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Analyze » AWS Databases & Analytics » HUNAWS1772735373

Incident Score: Analysis & Impact (HUNAWS1772735373)

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

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-15
Company Score Before Incident778 / 1000
Company Score After Incident763 / 1000
INCIDENT NUMBERHUNAWS1772735373
Type of Cyber IncidentCyber Attack
ATTACK VECTORExploitation of CVE-2025-55182 (React2Shell framework), Stolen AWS access tokens
DATA EXPOSEDProprietary source code, Private keys,...
INCIDENT DATE14/01/2026
STATUSpublished

Key Highlights From The Incident Analysis

  • Timeline of AWS Databases & Analytics'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 AWS Databases & Analytics 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 AWS Databases & Analytics breach identified under incident ID HUNAWS1772735373.

The analysis begins with a detailed overview of AWS Databases & Analytics's information like the linkedin page: https://www.linkedin.com/company/aws-databases, the number of followers: 266687, the industry type: IT Services and IT Consulting and the number of employees: None 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 778 and after the incident was 763 with a difference of -15 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 AWS Databases & Analytics and their customers.

A newly reported cybersecurity incident, "North Korea-Linked Hackers Target Crypto Supply Chain in Coordinated Campaign", has drawn attention.

A sophisticated cyberattack campaign, attributed to North Korea-linked threat actors, has targeted multiple layers of the cryptocurrency supply chain, compromising staking platforms, exchange software providers, and exchanges themselves.

The disruption is felt across the environment, affecting Crypto staking platforms, Exchange software providers and Cryptocurrency exchanges, and exposing Proprietary source code, Private keys and Cloud-stored secrets.

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 exploiting CVE-2025-55182, a vulnerability in the React2Shell framework and Steal Application Access Token (T1528) with high confidence (90%), supported by evidence indicating leveraging stolen AWS access tokens to bypass initial exploitation. Under the Execution tactic, the analysis identified Command and Scripting Interpreter (T1059) with moderate to high confidence (80%), supported by evidence indicating grep searches to extract sensitive files like .pem, .key, and .ppk credentials and Container Administration Command (T1609) with moderate to high confidence (70%), supported by evidence indicating compromised Docker container images contained hardcoded database credentials. Under the Persistence tactic, the analysis identified Account Manipulation (T1098) with moderate to high confidence (70%), supported by evidence indicating pivoted into Kubernetes clusters by updating kubeconfig files and Server Software Component: Web Shell (T1505.003) with moderate to high confidence (80%), supported by evidence indicating deployed VShell on port 8082 for command-and-control. Under the Privilege Escalation tactic, the analysis identified Abuse Elevation Control Mechanism: Setuid and Setgid (T1548.001) with moderate confidence (60%), supported by evidence indicating access to Kubernetes Secrets and ConfigMaps in plaintext and Valid Accounts (T1078) with high confidence (90%), supported by evidence indicating stolen AWS access tokens used to infiltrate cloud infrastructure. Under the Defense Evasion tactic, the analysis identified Protocol Tunneling (T1572) with high confidence (90%), supported by evidence indicating used FRP as a tunneling proxy over port 53 (DNS), Proxy: Multi-hop Proxy (T1090.003) with moderate to high confidence (80%), supported by evidence indicating connections to primary VPS routed over IPv6 to bypass IPv4 detection, and Masquerading (T1036) with moderate to high confidence (70%), supported by evidence indicating vShell deployed on port 8082, evading standard network monitoring. Under the Credential Access tactic, the analysis identified Unsecured Credentials: Credentials In Files (T1552.001) with high confidence (90%), supported by evidence indicating stole .env files with hardcoded private keys, .pem, .key, and .ppk credentials, Unsecured Credentials: Cloud Instance Metadata API (T1552.005) with moderate to high confidence (70%), supported by evidence indicating broad enumeration of AWS EC2 instances, RDS databases, and S3 buckets, and Steal Application Access Token (T1528) with high confidence (90%), supported by evidence indicating stolen AWS access tokens used to directly infiltrate cloud infrastructure. Under the Discovery tactic, the analysis identified Account Discovery (T1087) with moderate to high confidence (80%), supported by evidence indicating broad enumeration of AWS EC2, RDS, S3, Lambda, and EKS clusters, File and Directory Discovery (T1083) with high confidence (90%), supported by evidence indicating grep searches to extract sensitive files like .pem, .key, and .ppk credentials, and Cloud Storage Object Discovery (T1619) with moderate to high confidence (80%), supported by evidence indicating downloaded Terraform state files storing infrastructure secrets. Under the Collection tactic, the analysis identified Data from Cloud Storage (T1530) with high confidence (90%), supported by evidence indicating exfiltrated ConfigMaps, Kubernetes Secrets, and Docker container images and Data from Local System (T1005) with moderate to high confidence (80%), supported by evidence indicating stole proprietary source code and private keys from compromised systems. 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 deployed VShell on port 8082 for command-and-control, Proxy: External Proxy (T1090.002) with high confidence (90%), supported by evidence indicating used FRP as a tunneling proxy over port 53 (DNS), and Non-Application Layer Protocol (T1095) with moderate to high confidence (70%), supported by evidence indicating connections routed over IPv6 to bypass IPv4 detection tools. Under the Exfiltration tactic, the analysis identified Transfer Data to Cloud Account (T1537) with moderate to high confidence (80%), supported by evidence indicating exfiltrated Kubernetes Secrets, ConfigMaps, and Docker images in plaintext and Exfiltration Over C2 Channel (T1041) with high confidence (90%), supported by evidence indicating theft of proprietary source code, private keys, and cloud-stored secrets. Under the Impact tactic, the analysis identified Resource Hijacking (T1496) with moderate to high confidence (70%), supported by evidence indicating 52.6 TRX transferred during exploitation window (potential crypto theft). 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%)
Steal Application Access Token (90%)
Execution
Command and Scripting Interpreter (80%)
Container Administration Command (70%)
Persistence
Account Manipulation (70%)
Server Software Component: Web Shell (80%)
Privilege Escalation
Abuse Elevation Control Mechanism: Setuid and Setgid (60%)
Valid Accounts (90%)
Defense Evasion
Protocol Tunneling (90%)
Proxy: Multi-hop Proxy (80%)
Masquerading (70%)
Credential Access
Unsecured Credentials: Credentials In Files (90%)
Unsecured Credentials: Cloud Instance Metadata API (70%)
Steal Application Access Token (90%)
Discovery
Account Discovery (80%)
File and Directory Discovery (90%)
Cloud Storage Object Discovery (80%)
Collection
Data from Cloud Storage (90%)
Data from Local System (80%)
Command and Control
Application Layer Protocol: Web Protocols (80%)
Proxy: External Proxy (90%)
Non-Application Layer Protocol (70%)
Exfiltration
Transfer Data to Cloud Account (80%)
Exfiltration Over C2 Channel (90%)
Impact
Resource Hijacking (70%)

Sources & References