Miasma Software Supply Chain Attack Toolkit (Leaked)
Score: 9/10

Miasma Software Supply Chain Attack Toolkit (Leaked)

Team PCP's Miasma toolkit automates software supply chain attacks by poisoning package registries, hijacking GitHub Actions, and injecting malicious configurations into AI coding agents.

Executive Summary

The Miasma toolkit, attributed to Team PCP and linked to previous Mini Shai-Hulud campaigns, is an advanced software supply chain attack framework designed to propagate across developer ecosystems. The toolkit automates the discovery and compromise of credentials for PyPI, npm, RubyGems, and major cloud providers (AWS, Azure, GCP). It leverages GitHub as a resilient Command and Control (C2) infrastructure, utilizing public commit searches for tasking and exfiltration to bypass traditional network monitoring.

Technical analysis reveals that Miasma uses sophisticated propagation methods, including the exploitation of GitHub Actions OIDC trusted publishing, 'dangling commit' techniques to bypass branch protections, and the hijacking of semver tags in composite actions. It specifically targets the modern developer workflow by injecting malicious hooks into 13 AI coding tools (such as Claude, Cursor, and Copilot) and using a 'Living off the Pull Request' (LOTP) strategy to inject payloads into existing project files across 12+ programming languages.

This threat represents a critical risk to organizations relying on automated CI/CD pipelines and AI-assisted development. The toolkit includes an aggressive 'dead-man switch' that wipes a victim's home directory if its exfiltration token is revoked, as well as a persistent Python-based backdoor. The highly modular and obfuscated nature of the payload makes it resistant to static analysis and standard endpoint detection.

Key Details

Threat Name

Miasma Software Supply Chain Attack Toolkit

Affects

—

Adversary

Team PCP Other Adversaries and Aliases: TeamPCP

Malware/Tools

Miasma, Mini Shai-Hulud, Epsilon Stealer, Shai-Hulud, firedalazer, GITHUB_MONITOR.py, DEADMAN_SWITCH.sh

Report Score

9out of 10
Quality Score
Excellent
IOC Quality6
TTP Details10
Detection Guidance6
Enterprise Relevance10
Clarity & Structure9
Technical Depth10

Sources