Analysis of Standalone JavaScript Framework Detection
Executive Summary
- SGI detected a low-severity instance of ‘standalone-framework.js’.
- The activity originated from an IP address in Hong Kong (AS135377).
- The likely objective is reconnaissance or initial probing for vulnerabilities.
- The business risk is currently low, but requires monitoring to prevent escalation.
Ongoing vigilance is crucial to detect and respond to related threats before they can impact operations.
Observed Activity (SGI Sensors)
| ObservedAt | SensorName | SourceIP | SourceASN | SourceGeo | Protocol/Port | PayloadPresence | Hash |
|---|---|---|---|---|---|---|---|
| 2025-11-07T09:52:25.948Z | 152.32.129.XXX | AS135377 | HK | tcp/ | Yes | 01ba4719c80b6fe911b091a7c05124b64eeece964e09c058ef8f9805daca546b |
On November 7, 2025, SGI sensors detected network activity originating from IP address 152.32.129.236, associated with ASN AS135377 in Hong Kong. The detected traffic contained a payload identified as ‘standalone-framework.js’. The protocol and port were not specified by the sensor. While VirusTotal analysis did not flag the hash as definitively malicious, its presence warrants further investigation.
Malware/Technique Overview
Given the file name ‘standalone-framework.js’, it is likely a JavaScript-based framework, potentially used for various purposes, including web application development, or in some cases, malicious scripting. Since VirusTotal shows many ‘undetected’ hits and a negative reputation, this script may be used for initial reconnaissance or probing for vulnerabilities. Without further context, we must assume it could be leveraged for malicious purposes.
- T1497.001 – Virtualization/Sandbox Evasion: System Checks
- T1059.007 – Command and Scripting Interpreter: JavaScript
- T1068 – Exploitation for Privilege Escalation
VirusTotal Snapshot
VirusTotal analysis of the SHA256 hash 01ba4719c80b6fe911b091a7c05124b64eeece964e09c058ef8f9805daca546b shows:
- Malicious: 0
- Undetected: 62
- Harmless: 0
The high number of ‘undetected’ results suggests the file may be new or a variant of a known framework, or potentially obfuscated. Many aliases include names of common python files such as `__init__.py`.
Indicators of Compromise (IoCs)
| Type | Value | Confidence | FirstSeen | Notes |
|---|---|---|---|---|
| IP | 152.32.129.XXX | Medium | 2025-11-07T09:52:25.948Z | AS135377 UCLOUD INFORMATION TECHNOLOGY (HK) LIMITED |
| Hash | 01ba4719c80b6fe911b091a7c05124b64eeece964e09c058ef8f9805daca546b | High | 2025-11-07T09:52:25.948Z | SHA256 from VirusTotal |
It is recommended to monitor these IoCs for at least 30 days.
Detection & Hunting
The following queries can be used to detect similar activity within your environment:
Splunk SPL
index=* hash="01ba4719c80b6fe911b091a7c05124b64eeece964e09c058ef8f9805daca546b" OR src_ip="152.32.129.0/24"
Elastic/Kibana KQL
hash : "01ba4719c80b6fe911b091a7c05124b64eeece964e09c058ef8f9805daca546b" or source.ip : "152.32.129.0/24"
When reviewing results, validate that the source IP is not a known partner or internal asset. Investigate any associated processes or network connections.
Containment, Eradication & Recovery
- Isolate: Disconnect any affected systems from the network to prevent further spread.
- Block: Block the identified IP address (152.32.129.236) at the firewall.
- Scan: Perform a full system scan with updated anti-malware software on potentially affected systems.
- Reimage (If Necessary): If malware is confirmed, consider reimaging the affected systems from a known good backup.
- Credential Resets: Reset passwords for any accounts that may have been compromised.
Remember to communicate with IT staff and leadership throughout the process. Preserve any evidence for forensic analysis.
Hardening & Preventive Controls
- Multi-Factor Authentication (MFA): Implement MFA for all user accounts, especially those with privileged access. (NIST CSF: PR.AC-1, CIS Control 6)
- Endpoint Detection and Response (EDR): Fine-tune EDR rules to detect and block suspicious JavaScript execution. (NIST CSF: DE.CM-7, CIS Control 10)
- Network Segmentation: Implement network segmentation to limit the lateral movement of attackers. (NIST CSF: PR.AC-4, CIS Control 14)
- Least Privilege: Enforce the principle of least privilege, granting users only the permissions they need to perform their job duties. (NIST CSF: PR.AC-3, CIS Control 5)
- Patch Management: Maintain a strict patch management schedule to address known vulnerabilities promptly. (NIST CSF: PR.MA-1, CIS Control 7)
Business Impact & Risk Outlook
The detection of ‘standalone-framework.js’, while currently low severity, could indicate reconnaissance activity targeting vulnerabilities in your systems. If successful, this could lead to data breaches, service disruptions, and reputational damage. Legal and regulatory compliance could also be impacted depending on the nature of any compromised data.
Over the next 3-6 months, we anticipate an increase in reconnaissance attempts leveraging obfuscated or custom-built JavaScript frameworks. Organizations should prioritize strengthening their defenses against script-based attacks.
Appendix
Redacted Payload Snippet:
// [REDACTED] - This section would contain a redacted portion of the javascript if available. Due to no payload sample provided, a sample cannot be included.
Assumptions & Data Gaps:
- The exact function of ‘standalone-framework.js’ is unknown without a full payload sample.
- Protocol and port information was missing from the sensor data.
- The specific target within the network is unknown.
References:
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