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Analyze » Chem-Aqua, Inc. » GITCHE1774031536

Incident Score: Analysis & Impact (GITCHE1774031536)

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

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-19
Company Score Before Incident759 / 1000
Company Score After Incident740 / 1000
INCIDENT NUMBERGITCHE1774031536
Type of Cyber IncidentCyber Attack
ATTACK VECTORCompromised GitHub repositories (force-pushed version tags)
DATA EXPOSEDCI/CD secrets, SSH keys, cloud...
INCIDENT DATE28/02/2026
STATUSOngoing (attribution unconfirmed)

Key Highlights From The Incident Analysis

  • Timeline of Chem-Aqua, 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 Chem-Aqua, 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 Chem-Aqua, Inc. breach identified under incident ID GITCHE1774031536.

The analysis begins with a detailed overview of Chem-Aqua, Inc.'s information like the linkedin page: https://www.linkedin.com/company/chem-aqua, the number of followers: 50906, the industry type: Chemical Manufacturing and the number of employees: 927 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 759 and after the incident was 740 with a difference of -19 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 Chem-Aqua, Inc. and their customers.

Aqua Security recently reported "Trivy Open-Source Scanner Compromised Again in Supply Chain Attack", a noteworthy cybersecurity incident.

Aqua Security’s popular open-source vulnerability scanner, Trivy, was compromised for the second time in a month, leading to the distribution of malware designed to steal sensitive CI/CD secrets from GitHub Actions environments.

The disruption is felt across the environment, affecting GitHub Actions runners, Trivy VS Code extension (version 0.69.4), Trivy GitHub Actions repositories (`aquasecurity/trivy-action`, `aquasecurity/setup-trivy`), and exposing CI/CD secrets, SSH keys, cloud provider tokens, database passwords, Kubernetes tokens, cryptocurrency wallet details, environment variables.

In response, moved swiftly to contain the threat with measures like Locked down automated actions and tokens, removed malicious versions, and began remediation that includes Atomic token rotation, pinning GitHub Actions to full SHA hashes.

The case underscores how Ongoing (attribution unconfirmed), teams are taking away lessons such as Risks of mutable version tags in dependency management, importance of atomic token rotation, need to pin GitHub Actions to full SHA hashes, and recommending next steps like Pin GitHub Actions to full SHA hashes, implement atomic token rotation, enhance monitoring of repository changes, restrict `pull_request_target` workflows.

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 Supply Chain Compromise: Compromise Software Dependencies and Development Tools (T1195.002) with high confidence (95%), supported by evidence indicating force-pushed 75 out of 76 version tags in the `trivy-action` repository, Valid Accounts: Cloud Accounts (T1078.004) with high confidence (90%), supported by evidence indicating abused compromised credentials to publish malicious releases, and Phishing: Spearphishing Attachment (T1566.001) with moderate confidence (50%), supported by evidence indicating exploited a `pull_request_target` workflow to steal a Personal Access Token (PAT). Under the Execution tactic, the analysis identified Command and Scripting Interpreter: Python (T1059.006) with high confidence (95%), supported by evidence indicating python-based infostealer executed in GitHub Actions runners and Serverless Execution (T1648) with high confidence (90%), supported by evidence indicating malware executes in GitHub Actions runners. Under the Persistence tactic, the analysis identified Create or Modify System Process: Systemd Service (T1543.002) with high confidence (90%), supported by evidence indicating established persistence via a systemd service (`sysmon.py`). Under the Privilege Escalation tactic, the analysis identified Valid Accounts: Cloud Accounts (T1078.004) with high confidence (90%), supported by evidence indicating abused compromised credentials to publish malicious releases. Under the Credential Access tactic, the analysis identified Unsecured Credentials: Credentials In Files (T1552.001) with high confidence (95%), supported by evidence indicating harvesting credentials such as SSH keys, cloud provider tokens, database passwords, Unsecured Credentials: Bash History (T1552.003) with moderate to high confidence (80%), supported by evidence indicating scanned systems for environment variables and credentials, and Steal Application Access Token (T1528) with high confidence (90%), supported by evidence indicating stole a Personal Access Token (PAT) via `pull_request_target` workflow. Under the Collection tactic, the analysis identified Data from Local System (T1005) with high confidence (95%), supported by evidence indicating harvesting environment variables from memory and the filesystem and Data from Code Repositories (T1213.003) with moderate to high confidence (80%), supported by evidence indicating targeted GitHub Actions repositories `aquasecurity/trivy-action` and `aquasecurity/setup-trivy`. Under the Command and Control tactic, the analysis identified Application Layer Protocol: Web Protocols (T1071.001) with high confidence (90%), supported by evidence indicating exfiltrated data via HTTP POST requests to `scan.aquasecurtiy.org` and Ingress Tool Transfer (T1105) with moderate to high confidence (80%), supported by evidence indicating fetched and executed additional payloads via `sysmon.py`. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with high confidence (95%), supported by evidence indicating exfiltrated data via HTTP POST requests to `scan.aquasecurtiy.org` and Exfiltration Over Web Service: Exfiltration to Code Repository (T1567.001) with high confidence (90%), supported by evidence indicating abused the victim’s GitHub account to store data in a public repository named `tpcp-docs`. Under the Defense Evasion tactic, the analysis identified Masquerading: Match Legitimate Name or Location (T1036.005) with high confidence (90%), supported by evidence indicating rewrote existing tags rather than creating new releases and Subvert Trust Controls: Code Signing (T1553.002) with moderate to high confidence (80%), supported by evidence indicating compromised official GitHub Actions repositories. Under the Impact tactic, the analysis identified Resource Hijacking (T1496) with moderate to high confidence (70%), supported by evidence indicating focus on Solana validator keys and cryptocurrency wallets and Account Access Removal (T1531) with moderate confidence (60%), supported by evidence indicating deleted release versions in the earlier breach. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.

Initial Access
Supply Chain Compromise: Compromise Software Dependencies and Development Tools (95%)
Valid Accounts: Cloud Accounts (90%)
Phishing: Spearphishing Attachment (50%)
Execution
Command and Scripting Interpreter: Python (95%)
Serverless Execution (90%)
Persistence
Create or Modify System Process: Systemd Service (90%)
Privilege Escalation
Valid Accounts: Cloud Accounts (90%)
Credential Access
Unsecured Credentials: Credentials In Files (95%)
Unsecured Credentials: Bash History (80%)
Steal Application Access Token (90%)
Collection
Data from Local System (95%)
Data from Code Repositories (80%)
Command and Control
Application Layer Protocol: Web Protocols (90%)
Ingress Tool Transfer (80%)
Exfiltration
Exfiltration Over C2 Channel (95%)
Exfiltration Over Web Service: Exfiltration to Code Repository (90%)
Defense Evasion
Masquerading: Match Legitimate Name or Location (90%)
Subvert Trust Controls: Code Signing (80%)
Impact
Resource Hijacking (70%)
Account Access Removal (60%)

Sources & References