ABUSE.MOM
THREAT REPORT

IP Threat Report
136.255.77.195

ABUSE.MOM — BEHAVE OR GET EXPOSED

Generated: 2026-09-14 00:29:09
First seen: 2026-09-12 12:33:21
Last seen: 2026-09-13 01:17:28
95

⛔ Verdict: BLOCK

This IP address has been classified as a source of malicious automated activity. Threat score: 95/100. Total malicious requests observed: 21.

DANGER_PATH
01

Geolocation & Classification

IP Address
136.255.77.195
Type
Residential
Country
🇷🇴 Romania
City
Bucharest
ISP
Vodafone Romania S.A.
Organization
Urbioled SRL
Autonomous System
AS12302 Vodafone Romania S.A.
Hit Count
21
02

Detection Signatures

SignatureDescriptionPointsSeverity
Danger medium hits: 2Medium-risk: admin panels, config files+20
Danger strong hits: 3High-risk paths: shells, RCE vectors, exploits+75
Σ = 95
03

Observed Activity

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

[redacted]
GET
/
200
Requests shown: 1 · HTTP 404: 0 · Dangerous patterns: 0

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

04

Timeline

2026-09-12 12:33:21
First malicious request detected
IP entered monitoring from server access logs
During observation
Multiple detection signatures triggered
Danger medium hits: 2 (+20), Danger strong hits: 3 (+75)
2026-09-13 01:17:28
Last malicious request observed
Total score reached: 95/100
Next cycle
IP blocked — all subsequent requests denied (HTTP 403)
Added to blocklist automatically
05

Network Provider

Vodafone Romania S.A.
AS12302 · 🇷🇴 Romania
06

Recommendations

Actions taken & recommended

  • IP 136.255.77.195 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

⚙️ Defensive Recommendations

Block 136.255.77.195 at the network perimeter. Implement defense-in-depth combining IP blocking with application-layer protections.

09

Blacklist Status (DNSBL)

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

✓ Clean
bl.blocklist.de
✓ Clean
psbl.surriel.com
✓ Clean
cbl.abuseat.org
✓ Clean
zen.spamhaus.org
✓ Clean
spam.dnsbl.sorbs.net
✓ Clean
dnsbl.dronebl.org
✓ Clean
b.barracudacentral.org

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

10

Threat Analysis

136.255.77.195 has been assigned a threat score of 95/100 (Critical). This represents a critical risk level. Our detection systems have flagged multiple high-confidence indicators of malicious intent from this address.

📊 Threat Analysis

Our monitoring infrastructure has identified 136.255.77.195, geolocated to Bucharest, Romania, operating on the network of Vodafone Romania S.A., as a source of suspicious network activity. The address has been active for 1 days in our monitoring system, producing 21 flagged requests at a rate of ~21/day. Operating from a residential network, this IP may represent a compromised home gateway or IoT device that has been drafted into a larger attack infrastructure. Our records show 101 malicious IPs originating from Romania, positioning it as a significant contributor to global threat activity. A score of 95/100 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 Romania

85.204.124.94 (255)85.121.215.243 (230)38.133.142.84 (230)45.43.166.68 (230)38.133.142.105 (230)View all →

🏢 Same network: AS12302

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12

Security Intelligence

💡 SQL Injection Campaigns

SQL injection remains one of the most common web attack vectors. Attackers inject malicious SQL code through input fields to extract database contents, modify data, or gain administrative access. Automated scanners test for SQLi vulnerabilities at massive scale.

💡 Machine Learning in Threat Detection

Machine learning models analyze vast amounts of network traffic to identify attack patterns invisible to rule-based systems. Supervised models classify known attack types while unsupervised models detect anomalies that may indicate novel threats.

🔍 Check Any IP Address

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