Malicious code in nucbox (PyPI)
--- _-= Per source details. Do not edit below this line.=-_ ## Source: amazon-inspector (0357c6b685cea74f9200e3e7df019e807e34eac6518ec83f1a5a654c35d97959) The package was found to contain malicious code or consuming dependency that contains malicious code ## Source: kam193 (e98ac1a9b5840905b608a09e8e66c73b750c0baa17d6b7789adfc94a8fd815e4) Versions 0.1.2, 0.1.3 were compromised. Compromised packages start an obfuscated infostealer. The infostealer is a heavily obfuscated JavaScript code executed using Bun runtime on Python startup. It collectes all kinds of sensitive data, including API keys, credentials to package repositories, cryptocurrency assets, password manager data. Infostealer actively queries online services to collect additional secrets as well as attempts to gain persistence and spread further by publishing infected packages using collected credentials. Data are exfiltrated likely using Github. The code seems to threaten to wipe the user's data if it detects invalid GitHub tokens. Cleanup should be done with caution. It seems to be related to the recent Mini Shai Hulud campaign. --- Category: MALICIOUS - The campaign has clearly malicious intent, like infostealers. Campaign: 2026-06-compr-woodpecker Reasons (based on the campaign): - compromised-package - exfiltration-env-variables - exfiltration-cloud-tokens - exfiltration-credentials - abuses-pth - obfuscation - infostealer - The package contains code to detect if it is running in a sandbox environment. - exfiltration-crypto - files-exfiltration - destructive-actions
AI Analysis
Technical Summary
The nucbox package versions 0.1.2 and 0.1.3 on PyPI were compromised to include heavily obfuscated JavaScript infostealer code executed through the Bun runtime during Python startup. The malware collects a wide range of sensitive information including environment variables, cloud tokens, credentials, and cryptocurrency data. It attempts to maintain persistence and spread by publishing infected packages using stolen credentials. The code also detects sandbox environments and may perform destructive actions such as wiping user data if invalid GitHub tokens are found. This campaign is identified as 2026-06-compr-woodpecker and is associated with the Mini Shai Hulud campaign.
Potential Impact
The malicious code in nucbox versions 0.1.2 and 0.1.3 can lead to the theft of sensitive data including API keys, credentials, cryptocurrency assets, and password manager data. It can exfiltrate data likely via GitHub and may cause destructive outcomes such as wiping user data. The malware also attempts to propagate by publishing infected packages, increasing the risk of supply chain compromise.
Mitigation Recommendations
No official patch or remediation is currently documented. Users should immediately avoid using nucbox versions 0.1.2 and 0.1.3. Remove these versions from environments and perform thorough security audits to detect and remediate any potential compromise. Exercise caution during cleanup due to the malware's destructive potential. Monitor vendor advisories or PyPI for updates or official fixes. Consider using alternative trusted packages.
Malicious code in nucbox (PyPI)
Description
--- _-= Per source details. Do not edit below this line.=-_ ## Source: amazon-inspector (0357c6b685cea74f9200e3e7df019e807e34eac6518ec83f1a5a654c35d97959) The package was found to contain malicious code or consuming dependency that contains malicious code ## Source: kam193 (e98ac1a9b5840905b608a09e8e66c73b750c0baa17d6b7789adfc94a8fd815e4) Versions 0.1.2, 0.1.3 were compromised. Compromised packages start an obfuscated infostealer. The infostealer is a heavily obfuscated JavaScript code executed using Bun runtime on Python startup. It collectes all kinds of sensitive data, including API keys, credentials to package repositories, cryptocurrency assets, password manager data. Infostealer actively queries online services to collect additional secrets as well as attempts to gain persistence and spread further by publishing infected packages using collected credentials. Data are exfiltrated likely using Github. The code seems to threaten to wipe the user's data if it detects invalid GitHub tokens. Cleanup should be done with caution. It seems to be related to the recent Mini Shai Hulud campaign. --- Category: MALICIOUS - The campaign has clearly malicious intent, like infostealers. Campaign: 2026-06-compr-woodpecker Reasons (based on the campaign): - compromised-package - exfiltration-env-variables - exfiltration-cloud-tokens - exfiltration-credentials - abuses-pth - obfuscation - infostealer - The package contains code to detect if it is running in a sandbox environment. - exfiltration-crypto - files-exfiltration - destructive-actions
Affected software
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AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
The nucbox package versions 0.1.2 and 0.1.3 on PyPI were compromised to include heavily obfuscated JavaScript infostealer code executed through the Bun runtime during Python startup. The malware collects a wide range of sensitive information including environment variables, cloud tokens, credentials, and cryptocurrency data. It attempts to maintain persistence and spread by publishing infected packages using stolen credentials. The code also detects sandbox environments and may perform destructive actions such as wiping user data if invalid GitHub tokens are found. This campaign is identified as 2026-06-compr-woodpecker and is associated with the Mini Shai Hulud campaign.
Potential Impact
The malicious code in nucbox versions 0.1.2 and 0.1.3 can lead to the theft of sensitive data including API keys, credentials, cryptocurrency assets, and password manager data. It can exfiltrate data likely via GitHub and may cause destructive outcomes such as wiping user data. The malware also attempts to propagate by publishing infected packages, increasing the risk of supply chain compromise.
Mitigation Recommendations
No official patch or remediation is currently documented. Users should immediately avoid using nucbox versions 0.1.2 and 0.1.3. Remove these versions from environments and perform thorough security audits to detect and remediate any potential compromise. Exercise caution during cleanup due to the malware's destructive potential. Monitor vendor advisories or PyPI for updates or official fixes. Consider using alternative trusted packages.
Technical Details
- Gcve Source
- db.gcve.eu
- Osv Id
- MAL-2026-5276
- Osv Schema Version
- 1.7.4
- Aliases
- []
- Ecosystems
- ["PyPI"]
- Database Specific Severity
- null
- Cvss Version
- null
Threat ID: 6a4f6c6168715ace4315a06b
Added to database: 07/09/2026, 09:39:45 UTC
Last enriched: 07/09/2026, 10:04:26 UTC
Last updated: 07/30/2026, 02:54:49 UTC
Views: 19
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