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Security audit

UGC 口播种草视频 UGC Testimonial

Security checks for vulnerabilities and agentic risk

Overview

ClawScan marks this skill suspicious because scanners report external image processing without a clear privacy warning, while several files were only partially analyzed.

Consider the privacy implications before installing, especially if you would use identifiable faces or confidential images. Check which provider and images would be sent and whether you are comfortable with that processing. The scan is incomplete: it reports 54.5% coverage, with five files partially inspected, so the results do not establish that the remaining behavior is safe.

A.I.G

Vulnerability Patterns
  • Skill Instruction HijackingAlters the agent's session goals or safety constraints when the skill loads
  • Agent Memory PoisoningWrites attacker-controlled rules into memory that affect later sessions
  • Remote Payload Retrieval and ExecutionFetches external code whose behavior can change after review
  • Embedded Malicious CodeShips malicious scripts inside the skill and executes them locally
  • Unauthorized Access and Privilege EscalationObtains permissions beyond the task's legitimate needs

SkillSpector

Vulnerability Patterns
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Output HandlingUnvalidated Output Injection, Cross-Context Output, Unbounded Output
  • MCP Least PrivilegeUnderdeclared Capability, Wildcard Permission, Missing Permission Declaration
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
  • Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
Findings (12)

Incomplete referenced artifact analysis

High
Category
analysis-evasion
Confidence
100% confidence
Finding

Referenced artifact was not completely inspected

Content

Scanner excerpt · SKILL.md (reported line 78)May include surrounding context.

md
node scripts/video.mjs --mode storyboard --task ugc-testimonial \

Skill declares no tool scope ('permissions' or 'allowed-tools') but code capabilities were detected: env, network.

Medium
Category
MCP Least Privilege
Confidence
70% confidence
Finding

Without declared permissions the skill's intent is opaque and cannot be validated.

Content

No source excerpt is available for this finding.

Skill Enumeration

Medium
Category
Agent Snooping
Confidence
80% confidence
Finding

Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.

Content

Scanner excerpt · SKILL.md (reported line 110)May include surrounding context.

md
1. **先定人设**。问用户卖给谁，人设跟着买家画像走。
2. **写脚本给用户确认**。口播文案比画面更决定转化。
3. **锁脸**。多个口播镜头必须是同一个人，用 [brand-kit](https://github.com/dlazy-ai/ecommerce-skills/blob/main/skills/brand-kit/skill.md) 的 `model.reference`。
4. **`--dry-run` 过一遍**，再真跑。
5. **配旁白**。生成的视频不做唇形同步，成片后用剪辑软件配一条旁白，比同期声自然。

The generation workflow does not warn users that reference images may be transmitted to a video-model service.

Medium
Category
Output Handling
Confidence
90% confidence
Finding

The workflow directs the agent to use a persistent face reference and proceed with generation without explaining that reference images may leave the local environment. This creates a meaningful privacy and consent gap for identifiable faces or confidential product assets; script approval and a dry run do not necessarily establish approval for external image processing.

Content

No source excerpt is available for this finding.

MCP server referenced without pinned version: 'npx skills'.

Medium
Category
MCP Rug Pull
Confidence
70% confidence
Finding

npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.

Content

No source excerpt is available for this finding.

External Transmission

Medium
Category
Data Exfiltration
Confidence
60% confidence
Finding

Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.

Content

Scanner excerpt · scripts/lib/providers.mjs (reported line 134)May include surrounding context.

js
model: () => env.GEN_MODEL_OPENAI || 'gpt-image-1',
  describe(req) {
    const ep = req.images?.length ? 'images/edits' : 'images/generations'
    return `POST https://api.openai.com/v1/${ep}  model=${openai.model()} size=${mapSize(req.size)} n=${req.batch}`
  },
  async run(req) {
    const key = env.OPENAI_API_KEY

External Transmission

Medium
Category
Data Exfiltration
Confidence
70% confidence
Finding

Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.

Content

Scanner excerpt · scripts/lib/providers.mjs (reported line 153)May include surrounding context.

js
: await readFile(p)
        fd.append('image[]', new Blob([buf], { type: mimeOf(p) }), path.basename(p))
      }
      r = await fetch('https://api.openai.com/v1/images/edits', {
        method: 'POST', headers: { authorization: `Bearer ${key}` }, body: fd,
      })
    } else {

External Transmission

Medium
Category
Data Exfiltration
Confidence
60% confidence
Finding

Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.

Content

Scanner excerpt · scripts/lib/providers.mjs (reported line 153)May include surrounding context.

js
: await readFile(p)
        fd.append('image[]', new Blob([buf], { type: mimeOf(p) }), path.basename(p))
      }
      r = await fetch('https://api.openai.com/v1/images/edits', {
        method: 'POST', headers: { authorization: `Bearer ${key}` }, body: fd,
      })
    } else {

External Transmission

Medium
Category
Data Exfiltration
Confidence
70% confidence
Finding

Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.

Content

Scanner excerpt · scripts/lib/providers.mjs (reported line 157)May include surrounding context.

js
method: 'POST', headers: { authorization: `Bearer ${key}` }, body: fd,
      })
    } else {
      r = await fetch('https://api.openai.com/v1/images/generations', {
        method: 'POST',
        headers: { authorization: `Bearer ${key}`, 'content-type': 'application/json' },
        body: JSON.stringify({

External Transmission

Medium
Category
Data Exfiltration
Confidence
60% confidence
Finding

Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.

Content

Scanner excerpt · scripts/lib/providers.mjs (reported line 157)May include surrounding context.

js
method: 'POST', headers: { authorization: `Bearer ${key}` }, body: fd,
      })
    } else {
      r = await fetch('https://api.openai.com/v1/images/generations', {
        method: 'POST',
        headers: { authorization: `Bearer ${key}`, 'content-type': 'application/json' },
        body: JSON.stringify({

External Transmission

Medium
Category
Data Exfiltration
Confidence
60% confidence
Finding

Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.

Content

Scanner excerpt · scripts/lib/providers.mjs (reported line 261)May include surrounding context.

js
model: (req) =>
    env.GEN_MODEL_REPLICATE ||
    (req?.images?.length ? 'black-forest-labs/flux-kontext-pro' : 'black-forest-labs/flux-dev'),
  describe(req) { return `POST https://api.replicate.com/v1/models/${replicate.model(req)}/predictions` },
  async run(req) {
    const input = { prompt: req.prompt, num_outputs: req.batch }
    if (req.images?.length) input.input_image = await asDataUri(req.images[0])

External Transmission

Medium
Category
Data Exfiltration
Confidence
60% confidence
Finding

Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.

Content

Scanner excerpt · scripts/lib/providers.mjs (reported line 266)May include surrounding context.

js
const input = { prompt: req.prompt, num_outputs: req.batch }
    if (req.images?.length) input.input_image = await asDataUri(req.images[0])
    const j = await postJson(
      `https://api.replicate.com/v1/models/${replicate.model(req)}/predictions`,
      { input },
      { authorization: `Bearer ${env.REPLICATE_API_TOKEN}`, prefer: 'wait' },
      req.timeoutMs,