Security audit

Feishu Voice Chat

Security checks for vulnerabilities and agentic risk

Overview

This skill does what it says: it converts Feishu voice messages with Volcengine speech services and prepares Feishu audio replies, with privacy and dependency hygiene considerations.

Install only if Feishu users and administrators accept that voice content and synthesized reply text may be processed by Volcengine and sent through Feishu. Protect the VOLC_ACCESS_TOKEN, scope it to speech services if possible, and pin dependencies before use in sensitive or regulated environments.

SkillSpector

Vulnerability Patterns

Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
Supply ChainUnpinned Dependencies, External Script Fetching, Obfuscated Code
Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
Excessive AgencyUnrestricted Tool Access, Autonomous Decision Making, Scope Creep

Findings (5)

Missing User Warnings

Medium

Confidence: 95% confidence
Finding: The skill processes voice messages by sending audio to Volcengine for ASR/TTS and then transmitting generated audio through Feishu, but the description does not prominently warn users that third-party services receive their content. This creates a privacy and consent risk, especially because voice data may contain sensitive personal or business information.

Unpinned Dependencies

Low

Category: Supply Chain
Content: requests python-dotenv
Confidence: 90% confidence
Finding: The dependency 'requests' is unpinned, so installs may resolve to different versions over time, including versions with known security defects or breaking behavior. In a voice-processing skill that likely handles outbound HTTP calls for Feishu or model/TTS services, uncontrolled dependency drift increases supply-chain and reliability risk.

Unpinned Dependencies

Low

Category: Supply Chain
Content: requests python-dotenv
Confidence: 86% confidence
Finding: The dependency 'python-dotenv' is also unpinned, which allows future installs to pick up unexpected or vulnerable releases. While typically lower risk than a network library, it still creates avoidable supply-chain exposure and deployment inconsistency.

Known Vulnerable Dependency: requests — 10 advisory(ies): CVE-2014-1830 (Exposure of Sensitive Information to an Unauthorized Actor in Requests); CVE-2024-47081 (Requests vulnerable to .netrc credentials leak via malicious URLs); CVE-2024-35195 (Requests `Session` object does not verify requests after making first request wi) +7 more

High

Category: Supply Chain
Confidence: 96% confidence
Finding: The file includes 'requests' without a version pin, and the scanner reports multiple known advisories affecting that package family. Because this skill likely performs network requests as part of ASR/TTS or Feishu integration, vulnerable HTTP client behavior could expose credentials, weaken TLS/session guarantees, or leak sensitive data depending on the runtime-resolved version.

Known Vulnerable Dependency: python-dotenv — 1 advisory(ies): CVE-2026-28684 (python-dotenv: Symlink following in set_key allows arbitrary file overwrite via )

Low

Category: Supply Chain
Confidence: 70% confidence
Finding: The scanner reports a known advisory in 'python-dotenv', and since the requirement is unpinned, an affected version could be installed. This is less dangerous in the provided skill context unless the code uses dotenv mutation features like 'set_key' on attacker-influenced paths, but it still represents an avoidable dependency risk.

Static analysis

No suspicious patterns detected.