Security audit
Security checks for vulnerabilities and agentic risk
This skill is a local Ollama text-to-image helper whose network use and file output match its stated purpose.
Install only if you intend to use a local Ollama image model. Do not include secrets in prompts, confirm your local Ollama service and x/z-image-turbo model are trusted, and expect generated images to be written to the images directory or the output path you provide.
The skill invokes a local Ollama HTTP service, which is a network-capable action, but the manifest does not declare any tool scope or permission boundary. This creates a mismatch between documented and actual capabilities, increasing the risk of unintended network access and reducing users' ability to evaluate what the skill can do.
The trigger phrases include very generic requests such as '生成图片', '文生图', and '画一张图', which are common user intents and may cause the skill to activate in situations the user did not specifically intend for this tool. Overbroad activation can lead to unexpected execution, unnecessary local service calls, and unreviewed content generation requests.
The manifest description repeatedly specifies using Chinese prompts, including activation on submission of Chinese prompt text and command examples with "你的中文提示词". This imposes a language constraint in the skill's natural-language instructions without presenting it as optional or justified as a region-specific requirement.
The docstring explicitly requires the prompt to be in Chinese ("中文提示词"), and the CLI help at L72 repeats the same restriction. This is a natural-language policy concern because the skill imposes a specific language requirement without any visible opt-in, fallback, or justification that the tool is region-specific.
Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
start_time = time.perf_counter()
response = requests.post(
"http://localhost:11434/api/generate",
json={
"model": "x/z-image-turbo",
Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
start_time = time.perf_counter()
response = requests.post(
"http://localhost:11434/api/generate",
json={
"model": "x/z-image-turbo",
Code issues a request to a loopback, link-local, or private-range host. This can reach internal services not meant to be exposed and is a common SSRF pivot.
start_time = time.perf_counter()
response = requests.post(
"http://localhost:11434/api/generate",
json={
"model": "x/z-image-turbo",