ABUSE.MOM
THREAT REPORT

IP Threat Report
78.41.63.2

ABUSE.MOM — BEHAVE OR GET EXPOSED

Generated: 2026-05-30 07:14:02
First seen: 2026-03-20 03:00:07
Last seen: 2026-03-31 12:00:07
255

⛔ Verdict: BLOCK

This IP address has been classified as a source of malicious automated activity. Threat score: 255/100. Total malicious requests observed: 24.

DANGER_PATHREFERERUA_CHANGEDBURST
01

Geolocation & Classification

IP Address
78.41.63.2
Type
Residential
Country
🇳🇱 Netherlands
City
Amsterdam
ISP
Global Layer B.V.
Organization
0Day Host (SMC-Private) Limited
Autonomous System
AS49453 Global Layer B.V.
Hit Count
24
02

Detection Signatures

SignatureDescriptionPointsSeverity
Danger strong hits: 4High-risk paths: shells, RCE vectors, exploits+100
Danger medium hits: 4Medium-risk: admin panels, config files+40
Foreign referer seenReferer from unrelated external domain+10
UA changed for same IPMultiple User-Agents — bot rotation technique+25
Danger strong hits: 2High-risk paths: shells, RCE vectors, exploits+50
Danger medium hits: 2Medium-risk: admin panels, config files+20
Danger strong hits: 22High-risk paths: shells, RCE vectors, exploits+100
Danger medium hits: 30Medium-risk: admin panels, config files+60
Burst: 30 req / 2sAbnormally fast request rate — automated scanning+35
Burst: 30 req / 10sAbnormally fast request rate — automated scanning+35
Σ = 475
03

Observed Activity

Reconstructed HTTP requests from server access logs. Target domains redacted for security.

[redacted]
GET
/
200
[redacted]
GET
/page
200
Requests shown: 2 · HTTP 404: 0 · Dangerous patterns: 0

* Typical request patterns for detected signatures. Actual target domains are redacted.

04

Timeline

2026-03-20 03:00:07
First malicious request detected
IP entered monitoring from server access logs
During observation
Multiple detection signatures triggered
Danger strong hits: 4 (+100), Danger medium hits: 4 (+40), Foreign referer seen (+10)
2026-03-31 12:00:07
Last malicious request observed
Total score reached: 255/100
Next cycle
IP blocked — all subsequent requests denied (HTTP 403)
Added to blocklist automatically
05

Network Provider

Global Layer B.V.
AS49453 · 🇳🇱 Netherlands
06

Recommendations

Actions taken & recommended

  • IP 78.41.63.2 is blocked at application level (HTTP 403)
  • Consider blocking at firewall level (iptables/CSF) to reduce server load
  • Report abuse to the network provider via their abuse contact
  • Ensure sensitive files (.env, .git, backups) are not accessible from the web

🤖 User-Agent Anomaly Defense

IP 78.41.63.2 shows suspicious UA behavior. Block empty User-Agent requests. Implement JavaScript-based bot detection for sensitive endpoints.

🌊 Flood / DDoS Mitigation

Implement limit_req_zone in nginx. Deploy CDN with DDoS protection. Configure SYN cookies and connection tracking to throttle 78.41.63.2.

08

Open Ports & Services

Network reconnaissance data from Shodan. Open ports may indicate running services, misconfigurations, or potential attack surfaces.

OPEN PORTS (1)
PortServiceRiskDescription
3389RDPHighRemote Desktop Protocol — primary target for ransomware attacks

⚠️ 1 high-risk port detected on 78.41.63.2. Exposed RDP (3389) is the #1 entry point for ransomware attacks. These services should not be publicly accessible without strict firewall rules.

Hostnames: hosted-by.0dayhost.com
PTR: hosted-by.0dayhost.com

Data source: Shodan InternetDB. Scanned independently of abuse.mom.

09

Blacklist Status (DNSBL)

This IP was checked against major DNS-based blacklists used by mail servers and firewalls worldwide.

✓ Clean
ix.dnsbl.manitu.net
✓ Clean
dnsbl.sorbs.net
✓ Clean
zen.spamhaus.org
✓ Clean
bl.spamcop.net
✓ Clean
dnsbl-1.uceprotect.net
✓ Clean
psbl.surriel.com
✓ Clean
b.barracudacentral.org
✓ Clean
truncate.gbudb.net

Checked: Spamhaus, SpamCop, Barracuda, SORBS, CBL, UCEProtect. Results may change over time.

10

Threat Analysis

78.41.63.2 has been assigned a threat score of 255/100 (Critical). With this rating, the IP falls into the critical severity bracket — among the most dangerous addresses in our monitoring database.

The following attack categories were identified:

User-Agent AnomalyRequest Flooding

📊 Threat Analysis

Threat intelligence analysis has linked 78.41.63.2 to malicious activity originating from Amsterdam, Netherlands, operating on the network of Global Layer B.V.. The address has been under observation since its initial detection. The address has been active for 11 days in our monitoring system, producing 24 flagged requests at a rate of ~2.2/day. This residential IP is likely a compromised consumer device. Home routers and IoT equipment with default credentials are prime targets for botnet operators. The dual attack vectors of User-Agent Anomaly combined with Request Flooding indicate a coordinated assault rather than opportunistic scanning. Our records show 107 malicious IPs originating from Netherlands, positioning it as a significant contributor to global threat activity. A score of 255/100 places this address in the top tier of severity. Block and investigate any historical connections.

This IP is classified as residential, suggesting it may belong to a compromised home device, IoT botnet member, or an infected personal computer. Residential IPs involved in attacks often indicate malware infection without the owner's knowledge.

11

Related Threats

🇳🇱 Top threats from Netherlands

185.184.192.251 (338)45.88.138.44 (320)45.82.64.236 (315)5.181.169.192 (313)157.22.73.141 (313)View all →

🏢 Same network: AS49453

View all →
12

Security Intelligence

💡 XML External Entity (XXE) Attacks

XXE vulnerabilities in XML parsers allow attackers to read local files, perform SSRF, and execute denial of service attacks. Many legacy applications and APIs remain vulnerable to XXE due to insecure default XML parser configurations.

💡 Web Application Firewall Strategies

WAFs inspect HTTP traffic to block common attacks but require careful tuning. Overly aggressive rules cause false positives while permissive configurations miss attacks. Modern WAFs combine signature matching with behavioral analysis and machine learning.

🔍 Check Any IP Address

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