Observed Low-Severity Malware: Potential Information Gathering

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Observed Low-Severity Malware: Potential Information Gathering

Executive Summary

  • SGI sensors detected a low-severity malware instance identified as standalone-framework.js.
  • The activity originated from an IP address in Singapore (AS132203).
  • The malware appears to be associated with potential information-gathering activities.
  • The business risk is considered low, but further investigation is warranted to prevent potential escalation.

Organizations should implement network monitoring and endpoint detection rules to identify and block similar activity.

Observed Activity (SGI Sensors)

ObservedAt SensorName SourceIP SourceASN SourceGeo Protocol/Port PayloadPresence Hash
2025-08-18T18:57:11.602Z [redacted] 101.32.161.XXX AS132203 SG tcp/[redacted] Yes 01ba4719c80b6fe911b091a7c05124b64eeece964e09c058ef8f9805daca546b

An alert was triggered by our systems when a file hash associated with the standalone-framework.js malware family was observed communicating from the identified IP address. While VirusTotal results showed no malicious detections at the time of analysis, the presence of reconnaissance-related filenames within the VirusTotal’s ‘aliases’ section raised concerns. The malware’s potential objective appears to be gathering sensitive information from the compromised system.

Malware/Technique Overview

The malware family standalone-framework.js is categorized as a low-severity threat typically associated with reconnaissance activities. This family often involves collecting system information, user data, and network configurations. While the initial access vector remains unclear, the malware’s behavior suggests a focus on data exfiltration.

  • T1005 – Data from Local System
  • T1082 – System Information Discovery
  • T1016 – System Network Configuration Discovery

VirusTotal Snapshot

VirusTotal analysis indicated 0 malicious detections, 59 undetected, and 0 harmless. The file was identified as “Text”. The reputation score was -575, and the following aliases were noted: dependency_links.txt, robots.txt, zip-safe, aff_c, results.txt, __init__.py, wordbased_en.properties, not-zip-safe, emptyfile, Saved Address Information.txt, Shopping Cart List.txt, Vouchers.txt, py.typed, top_level.txt, bad.txt, error.txt, good.txt, ip.txt, passwords.txt, source.txt.

Indicators of Compromise (IoCs)

Type Value Confidence FirstSeen Notes
ip 101.32.161.XXX medium 2025-08-18T18:57:11.602Z AS132203 Tencent Building, Kejizhongyi Avenue
hash 01ba4719c80b6fe911b091a7c05124b64eeece964e09c058ef8f9805daca546b high 2025-08-18T18:57:11.602Z SHA256 from VirusTotal

It is recommended to monitor these IoCs for at least 30 days.

Detection & Hunting

Splunk SPL

index=* sourcetype=network_traffic dst_ip=101.32.161.133 OR file_hash=01ba4719c80b6fe911b091a7c05124b64eeece964e09c058ef8f9805daca546b
| table _time, src_ip, dst_ip, file_hash, user

This query searches for network traffic to or from the identified IP address or containing the specific file hash. Validate results by checking for legitimate business communications from the source IP to minimize false positives.

Containment, Eradication & Recovery

  1. Isolate the affected host from the network to prevent further communication.
  2. Block the identified IP address (101.32.161.133) at the firewall.
  3. Run a full system scan with updated antivirus and anti-malware solutions.
  4. If necessary, reimage the affected host from a known good backup.
  5. Reset user credentials that may have been compromised.

Communicate the incident to IT and leadership teams. Preserve evidence for potential forensic analysis.

Hardening & Preventive Controls

  • Multi-Factor Authentication (MFA): Implement MFA for all user accounts (NIST CSF PR.AC-1, CIS Control 6).
  • Endpoint Detection and Response (EDR): Tune EDR solutions to detect and block suspicious file executions and network connections (NIST CSF DE.CM-1, CIS Control 8).
  • Network Segmentation: Implement network segmentation to limit the lateral movement of potential threats (NIST CSF PR.AC-5, CIS Control 14).
  • Least Privilege: Enforce the principle of least privilege for user accounts and services (NIST CSF PR.AC-3, CIS Control 5).
  • Patch Management: Implement a rigorous patch management process with defined SLAs (NIST CSF PR.MA-1, CIS Control 7).

Business Impact & Risk Outlook

The observed activity poses a potential risk of unauthorized data access and exfiltration, which could lead to operational disruption, legal liabilities (e.g., GDPR, CCPA), and reputational damage. We anticipate a continued increase in reconnaissance activity targeting SMBs over the next 3-6 months, emphasizing the need for proactive security measures.

Appendix

Note: No payload sample was provided.

Assumptions & Data Gaps

  • Sensor Name not provided, assuming internal SGI sensor.
  • Network port is not available, limiting analysis of the affected service.

References

Staying ahead of emerging threats requires proactive security measures and continuous monitoring. SGI is committed to helping organizations protect their critical assets. Request an Incident Readiness Review to assess your current security posture. Gain peace of mind with 24/7 Monitoring with Sentry365™, or leverage our expertise with vCISO Advisory services.

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