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Analyze » Dawson James Securities, Inc. » DAW1770631199

Incident Score: Analysis & Impact (DAW1770631199)

The details regarding individual company incidents & reports gives you full view from every side.

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-22
Company Score Before Incident690 / 1000
Company Score After Incident668 / 1000
INCIDENT NUMBERDAW1770631199
Type of Cyber IncidentCyber Attack
ATTACK VECTORexposed Docker APIs, Kubernetes clusters, Ray dashboards, Redis servers, React2Shell vulnerability (CVE-2025-55182)
DATA EXPOSEDCV databases, identity records, corporate...
INCIDENT DATE24/12/2025
STATUSpublished

Key Highlights From The Incident Analysis

  • Timeline of Dawson James Securities, Inc.'s Cyber Attack and lateral movement inside company's environment.
  • Overview of affected data sets, including SSNs and PHI, and why they materially increase incident severity.
  • How Rankiteo’s incident engine converts technical details into a normalized incident score.
  • How this cyber incident impacts Dawson James Securities, Inc. Rankiteo cyber scoring and cyber rating.
  • Rankiteo’s MITRE ATT&CK correlation analysis for this incident, with associated confidence level.

Full Incident Analysis Transcript

In this Rankiteo incident briefing, we review the Dawson James Securities, Inc. breach identified under incident ID DAW1770631199.

The analysis begins with a detailed overview of Dawson James Securities, Inc.'s information like the linkedin page: https://www.linkedin.com/company/dawson-james-securities, the number of followers: 793, the industry type: Investment Banking and the number of employees: 46 employees

After the initial compromise, the video explains how Rankiteo's incident engine converts technical details into a normalized incident score. The incident score before the incident was 690 and after the incident was 668 with a difference of -22 which is could be a good indicator of the severity and impact of the incident.

In the next step of the video, we will analyze in more details the incident and the impact it had on Dawson James Securities, Inc. and their customers.

On 25 December 2025, a cybersecurity incident called "TeamPCP Launches Large-Scale Cloud-Native Cybercrime Campaign" came to light.

Cybersecurity researchers have uncovered a worm-driven campaign orchestrated by the threat group TeamPCP (also known as DeadCatx3, PCPcat, PersyPCP, and ShellForce), which has systematically targeted cloud-native environments to establish malicious infrastructure for follow-on...

The disruption is felt across the environment, affecting cloud-native environments, AWS environments and Microsoft Azure environments, and exposing CV databases, identity records and corporate files.

Formal response steps have not been shared publicly yet.

Overall, the incident is a reminder of why proactive monitoring and strong governance matter.

Finally, we try to match the incident with the MITRE ATT&CK framework to see if there is any correlation between the incident and the MITRE ATT&CK framework.

The MITRE ATT&CK framework is a knowledge base of techniques and sub-techniques that are used to describe the tactics and procedures of cyber adversaries. It is a powerful tool for understanding the threat landscape and for developing effective defense strategies.

MITRE ATT&CK® Correlation Analysis

Rankiteo's analysis has identified several MITRE ATT&CK tactics and techniques associated with this incident, each with varying levels of confidence based on available evidence. Under the Initial Access tactic, the analysis identified Exploit Public-Facing Application (T1190) with high confidence (90%), supported by evidence indicating exposed Docker APIs, Kubernetes clusters, Ray dashboards, Redis servers, External Remote Services (T1133) with moderate to high confidence (80%), supported by evidence indicating exploits misconfigurations and known vulnerabilities in cloud-native environments, and Exploitation of Remote Services (T1210) with high confidence (90%), supported by evidence indicating react2Shell vulnerability (CVE-2025-55182, CVSS 10.0). Under the Execution tactic, the analysis identified Command and Scripting Interpreter (T1059) with high confidence (90%), supported by evidence indicating scanner.py, kube.py, react.py, pcpcat.py automate exploitation and payload deployment, Container Administration Command (T1609) with moderate to high confidence (80%), supported by evidence indicating deploys malicious containers with Base64-encoded payloads via exposed Docker APIs, and Deploy Container (T1610) with moderate to high confidence (80%), supported by evidence indicating malicious containers deployed via pcpcat.py and proxy.sh. Under the Persistence tactic, the analysis identified Escape to Host (T1611) with moderate to high confidence (70%), supported by evidence indicating establishes persistent backdoors via privileged pods in Kubernetes and Server Software Component: Web Shell (T1505.003) with moderate confidence (60%), supported by evidence indicating proxy.sh performs environment fingerprinting and establishes backdoors. Under the Privilege Escalation tactic, the analysis identified Escape to Host (T1611) with moderate to high confidence (70%), supported by evidence indicating harvests Kubernetes cluster credentials and propagates across pods and Exploitation for Privilege Escalation (T1068) with moderate to high confidence (80%), supported by evidence indicating exploits React2Shell (CVE-2025-55182) for remote command execution. Under the Defense Evasion tactic, the analysis identified Obfuscated Files or Information (T1027) with moderate to high confidence (80%), supported by evidence indicating deploys Base64-encoded payloads via malicious containers and Hide Artifacts: Hidden Window (T1564.003) with moderate confidence (60%), supported by evidence indicating proxy.sh and scanner.py operate in background for infrastructure exploitation. Under the Credential Access tactic, the analysis identified Cloud Instance Metadata API (T1552.007) with moderate to high confidence (70%), supported by evidence indicating kube.py harvests Kubernetes cluster credentials. Under the Discovery tactic, the analysis identified Account Discovery (T1087) with moderate to high confidence (70%), supported by evidence indicating kube.py discovers Kubernetes resources and propagates across pods, Network Service Scanning (T1046) with high confidence (90%), supported by evidence indicating scanner.py scans for misconfigured Docker APIs and Ray dashboards, and Cloud Service Discovery (T1526) with moderate to high confidence (80%), supported by evidence indicating targets AWS and Microsoft Azure environments opportunistically. Under the Lateral Movement tactic, the analysis identified Lateral Tool Transfer (T1570) with moderate to high confidence (80%), supported by evidence indicating proxy.sh propagates across pods in Kubernetes clusters and Remote Services: Cloud Services (T1021.007) with moderate to high confidence (70%), supported by evidence indicating compromises cloud-native environments for follow-on exploitation. Under the Collection tactic, the analysis identified Data from Cloud Storage (T1530) with moderate to high confidence (80%), supported by evidence indicating cV databases, identity records, and corporate files compromised. Under the Command and Control tactic, the analysis identified Application Layer Protocol: Web Protocols (T1071.001) with moderate to high confidence (80%), supported by evidence indicating c2 server (67.217.57.240) linked to Sliver open-source C2 framework and Ingress Tool Transfer (T1105) with moderate to high confidence (70%), supported by evidence indicating deploys proxy, P2P, and tunneling utilities via proxy.sh. Under the Exfiltration tactic, the analysis identified Transfer Data to Cloud Account (T1537) with moderate to high confidence (80%), supported by evidence indicating stolen data published via ShellForce for ransomware and fraud and Exfiltration Over C2 Channel (T1041) with moderate to high confidence (70%), supported by evidence indicating data exfiltration via Sliver C2 framework. Under the Impact tactic, the analysis identified Resource Hijacking (T1496) with high confidence (90%), supported by evidence indicating cryptocurrency mining via mine.sh deployed by scanner.py, Data Encrypted for Impact (T1486) with moderate to high confidence (70%), supported by evidence indicating ransomware deployment as part of hybrid monetization model, and Defacement: External Defacement (T1491.002) with moderate confidence (60%), supported by evidence indicating stolen data published via ShellForce for extortion and reputation-building. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.

Initial Access
Exploit Public-Facing Application (90%)
External Remote Services (80%)
Exploitation of Remote Services (90%)
Execution
Command and Scripting Interpreter (90%)
Container Administration Command (80%)
Deploy Container (80%)
Persistence
Escape to Host (70%)
Server Software Component: Web Shell (60%)
Privilege Escalation
Escape to Host (70%)
Exploitation for Privilege Escalation (80%)
Defense Evasion
Obfuscated Files or Information (80%)
Hide Artifacts: Hidden Window (60%)
Credential Access
Cloud Instance Metadata API (70%)
Discovery
Account Discovery (70%)
Network Service Scanning (90%)
Cloud Service Discovery (80%)
Lateral Movement
Lateral Tool Transfer (80%)
Remote Services: Cloud Services (70%)
Collection
Data from Cloud Storage (80%)
Command and Control
Application Layer Protocol: Web Protocols (80%)
Ingress Tool Transfer (70%)
Exfiltration
Transfer Data to Cloud Account (80%)
Exfiltration Over C2 Channel (70%)
Impact
Resource Hijacking (90%)
Data Encrypted for Impact (70%)
Defacement: External Defacement (60%)

Sources & References