syncause-debugger
Fail
Audited by Gen Agent Trust Hub on Oct 1, 2026
Risk Level: HIGHCREDENTIALS_UNSAFEOBFUSCATIONREMOTE_CODE_EXECUTIONDYNAMIC_EXECUTIONINDIRECT_PROMPT_INJECTIONEXTERNAL_DOWNLOADS
Full Analysis
- [CREDENTIALS_UNSAFE]: The file
references/install/java.mdcontains a hardcoded GitHub Personal Access Token. Hardcoding active credentials in documentation is a significant security risk. - [OBFUSCATION]: The GitHub Personal Access Token in
references/install/java.mdis split across two properties (syncause.repo.token.p1andsyncause.repo.token.p2), which is a technique typically used to bypass automated secret scanning tools. - [REMOTE_CODE_EXECUTION]: The Node.js installation process in
references/install/nodejs.mdinvolves piping a remote shell script directly into bash (curl | bash). This provides the script with full execution privileges on the user's machine. - [DYNAMIC_EXECUTION]: The Java installation (
references/install/java.md) utilizes thebyte-buddy-maven-pluginto perform bytecode transformations. This allows the SDK to inject logic into the application's classes at runtime. - [INDIRECT_PROMPT_INJECTION]: The skill's primary function involves analyzing runtime traces and snapshots from external applications via MCP tools (e.g.,
get_trace_insight,inspect_method_snapshot). Since this data is generated by the application being debugged and could contain user-influenced logs or errors, it represents a surface for indirect prompt injection. - Ingestion points: Runtime trace data retrieved via
get_trace_insightandinspect_method_snapshot(SKILL.md). - Boundary markers: None present; the skill treats all captured runtime state as trusted data.
- Capability inventory: The skill has the ability to edit source code (Phase 2), execute shell commands for bug reproduction (Phase 1), and perform cleanup/uninstallation tasks (Phase 4).
- Sanitization: No sanitization or filtering of the captured runtime data is performed before it is presented to the agent.
- [EXTERNAL_DOWNLOADS]: The skill downloads and installs various artifacts from external sources, including a Python wheel from GitHub releases and multiple Node.js packages from the NPM registry.
Recommendations
- AI detected serious security threats
Audit Metadata