Threat Trends Digest – September 2026

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Welcome to the Threat Trends Digest, a monthly view of real-world threat patterns.

This report compiles data from the previous month using Malware Patrol’s global telemetry and live attack observations to surface key stats on malware, phishing, ransomware, C2s, and domain generation algorithms (DGAs). You’ll find insights into the most exploited TLDs, frequently seen malware hashes and IPs, and other critical indicators. Use this digest to keep a close pulse on attacker behavior, uncover shifting patterns, and better align your defenses with the latest threat activity.

For more articles, check out our #onpatrol4malware blog.

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IOCs

Malicious IPs

IP Source (ISP/ASN) Country 
106.41.200.151 CHINANET HUNAN PROVINCE NETWORK CN
89.111.158.16 JSC RU-CENTER RU
173.205.127.152 Web Hosting Hub, Inc US
74.115.51.9 Weebly, Inc. US
74.115.51.8 Weebly, Inc. US
185.143.233.238 AbrArvan BGP Anycast IR
185.143.234.238 AbrArvan BGP Anycast IR
43.231.112.25 Apartment # 34, 2nd khoroo MN
162.241.24.119 Unified Layer US
64.40.13.26 GLOBALHOSTINGSOLUTIONS INC US
212.99.45.180 Completel SAS FR
77.65.212.167 PROGRESO.PL SP Z O.O PL
64.37.63.18 HostDime.com, Inc. US
178.48.185.211 2Connect Telecommunications Infrastructure & Network Services Ltd. HU
203.162.31.118 VietNam Data Communication Company VN
213.186.33.19 OVH SAS FR
67.227.189.236 Liquid Web, L.L.C US
213.186.33.4 OVH SAS FR
154.0.169.106 AFRIHOST SP (PTY) LTD ZA
210.245.95.158 FPT Telecom Company VN

Attacking IPs

IP Source (ISP/ASN) Country
193.111.248.174 Ferdinand Zink trading as Tube-Hosting DE
103.161.34.10 GSJZ(CHINA)TECHNOLOGY CO.,LIMITED t/a Guosheng IDC lease DE
176.65.131.18 ZeXoTeK IT-Services GmbH DE
103.161.35.72 GSJZ(CHINA)TECHNOLOGY CO.,LIMITED t/a Guosheng IDC lease DE
193.111.248.216 Ferdinand Zink trading as Tube-Hosting DE
216.152.147.202 GTHost CA
84.247.184.254 Contabo GmbH FR
213.199.50.203 Contabo GmbH FR
192.227.173.60 HostPapa US
103.154.233.221 Netclues Technologies Private Limited IN
213.199.50.230 Contabo GmbH FR
213.199.50.178 Contabo GmbH FR
95.174.113.63 Consumer Internet Cooperative PG-19 RU
104.168.65.101 HostPapa US
45.153.34.104 TechTies Inc. NL
45.153.34.106 TechTies Inc. NL
198.23.197.71 HostPapa US
23.238.92.11 RackNerd LLC US
45.134.226.143 Contabo GmbH FR
146.70.87.165 M247 LTD Los Angeles Infrastructure US

Malware Hashes

Hash VT Detections Classification
eec5c6c219535fba3a0492ea8118b397 53/63 trojan.mirai/mozi
59ce0baba11893f90527fc951ac69912 42/61 trojan.mirai/mozi
31549917cdc6e3f9d40a48ea5998493f 56/67 adware.qjwmonkey/dangeroussig
8bdd2cdd39b2ad7b679faa50f629ce2b 29/62 phishing.akgpp/malurl
3849f30b51a5c49e8d1546960cc206c7 50/62 trojan.mirai/mozi
a73ddd6ec22462db955439f665cad4e6 49/62 trojan.mirai/mozi
796c596185e63803a4ec4003aa60f425 54/68 adware.qjwmonkey/bundler
d4f0c4ab122e0a7f27ba5864934a4ca8 35/64 trojan.sagnt/r002c0db526
dbc520ea1518748fec9fcfcf29755c30 45/62 trojan.mirai/ddos
fbe51695e97a45dc61967dc3241a37dc 47/62 trojan.mirai/mozi
c0fd19c0e4a252efb1864b267fb154ae 53/70 adware.ababsoftware/downloadasist
cbcb58ffe45c202c11bcf2070496aed6 56/67 trojan.cugn/nsis
96dd80012c33291e1621b66f5bd66967 61/69 adware.qjwmonkey/bundler
5116812ebf7d518f7776a1500a26296c 40/64 trojan.mirai/gafgyt
5294f25631d20b68ebf3a9acd4cc1f5d 33/64 trojan.malpack/rootkit
595486a5108206c8bc47b92592b83e28 37/63 trojan.mirai/dirtyfrag
5dfc3eefe1c51312d0020910020c4025 55/67 adware.qjwmonkey/nezchi
0c00a35e30cf2583d06c3a795ee1f0f3 43/71 trojan.webwatcher/occamy
cc354e0cd2cfde3c80a17ead892ea48e 38/63 trojan.mirai/usbli326
afbefb79120fd5d265e6a727825919e8 37/63 trojan.mirai/dirtyfrag

To learn more about how we collect, analyze, and deliver actionable threat intelligence, explore our Threat Intelligence Services. If you’re interested in running your own queries – whether for threat actors, CVEs, infrastructure, or emerging activity – see how our MCP Server helps turn intelligence into practical security insight. Both are designed to support real-world analysis, investigation, and decision-making.

Take advantage of our free threat intel trial.

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Threat Trends Digest – May 2026

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Welcome to the Threat Trends Digest, a monthly view of real-world threat patterns.

This report compiles data from the previous month using Malware Patrol’s global telemetry and live attack observations to surface key stats on malware, phishing, ransomware, C2s, and domain generation algorithms (DGAs). You’ll find insights into the most exploited TLDs, frequently seen malware hashes and IPs, and other critical indicators. Use this digest to keep a close pulse on attacker behavior, uncover shifting patterns, and better align your defenses with the latest threat activity.

For more articles, check out our #onpatrol4malware blog.

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IOCs

Top Malicious IPs

IP

Source (ISP/ASN)

106.41.200.151 ChinaNet Hunan Province Network / AS4134
140.82.116.4 Github IP
185.199.111.133 Github IP
185.199.109.133 Github IP
70.40.210.164 VPN/Data Center IP
206.72.194.50 VPN/Data Center IP
74.115.51.8 Weebly Inc. / AS27647
74.115.51.9 Weebly Inc. / AS27647
64.40.13.26 GlobalHostingSolutions Inc  / AS395512
77.65.212.167 Progreso.pl SP Z O.O / AS210379
87.98.239.3 VPN/Data Center IP
162.214.80.24 VPN/Data Center IP
64.37.63.18 VPN/Data Center IP
104.18.43.151 Cloudflare IP Range
213.186.33.19 VPN/Data Center IP
160.22.122.114 Ionsite Software One Member Co Ltd / AS135918
217.182.30.109 VPN/Data Center IP
5.223.56.39 VPN/Data Center IP
188.241.222.214 Awesome Projects S.R.L. / AS5606
43.231.112.25 Apartment # 34, 2nd khoroo / AS63962
Summary
  • Malicious infrastructure is heavily concentrated in hosting, cloud, VPN, and proxy networks, with approximately 40–45% of the IPs originating from VPN/data center providers. This is consistent with infrastructure commonly used to host:
    • Malware payloads / Ransomware staging servers / Phishing kits / C2 systems / Cryptomining operations / DGA-related infrastructure
  • Several IPs originate from major cloud and developer platforms, including GitHub and Cloudflare, highlighting a common adversary tactic of abusing trusted services to distribute malware, host malicious content, or conceal attacker infrastructure behind reputable providers.
  • Overall, the dataset reinforces a common modern threat trend: attackers increasingly rely on cloud services, VPS providers, VPN networks, and short-lived rented infrastructure to host and rotate malware, phishing, ransomware, and C2 operations while blending into legitimate internet traffic.

Top Attacking IPs

IP

Source (ISP/ASN)

103.161.34.10 Guosheng IDC Lease / AS198584
103.161.35.72 Guosheng IDC Lease / AS198584
80.75.212.112 Tube Hosting / AS49581
176.65.131.18 Zexotek IT-Services GmbH / AS198584
80.75.212.67 Tube Hosting / AS49581
130.12.183.13 Netiface LLC / AS51396
45.153.34.104 VMHeaven.io / AS51396
172.245.75.28 VPN/Data Center IP
103.157.26.137 PT Linkgo Metro Teknologi / AS141107
172.245.75.11 VPN/Data Center IP
162.248.101.69 Galaxygate, LLC / AS397031
51.75.104.160 VPN/Data Center IP
185.119.90.69 United Internet Ltd. / AS207604
173.249.209.8 VPN/Data Center IP
135.148.160.225 VPN/Data Center IP
94.46.187.205 VPN/Data Center IP
185.103.255.38 IP Market – FZCO / AS200740
80.75.212.28 Tube Hosting / AS49581
185.214.10.121 365 Group LLC / AS202602
161.97.91.164 VPN/Data Center IP
 
Summary
  • ~35–40% of the IPs are identifiable VPN or data center addresses, a pattern commonly associated with:
    • Credential stuffing campaigns / SSH brute-force / Automated exploit frameworks / Anonymized attack infrastructure
  • The concentration of hosting-provider IPs strongly suggests largely automated activity, including:
    • Internet-wide scanning / Bot-driven reconnaissance / Credential harvesting attempts / Proxy/VPN-based attacks / Security research scanning / Commodity malware operations
  • Overall, the data reflects opportunistic internet “background noise” and automated threat activity, highlighting the continued prevalence of large-scale reconnaissance and brute-force operations targeting exposed services.

Top Malware Hashes

Hash

VirusTotal Detections

VirusTotal Label

31549917cdc6e3f9d40a48ea5998493f 61/75 adware.qjwmonkey/dangeroussig
59ce0baba11893f90527fc951ac69912 51/75 trojan.mirai/mozi
8bdd2cdd39b2ad7b679faa50f629ce2b 28/75 phishing.akgpp/malurl
3849f30b51a5c49e8d1546960cc206c7 51/75 trojan.mirai/mozi
eec5c6c219535fba3a0492ea8118b397 54/75 trojan.mirai/mozi
a73ddd6ec22462db955439f665cad4e6 51/75 trojan.mirai/mozi
796c596185e63803a4ec4003aa60f425 56/75 adware.qjwmonkey/bundler
c0fd19c0e4a252efb1864b267fb154ae 53/75 adware.ababsoftware/downloadasist
96dd80012c33291e1621b66f5bd66967 62/75 adware.qjwmonkey/bundler
a9438d893c19d866cf720a581c9476bc 65/75 virus.tenga/remoteexec
64eb7ad3aaf9b6639ccc5c0b30b6e59f 58/75 trojan.msil/powershell
fbe51695e97a45dc61967dc3241a37dc 50/75 trojan.mirai/mozi
5dfc3eefe1c51312d0020910020c4025 56/75 adware.qjwmonkey/nezchi
9b6c3518a91d23ed77504b5416bfb5b3 51/75 trojan.hajime/mirai
724f25e7f93eae0ae54a80142e11b7ef 39/75 trojan.sshdoor/abtrojan
5377e8f2ebdb280216c37a6195da9d6c 47/75 trojan.hajime/mirai
9f35fd3bcbc01b097602dbd85d6ecfbb 21/75 trojan.msil/powershell
936b35bfee8232f437bf6b46e88401dd 41/75 trojan.sshdoor/sshdkit
e4f0fc29322640a13934b97c788dd4d5 40/74 trojan.lazy/misc
f7459bc26baf2db287c39770f6a1e19c 34/75 trojan.mirai/awtg

To learn more about how we collect, analyze, and deliver actionable threat intelligence, explore our Threat Intelligence Services. If you’re interested in running your own queries – whether for threat actors, CVEs, infrastructure, or emerging activity – see how our MCP Server helps turn intelligence into practical security insight. Both are designed to support real-world analysis, investigation, and decision-making.

Take advantage of our free threat intel trial.

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Threat Trends Digest – February 2026

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Welcome to the Threat Trends Digest, a monthly view of real-world threat patterns.

This report compiles data from the previous month using Malware Patrol’s global telemetry and live attack observations to surface key stats on malware, phishing, ransomware, C2s, and domain generation algorithms (DGAs). You’ll find insights into the most exploited TLDs, frequently seen malware hashes and IPs, and other critical indicators. Use this digest to keep a close pulse on attacker behavior, uncover shifting patterns, and better align your defenses with the latest threat activity.

For more articles, check out our #onpatrol4malware blog.

January Threat Trends
January Threat Trends
January Threat Trends
January Threat Trends
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IOCs

Top Malicious IPs

74.115.51.9
213.186.33.16
66.147.242.174
104.21.65.87
172.67.189.179
211.97.84.77
198.23.50.111
8.218.200.39
213.186.33.17
149.56.178.73
95.173.180.244
54.83.252.56
67.20.113.17
82.165.181.201
116.196.150.210
169.150.221.147
142.4.17.174
173.231.196.56
64.37.63.18
60.31.192.68

Top Malware Hashes

59ce0baba11893f90527fc951ac69912
8bdd2cdd39b2ad7b679faa50f629ce2b
3849f30b51a5c49e8d1546960cc206c7
eec5c6c219535fba3a0492ea8118b397
a73ddd6ec22462db955439f665cad4e6
ecf47832c60945488d601012e568b663
3a8e23ef4cc9578a00b292323579b4d4
5377e8f2ebdb280216c37a6195da9d6c
fbe51695e97a45dc61967dc3241a37dc
9b6c3518a91d23ed77504b5416bfb5b3
3a9349af006440c7e0da677724551239
d65960b89e28e465691ed757a2fdec2a
9fa84266be8c795dc61dd60fd5c1567c
c210a847989f7e47e7569ce1df92ae9e
724f25e7f93eae0ae54a80142e11b7ef
dbc520ea1518748fec9fcfcf29755c30
0b0212e124390ff12d9c04a483e2334e
ad6a76af945f652961da68bf364cdde1
cbcb58ffe45c202c11bcf2070496aed6
cb41caac2b6d810837618e153dfc3cc5

Top Attacking IPs

176.65.128.158
84.247.147.74
60.251.54.203
23.137.105.55
154.26.139.222
84.247.147.209
161.97.115.157
95.174.113.63
45.153.34.104
45.153.34.106
34.80.38.201
84.247.147.238
161.97.117.226
173.249.17.160
36.102.207.194
82.197.69.32
84.247.147.68
173.249.25.37
207.180.221.87
173.249.29.134

To learn more about how we collect, analyze, and deliver actionable threat intelligence, explore our Threat Intelligence Services. If you’re interested in running your own queries – whether for threat actors, CVEs, infrastructure, or emerging activity – see how our MCP Server helps turn intelligence into practical security insight. Both are designed to support real-world analysis, investigation, and decision-making.

Take advantage of our free threat intel trial.

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Threat Trends Digest – January 2026

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Welcome to the Threat Trends Digest, a monthly view of real-world threat patterns.

This report compiles data from the previous month using Malware Patrol’s global telemetry and live attack observations to surface key stats on malware, phishing, ransomware, C2s, and domain generation algorithms (DGAs). You’ll find insights into the most exploited TLDs, frequently seen malware hashes and IPs, and other critical indicators. Use this digest to keep a close pulse on attacker behavior, uncover shifting patterns, and better align your defenses with the latest threat activity.

For more articles, check out our #onpatrol4malware blog.

January Threat Trends
January Threat Trends
January Threat Trends
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IOCs

Top Malicious IPs

91.238.72.69
120.138.9.38
103.15.20.10
81.91.85.141
176.53.12.17
43.231.112.25
45.114.225.27
46.59.86.3
72.9.148.195
163.44.198.41
192.250.229.213
31.31.198.199
203.175.8.87
194.93.14.42
198.187.31.106
95.173.180.70
212.99.45.180
203.98.83.109
103.16.146.2
198.38.87.214

Top Malware Hashes

59ce0baba11893f90527fc951ac69912
8bdd2cdd39b2ad7b679faa50f629ce2b
3849f30b51a5c49e8d1546960cc206c7
a73ddd6ec22462db955439f665cad4e6
eec5c6c219535fba3a0492ea8118b397
fbe51695e97a45dc61967dc3241a37dc
9b6c3518a91d23ed77504b5416bfb5b3
3a9349af006440c7e0da677724551239
5377e8f2ebdb280216c37a6195da9d6c
724f25e7f93eae0ae54a80142e11b7ef
dbc520ea1518748fec9fcfcf29755c30
221d8352905f2c38b3cb2bd191d630b0
cbcb58ffe45c202c11bcf2070496aed6
b8ed2cb3e9fedec5b164ce84ad5a08d0
6a16e166948ddb9e6e9f9de503e21c60
fd28239ca545da6ae157a6c7ab14dbf0
ebbcfb749a959fb53e9fc8b6dc915838
c3c561c20e48169f4906c6b0b135984b
936b35bfee8232f437bf6b46e88401dd
5f49ac82edd8f3a3d7c47746b6523de9

Top Attacking IPs

80.75.212.112
205.209.119.82
85.192.63.30
80.75.212.116
80.75.212.126
162.220.15.190
162.220.15.170
193.141.60.60
130.12.183.19
134.209.37.214
69.164.255.130
65.109.32.114
20.12.212.103
204.76.203.223
65.108.231.96
38.190.177.184
135.181.128.54
65.21.123.25
142.132.220.146
65.108.120.126

To learn more about how we collect, analyze, and deliver actionable threat intelligence, explore our Threat Intelligence Services. If you’re interested in running your own queries – whether for threat actors, CVEs, infrastructure, or emerging activity – see how our MCP Server helps turn intelligence into practical security insight. Both are designed to support real-world analysis, investigation, and decision-making.

Take advantage of our free threat intel trial.

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Predicting Cyber Fraud Through Real-World Events: Insights from Domain Registration Trends

Malware Patrol recently partnered with Cisco’s SURGe Team to investigate how cybercriminals exploit newly registered domains (NRDs) for fraud during major geopolitical events. While we’ve offered NRD data for several years and know firsthand how powerful it is for uncovering malicious activity, the sheer volume of data – 200,000+ domains per day – makes it rather difficult to explore and manipulate it in meaningful ways without the right tooling and know-how. Thankfully, the knowledgeable SURGe team and Splunk Enterprise enabled us to slice and visualize a whopping two and a half years’ worth of newly registered domains in myriad ways, helping us surface patterns, trends, and supporting statistics that would have been hard to see otherwise. We’d like to express our appreciation to their team, namely: Lauren Stemler, Ryan Fetterman, James Hodgkinson and Vandita Anand.

In short, by retroactively aligning NRD activity with a timeline of key geopolitical events, we were able to validate that this data is extremely useful for spotting threats and cybercrime infrastructure. And while our analysis looked backward, the same logic applies going forward: using current newly registered domains data in near real time can help surface burgeoning campaigns and fraud as geopolitical events unfold. We hope this research helps security teams see new ways to make use of NRD data to protect against emerging threats, or at least underscores that the intersection of geopolitics and domain registrations is an important signal they shouldn’t ignore.

The original article appears on their site.

Predicting Cyber Fraud Through Real-World Events: Insights from Domain Registration Trends

Events in the physical world influence the digital world. In the wake of major geopolitical events, attackers register new domains and infrastructure to support fraudulent activities. These domains come in many forms, for example, posing as a natural disaster relief fund to solicit donations, collecting interest in a crypto coin offering, or creating a fake auto insurance website. Large-scale newly registered domain (NRD) analysis reveals consistent patterns in this behavior, allowing us to predict attacker activity long before associated fraud becomes visible.

To demonstrate the relationship between these physical and digital events, Cisco’s SURGe Team and Malware Patrol analyzed more than 200 million historical NRD records in Splunk Enterprise. Since most cyber campaigns require supporting infrastructure, NRDs offer a useful signal of malicious intent. By examining domain registration patterns around key U.S. events from 2023 to mid 2025, specifically in cryptocurrency, natural disasters, and financial sectors, we aimed to identify trends that connect real-world disruption with spikes in suspicious digital activity. This work offers practical insights for defenders seeking to anticipate and analyze fraud tied to geopolitical developments.

Understanding the Link Between Headlines and Cyber Threats

We began our research effort by building a comprehensive list of major breaking news events from January 2023 through August 2025, then narrowed our focus to events with clear opportunities for financially motivated cybercrime, prioritizing situations where adversaries could exploit urgency or heightened interest to obtain money or sensitive information. This prioritization process led to three event categories where attackers create infrastructure in response to real-world developments: cryptocurrency, financial (non-crypto), and natural disasters.
After selecting these three categories, we expanded each into a detailed event timeline. For cryptocurrency, this included Bitcoin price milestones, regulatory shifts, and exchange-related news. For financial events, we incorporated interest rate decisions, market volatility, earnings reports, and tariff/policy announcements. For natural disasters, we tracked hurricanes, wildfires, tornado outbreaks, floods, and severe weather systems. Each event was assigned a time window to allow consistent comparison against NRD activity.

Inside the Dataset: What 213 Million New Domain Registrations Reveal

Our analysis relied on Malware Patrol’s global NRD dataset, which contains more than 213 million domain registrations for the selected period. Each record contains metadata including timestamp, Top-Level Domain (TLD), hosting information, and historical indicators that can be used towards fraud classification. To isolate patterns tied to geopolitical events, we developed custom keyword and regex-based classifiers to tag domains relevant to cryptocurrency, natural disasters, and financial markets.

newly registered domains statistics

Splunk Enterprise’s large-scale search and visualization capabilities allowed us to detect anomalies, compare category-level trends against global baselines, and identify moments where domain activity sharply diverged from normal behavior. NRD data does not capture all malicious infrastructure, but it can expose the earliest stages of fraud campaigns.

Detecting Event-Driven Patterns

With this dataset mapped and categorized, the next step was to determine whether meaningful patterns emerged around real-world events. To explore this idea, we used various types of data analysis, combining event volume, fraud rate, and applying Natural Language Processing techniques to intuit the meaning behind the data.

We generated time charts of domain registration activity within each category, and across the full timeframe, measuring activity to identify statistical anomalies using rolling sensitivity bands.

The peaks and valleys of our time charts were aligned with our documented timelines of significant events to look for co-occurrences where we can retroactively confirm significant fraud activity occurred.

Semantic Shift: How is keyword use changing over time?

The volumetric and fraud-rate analyses showed when unusual behavior occurred within a category of interest, but not what attackers were trying to exploit. To capture language-specific changes, we conducted a semantic shift analysis, which would reflect how the language of newly registered domains within a category of interest changed over time.

We parsed each domain into meaningful tokens removing TLDs and subdomains, splitting on punctuation, and digits, segmenting fused words, and removing boilerplate stop words (extremely common words like “a,” “the,” “is,” are filtered out because they have little semantic value on their own). Token counts were aggregated monthly to form a month-by-term frequency matrix. We then converted this matrix into TF-IDF vectors so that each month was represented by its characteristic vocabulary rather than raw frequency dominated by common terms.

To visualize how that vocabulary changed, we projected the monthly TF-IDF vectors into two dimensions using t-SNE. Plotting them chronologically produced a trajectory in which nearby points reflected similar keyword distributions, while long jumps indicated major shifts in attacker themes.

We interpreted these jumps by reviewing top-ranked terms each month and, when useful, examining cosine distances and keyword heatmaps. For example, between December 2024 and January 2025, in the natural disaster category, new terms such as “rebuild,” “wildfire,” “disaster,” “la,” and “firestorm” suddenly became dominant, with “supplies” and “emergency” rising sharply as well. This shift aligned precisely with the Palisades Fire (discussed below) and appeared clearly in the semantic trajectory even before drilling into individual domains.

This natural language analysis, combined with event tagging, anomaly detection, and fraud-rate modeling, helped reveal not only when domain activity spiked in response to real-world events, but how attacker intent and focus changed in measurable ways.

Key Finding #1 Real-world crises create immediate and measurable spikes in fraudulent domain activity

Natural disaster–related domains represent the smallest subset of the study’s tagged NRDs, averaging 313 domains per day. Despite the lower volume, some important insights can be gained from this category due to its event-driven fluctuations. Natural disasters offer one of the clearest demonstrations of how quickly attackers capitalize on real-world crises.

One event that clearly illustrates this pattern is The January 2025 Palisades Fire in Los Angeles County – one of the most destructive and costly wildfire events in recent U.S. history. Within hours of the first evacuation alerts, our data showed a sudden surge in newly registered domains referencing the fire, Los Angeles, relief efforts, or related humanitarian themes. As the fire intensified over the following days, malicious activity grew alongside it.

Attackers registered domains impersonating relief organizations, emergency resource hubs, and donation portals, rapidly deploying infrastructure to exploit public confusion and urgency.

newly registered domains related to natural disasters

Attackers also blended in more modern lures, including Solana-themed “wildfire relief” tokens and fake cryptocurrency airdrops. Several domain clusters were bulk-registered with identical landing pages designed to harvest email addresses for later phishing campaigns, an increasingly common pattern in crisis-driven fraud. For more information on the most common attack techniques being observed, please check out the Cisco Talos Year in Review Report.

The language embedded in these domains provided further evidence. Using our semantic-shift analysis, we observed a sudden rise in tokens such as “wildfire,” “firestorm,” “lafire,” “supplies,” “donate,” and “emergency”, terms that were largely absent from the dataset just one month prior. January 2025 became the clear high-water mark for natural disaster–related domain registrations in the entire two-year period, and a significant outlier compared to overall NRD activity and the baseline growth trends of other event categories.

Viewed alongside earlier case studies, the Palisades Fire reinforces a broader pattern: real-world shocks produce immediate, measurable spikes in attacker infrastructure. Unlike crypto or financial events, which often generate longer-term waves of fraud, disaster-driven domain activity is sudden and closely tied to public attention cycles. The rapid registration of look-alike donation sites, emergency-aid portals, and geographically themed domains demonstrates how quickly threat actors mobilize when people are most vulnerable. For defenders, this means disaster-driven fraud often materializes before the public fully understands the scale of the event.

Key Finding #2: Crypto events produce the highest fraud volume and the longest-lasting impact.

While natural disasters trigger short-lived bursts of attacker activity, cryptocurrency events generate more persistent waves of fraud. Across the entire dataset, crypto-related domains represented the largest event-linked category and consistently showed the highest fraud prevalence. This pattern coincided with major market and regulatory milestones. One of the most significant upticks occurred in March 2024, when Bitcoin surpassed its previous all-time high. In the days surrounding this event, our dataset recorded one of the largest domain registration spikes in the two-year period, with newly created domains referencing Bitcoin, wallets, exchanges, investment platforms, and token names far exceeding upper sensitivity thresholds.

Unlike natural-disaster spikes, crypto activity didn’t return to baseline. Instead, March 2024 marked the beginning of a new elevated period that persisted throughout late 2024 and well into 2025. One of our hypotheses prior to starting analysis was that the recent positive changes in the regulatory environment in the U.S. would create more opportunities for crypto-related fraud. These events, for example include:

  • January 10, 2024: the SEC approved the first 11 Bitcoin exchange-traded products (ETFs/ETPs) in the U.S. These ETFs provide investors with direct exposure to Bitcoin’s price movements without the need to buy, store, or manage Bitcoin personally.
  • March 6, 2025: The U.S. signed an executive order establishing a strategic bitcoin reserve, specifically naming Bitcoin, Ethereum, XRP, Solana, and Cardano currencies.
  • March 28, 2025: The U.S. FDIC rescinded its 2022 letter that required banks to notify and obtain prior approval for crypto activities. At this point, FDIC-supervised may engage in permissible crypto activities without prior approval.
  • July 18, 2025: The U.S. approves the Guiding and Establishing National Innovation for U.S. Stablecoins (GENIUS act). This legislation continued to signal the trend that cryptocurrencies would be regulated, including reserve rules and marketing standards.

These developments drew millions of new and inexperienced users into the market, widening the pool of potential victims. Attackers responded by registering domains that impersonated exchanges, mimicked customer dashboards, hosted fake wallet downloads, and advertised fraudulent staking or investment opportunities.

The rise in pig-butchering operations during this period further illustrates how attackers adapted to this influx of new users. These long-con social engineering schemes rely on building trust with victims over weeks or months before steering them toward fabricated crypto-investment platforms. Crypto fraud was not only quick-hit phishing attempts, but attackers were playing the long game of establishing trust between themselves and their victims.

Since crypto coin scams often involve multiple domains on shared infrastructure, we used known fraud IOCs to hunt for clusters of other probable fraud activity. Building on a list of initial IOCs we have created flexible categories for capturing common memecoin related themes, and then bucket the category count to give us a variety of sorting options for investigating the data:

The resulting output aggregates suspicious categories as a distinct count and can be used to review values of domain names sharing IP space with known fraud sites.

While U.S. regulation has helped legitimize cryptocurrencies in the past years, investors should consider any investment opportunities advertised in this realm with healthy skepticism and due diligence. The FBI cites increased risk of scam for companies that are not part of self-regulatory organizations like the National Futures Association or FINRA.

Key Finding #3: Economic Fears Supercharge Uncertainty & Cyber Crime

In the financial (non-crypto) category, one of the strongest domain registration surges occurred in March 2024, during a period of heavy U.S. news coverage about increased cost of living and rising insurance costs. As we examined the data, a clear pattern emerged: insurance-related keywords began increasing frequency as early as February and reached a peak in April.

From January through April 2024, U.S. national news outlets repeatedly highlighted double-digit increases in auto-insurance rates, numerous hospital and insurer contract disputes, as well as claims & prior-authorization denial controversies, were publicized. Additionally, Centers for Medicare & Medicaid Services (CMS) confirmed a 2025 premium increase (3.7%) for Medicare Advantage. This sustained narrative produced high consumer awareness and uncertainty, resulting in the kind of environment scammers reliably exploit to deploy convincing insurance-themed phishing, refund fraud, fake coverage notifications, eligibility-verification fraud, and fake insurer-comparison websites.

In the data, we observed a shift in the domains being registered during this period. Insurance-related terms such as “insurance,” “rate,” “car,” “Medicare,” “renew,” and “health” appeared with increasing frequency. We also observed clusters using commonly abused TLDs (.xyz, .site, .online, .buzz, .bond), consistent with disposable phishing infrastructure. Numerous domains were generic or service-oriented (e.g., “insurance,” “health insurance,” “getinsurance,” “ethical insurance”), typical of phishing, scam, or fraud-oriented lures targeting people seeking coverage.

March 2024 – Volume Precedes Focused Campaigns

The data from March mirrors the rise in general financial-services domain creation during ongoing tax-season fraud, refund scams, and credit-repair themes while also demonstrating a strong overlap with the insurance-related narratives that were entering peak national coverage.

• car-insurance-47993.bond (multiple sequential variants)
• health-insurance-19289.bond (multiple sequential variants)
• insuranceconcierge.expert, insuranceconcierge.guru (bulk-pattern cluster)
• betterinsurancerate.net
• insurebestrateusa.info
• auto-insurance-deals.shop
• autoinsurancefind.today
• plansmedicare.org
• fullycoveredinsurance.com

April 2024 – A Surge in Insurance-Specific Keywords

Despite March’s higher overall volume, April produced significantly more domains containing insurance-trigger keywords:
• autoinsuranceforseniors204203.life (multiple sequential variants)
• accident-insurance-15849.bond (multiple sequential variants)
• getinsurance.pro
• governmentmedicalinsurance.com
• gov-insurance-now-8.live
• cheapautoinsurancetip.top
• cheapcarinsurancenet.top
• health-insurance-12396.bond (multiple sequential variants)
• insuranceforseniorsite.com
• medical-insurance122.online (multiple sequential variants)
• middle-agedandelderlyinsurance991.online (multiple sequential variants)
• senior-car-insurance-20352.bond (multiple sequential variants)
• americanmedicarequote.com, americanmedicarequotes.com
• medicareformedicare.site, medicare-plans-help.today
• the-car-insurance030.site (multiple sequential variants)

As a point of interest, April’s activity showed more diverse insurance subcategories (auto, medical, Medicare, homeowners, cyber, senior, contractor), suggesting that the campaigns were directly “riding” the elevated media noise from the preceding months. There were also more bulk/cluster registration patterns in April’s data, a possible indication of heightened (or peak) malicious campaign activity.
Our analysis indicates that both the March 2024 financial-domain surge and the insurance-specific increase in April can likely be explained by the compounding effect of January to March news cycles. The steady stream of headlines created fertile ground for threat actors to exploit confusion around benefits, coverage options, and plan updates.

Cross-Category Comparison: How Each Event Type Behaves in the Data

Since the scale of each category of interest is different, for a direct side-by-side comparison, we instead tracked the relative growth of each category. Each line starts at 100 for the first month; rising to 150 means +50% vs its own baseline. The tight tracking of these lines shows how each category is still influenced by macro-level trends, and deviations from the cohort overall are more notable.

As a grouped category, crypto-related domains had the highest fraud rate, of 26.86%, well above the global baseline of 23.10%. While the Natural Disaster category is much smaller in daily volume, it produces the sharpest short-term deviations and is easier to track trends without detailed keywords, compared to the financial categories. Fraud rates for Natural Disasters were also elevated to 24.26%. Financial (non-crypto) events tend to create modest increases in suspicious domain activity. Fraud rates for this category average 23.69%, slightly higher than the global baseline. Our categorization of ‘fraud’ for these purposes included any historical hosting of malware, domain generation algorithms, or command-and-control infrastructure. Since this reputation is IP-based, we expect the rate of fraud domains (many of which can be hosted on the same IP) to be potentially inflated and not representative of the true global rate of fraudulent domains.

Conclusions: Turning Event Awareness into Early Action

Attacker infrastructure frequently appears within hours or days of major real-world events, which means defenders benefit from treating external developments as operational signals. Incorporating event awareness into threat intelligence workflows begins with tracking high-impact geopolitical and economic activity and prioritizing the events most relevant to your sector or user base.

Once relevant events are identified, teams can determine which organizations or services attackers are most likely to impersonate. Converting those likely targets into keyword patterns makes NRD monitoring more effective, allowing clusters of newly registered domains to surface as early indicators of staging activity. Domains using unusual TLDs, typosquatting, or obfuscated permutations (for example, govuk-verify[.]info or unhcr-supp0rt[.]org) can then be evaluated against known threat-actor behaviors to assess whether they align with phishing kits or previously observed campaigns.

Adding contextual tags, such as the associated event, likely “spoofed entity”, or “suspected TTP”, helps SOC analysts and threat hunters pivot on related domains more effectively. Certificate metadata and sandboxing results provide additional signals to distinguish benign alerts from malicious activity. Feeding this enriched context into a SIEM or TIP allows detections to operate faster and with greater precision.

These findings highlight that NRD monitoring is a reliable early indicator of cybercrime taking shape. By pairing domain trends with current events, defenders can anticipate the kinds of lures and impersonation themes that are likely to emerge next. Building this context into threat intelligence programs helps teams detect malicious infrastructure earlier, prioritize investigations more effectively, and prepare for incoming campaigns rather than reacting after the fact. As cybercriminals align their operations with real-world disruptions, adopting event-driven threat intelligence is essential for staying ahead.

Credit to authors and collaborators: Lauren Stemler (Splunk / SURGe), Ryan Fetterman (Splunk / SURGe), James Hodgkinson (Splunk / SURGe) and Vandita Anand (Splunk / SURGe), Andre Correa (Malware Patrol), Leslie Dawn (Malware Patrol).

 

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