

ONYPHE SAS

~98 ms

Interaction Time

Executive Summary

Suricata detected internet-wide reconnaissance by ONYPHE (commercial scanner). The probe executed a clean TCP handshake, captured a banner, and immediately reset — classic cataloging behavior for sale in a commercial database. While not malicious per se, this activity enables both defenders and adversaries.

Observation Timeline

Detection

Suricata flagged inbound probe to 9770/TCP

T+00:00

Event triaged
Session reconstructed
Confirmed banner grab + RST

Attribution

IP linked to ONYPHE SAS (AS213412), known commercial scanner

T+00:04

ASN + org lookups
Checked existing sightings in TI feeds
Tagged as “mass scanner”

Assessment

Non-targeted internet-wide enumeration; low immediate risk but high OSINT impact

T+00:10

Categorized as mapping activity
Evaluated exposure of deception fingerprints

Response

Implemented scanner-specific responses and tracking

T+00:18

Decoy banner rotation enabled
Honeytoken beacon prepared
Correlation alert created

Scan Characteristics

• Target port: 9770/TCP (non-standard, high-entropy)
• Connection: TCP SYN → banner grab → immediate RST
• Duration: ~98ms total interaction time
• Bytes: ~128 sent / 74 received
• Behavior: Clean handshake with controlled termination

Scanner Infrastructure

• Organization: ONYPHE SAS — commercial threat intelligence provider
• Network: AS213412; traffic observed from 91.231.89.129 (OVH/Gravelines region)
• Reputation: Labeled “mass scanner” across multiple threat feeds
• Model: Sells access to discovered services, banners, certificates

Findings may be re-sold — assume your deception fingerprints are catalogued.

The Researcher Paradox

• Legally operated scanners mirror attacker recon behavior
• Blocking them can reduce researcher visibility while attackers still find paths
• Their datasets can be purchased by threat actors (“reconnaissance-as-a-service”)

Strategic Recommendations

• Respond with decoy banners or delayed/variable responses to pollute commercial datasets
• Correlate scans with later targeted traffic; raise priority when correlation exists
• Use honeytokens that only appear after indexing — detect downstream consumption
• Segment deception infra so cataloging doesn’t reveal production fingerprints

Consider sharing noisy decoy intel to dilute value while tracking reuse.

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