ABUSE.MOM
THREAT REPORT

IP Threat Report
101.132.184.223

ABUSE.MOM — BEHAVE OR GET EXPOSED

Generated: 2026-05-30 07:19:03
First seen: 2026-04-06 23:00:06
Last seen: 2026-04-08 07:00:05
90

⛔ Verdict: BLOCK

This IP address has been classified as a source of malicious automated activity. Threat score: 90/100. Total malicious requests observed: 2.

BURSTREFERERRATIO_404REDIRECT_PROBE
01

Geolocation & Classification

IP Address
101.132.184.223
Type
Residential
Country
🇨🇳 China
City
Shanghai
ISP
Hangzhou Alibaba Advertising Co
Organization
Aliyun Computing Co., LTD
Autonomous System
AS37963 Hangzhou Alibaba Advertising Co.,Ltd.
Hit Count
2
02

Detection Signatures

SignatureDescriptionPointsSeverity
Burst: 7 req / 2sAbnormally fast request rate — automated scanning+35
Burst: 14 req / 10sAbnormally fast request rate — automated scanning+35
Foreign referer seenReferer from unrelated external domain+10
404 ratio >= 60%Majority of requests returned 404 — enumeration+25
Probe pattern 302->404 same pathBehavioral anomaly detected by automated analysis+20
Burst: 5 req / 2sAbnormally fast request rate — automated scanning+35
Σ = 160
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

2026-04-06 23:00:06
First malicious request detected
IP entered monitoring from server access logs
During observation
Multiple detection signatures triggered
Burst: 7 req / 2s (+35), Burst: 14 req / 10s (+35), Foreign referer seen (+10)
2026-04-08 07:00:05
Last malicious request observed
Total score reached: 90/100
Next cycle
IP blocked — all subsequent requests denied (HTTP 403)
Added to blocklist automatically
05

Network Provider

Hangzhou Alibaba Advertising Co
AS37963 · 🇨🇳 China
06

Recommendations

Actions taken & recommended

  • IP 101.132.184.223 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

🌊 Flood / DDoS Mitigation

Implement limit_req_zone in nginx. Deploy CDN with DDoS protection. Configure SYN cookies and connection tracking to throttle 101.132.184.223.

🔎 Path Enumeration Protection

Block scanning from 101.132.184.223: rate-limit 404 responses per IP, deploy a honeypot 404 page, ensure no backup files are web-accessible.

08

Open Ports & Services

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

OPEN PORTS (4)
PortServiceRiskDescription
22SSHLowSecure Shell — common brute force target for remote access
80HTTPLowHTTP web server — standard web traffic
443HTTPSLowHTTPS web server — encrypted web traffic
3306MySQLHighMySQL database — should never be exposed to the internet

⚠️ 1 high-risk port detected on 101.132.184.223. These services should not be publicly accessible without strict firewall rules.

KNOWN VULNERABILITIES (CVE) (14)
CVE IDLink
CVE-2019-16905NVD →
CVE-2020-15778NVD →
CVE-2023-48795NVD →
CVE-2023-38408NVD →
CVE-2020-14145NVD →
CVE-2025-32728NVD →
CVE-2023-51767NVD →
CVE-2007-2768NVD →
CVE-2008-3844NVD →
CVE-2021-41617NVD →
CVE-2025-26465NVD →
CVE-2023-51385NVD →
CVE-2021-36368NVD →
CVE-2016-20012NVD →

🔴 This host has 14 known CVEs associated with its exposed services. This volume strongly suggests severely outdated software. Review each CVE in the NVD database.

DETECTED TECHNOLOGIES
f5:nginxoracle:mysql:5.7.40-logopenbsd:openssh:8.0
Hostnames: ahjzpx.anjianzi.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
b.barracudacentral.org
✓ Clean
truncate.gbudb.net
✓ Clean
psbl.surriel.com

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

10

Threat Analysis

101.132.184.223 has been assigned a threat score of 90/100 (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:

Request FloodingPath Enumeration

📊 Threat Analysis

Network traffic from 101.132.184.223, located in Shanghai, China, operating on the network of Hangzhou Alibaba Advertising Co, has been classified as malicious by our automated threat scoring engine. The address has been active for 1 days in our monitoring system, producing 2 flagged requests at a rate of ~2/day. The address is classified as residential, meaning it likely belongs to an end-user ISP connection. Malicious activity from residential IPs typically indicates device compromise or botnet membership. The dual attack vectors of Request Flooding combined with Path Enumeration indicate a coordinated assault rather than opportunistic scanning. China currently accounts for 123 blocked IPs in our database, making it a significant source of malicious traffic. At 90/100, this is an extremely high-risk address. All traffic should be considered hostile.

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

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🏢 Same network: AS37963

120.26.168.44 (230)139.196.99.108 (195)47.116.207.202 (190)121.43.99.231 (185)182.92.218.96 (170)View all →
12

Security Intelligence

💡 DDoS Mitigation Approaches

Distributed denial of service attacks overwhelm infrastructure with traffic volume. Effective mitigation combines always-on traffic scrubbing, anycast network distribution, rate limiting, and the ability to quickly scale absorption capacity during attacks.

💡 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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