analyzing-docker-container-forensics

Warn

Audited by Gen Agent Trust Hub on Sep 14, 2026

Risk Level: MEDIUMPRIVILEGE_ESCALATIONEXTERNAL_DOWNLOADSREMOTE_CODE_EXECUTIONCOMMAND_EXECUTIONDYNAMIC_EXECUTIONINDIRECT_PROMPT_INJECTION
Full Analysis
  • [PRIVILEGE_ESCALATION]: The skill instructions in SKILL.md require administrative access to install tools, specifically using sudo dpkg -i for the dive analysis package.\n- [EXTERNAL_DOWNLOADS]: The skill downloads binaries from external sources, including GitHub (github.com/wagoodman/dive) and Google Cloud Storage (storage.googleapis.com/container-diff). While these platforms are reputable, the binaries are executed with elevated privileges.\n- [REMOTE_CODE_EXECUTION]: The workflow includes downloading and immediate execution or installation of remote binaries (dive and container-diff), which bypasses standard package registry verification processes.\n- [COMMAND_EXECUTION]: Both SKILL.md and scripts/agent.py perform extensive shell command execution via the docker CLI and other system utilities to collect forensic evidence.\n- [DYNAMIC_EXECUTION]: The workflow in SKILL.md dynamically generates and executes Python scripts using heredocs (python3 << 'PYEOF') to parse and analyze JSON data from container artifacts.\n- [INDIRECT_PROMPT_INJECTION]: The skill is designed to ingest and process data from compromised environments, creating a potential surface for indirect prompt injection.\n
  • Ingestion points: Filesystem metadata from docker diff, configuration JSON from docker inspect, and container log files.\n
  • Boundary markers: None identified; untrusted data is processed directly by analysis scripts.\n
  • Capability inventory: The skill has the ability to execute shell commands and write evidence to the host filesystem.\n
  • Sanitization: The Python scripts use simple pattern matching but do not employ comprehensive sanitization for data that might be fed back into an LLM context.
Audit Metadata
Risk Level
MEDIUM
Analyzed
Sep 14, 2026, 05:50 PM