feishu-notify
Fail
Audited by Gen Agent Trust Hub on Jul 18, 2026
Risk Level: HIGHCOMMAND_EXECUTIONREMOTE_CODE_EXECUTIONDATA_EXFILTRATION
Full Analysis
- [COMMAND_EXECUTION]: The skill constructs shell commands using
curlwhere user-provided input from$ARGUMENTS(and data from other skills) is interpolated into the-dJSON payload. There is no evidence of shell escaping or sanitization, which allows a malicious message to break out of the JSON string and execute arbitrary commands on the local system (e.g., using backticks or command substitution). - [REMOTE_CODE_EXECUTION]: The documentation explicitly directs users to download and run a bridge application from a third-party GitHub repository (
github.com/joewongjc/feishu-claude-code) for interactive mode. This source is not a verified or well-known vendor, posing a risk of executing unvetted or malicious code on the user's machine. - [DATA_EXPOSURE]: The skill is designed to read
~/.claude/feishu.json, a configuration file containing sensitive data such as Feishu webhook URLs. While this is necessary for the skill's function, it establishes a pattern of accessing sensitive configuration files in the user's home directory. - [INDIRECT_PROMPT_INJECTION]: In interactive mode, the skill polls a remote
BRIDGE_URLand returns the response directly to other calling skills (like/auto-review-loopor/run-experiment). If these calling skills process the 'reply' content as instructions, an attacker who controls the bridge or the Feishu account could influence the agent's behavior. - Ingestion points: Network response from
curl -s "$BRIDGE_URL/poll..."inSKILL.md(Step 3). - Boundary markers: None; the raw reply is returned to the calling skill.
- Capability inventory: Calling skills listed in the 'Event Catalog' (e.g.,
/run-experiment,/research-pipeline) typically possess broad capabilities including file system access and subprocess execution. - Sanitization: None; the skill provides no mechanism to validate or escape the content received from the remote bridge.
Recommendations
- AI detected serious security threats
Audit Metadata