ABUSE.MOM
THREAT REPORT

IP Threat Report
70.153.136.253

ABUSE.MOM — BEHAVE OR GET EXPOSED

Generated: 2026-05-27 04:28:51
First seen: 2026-05-12 23:00:06
Last seen: 2026-05-24 10:21:55
85

⛔ Verdict: BLOCK

This IP address has been classified as a source of malicious automated activity. Threat score: 85/100. Total malicious requests observed: 299.

DANGER_PATHREDIRECT_PROBEREFERER
01

Geolocation & Classification

IP Address
70.153.136.253
Type
Residential
Country
🇮🇩 Indonesia
City
Jakarta
ISP
Microsoft Corporation
Organization
CHA ADSL EEUA
Autonomous System
AS8075 Microsoft Corporation
Hit Count
299
02

Detection Signatures

SignatureDescriptionPointsSeverity
Danger strong hits: 2High-risk paths: shells, RCE vectors, exploits+50
Danger strong hits: 3High-risk paths: shells, RCE vectors, exploits+75
Foreign refererReferer from unrelated external domain+10
Foreign referer seenReferer from unrelated external domain+10
Probe 302→404Behavioral anomaly detected by automated analysis+20
Probe pattern 302->404 same pathBehavioral anomaly detected by automated analysis+20
Σ = 185
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

2026-05-12 23:00:06
First malicious request detected
IP entered monitoring from server access logs
During observation
Multiple detection signatures triggered
Danger strong hits: 2 (+50), Danger strong hits: 3 (+75), Foreign referer (+10)
2026-05-24 10:21:55
Last malicious request observed
Total score reached: 85/100
Next cycle
IP blocked — all subsequent requests denied (HTTP 403)
Added to blocklist automatically
05

Network Provider

Microsoft Corporation
AS8075 · 🇮🇩 Indonesia
06

Recommendations

Actions taken & recommended

  • IP 70.153.136.253 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

🔎 Path Enumeration Protection

Block scanning from 70.153.136.253: rate-limit 404 responses per IP, deploy a honeypot 404 page, ensure no backup files are web-accessible.

09

Blacklist Status (DNSBL)

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

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

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

10

Threat Analysis

70.153.136.253 has been assigned a threat score of 85/100 (Critical). A score this high marks a critical threat actor. This address has demonstrated persistent, aggressive malicious behavior across multiple detection vectors.

The following attack categories were identified:

Path Enumeration

📊 Threat Analysis

Threat intelligence analysis has linked 70.153.136.253 to malicious activity originating from Jakarta, Indonesia, operating on the network of Microsoft Corporation. The address has been under observation since its initial detection. The address has been active for 11 days in our monitoring system, producing 299 flagged requests at a rate of ~27.2/day. This is a residential IP address, suggesting a compromised home device such as a router, smart appliance, or infected workstation participating in a botnet. The IP exhibits directory enumeration behavior, systematically requesting non-existent paths to discover hidden files and misconfigured resources. Indonesia currently accounts for 101 blocked IPs in our database, making it a significant source of malicious traffic. A threat score of 85/100 places this IP in the high-risk category. Blocking at the firewall level is recommended.

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 Indonesia

157.15.40.88 (340)203.175.125.130 (340)157.15.40.93 (340)157.15.40.62 (340)157.15.40.89 (340)View all →

🏢 Same network: AS8075

74.241.249.229 (340)20.151.111.128 (308)4.182.24.88 (285)20.65.61.3 (283)4.205.39.97 (283)View all →
12

Security Intelligence

💡 Credential Stuffing at Scale

Credential stuffing uses stolen username-password pairs from data breaches to attempt logins across many websites. Since users frequently reuse passwords, these automated attacks achieve success rates of 0.1-2%, which translates to thousands of compromised accounts from millions of attempts.

💡 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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