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Security audit

model-intel-check(zjh)

Security checks for vulnerabilities and agentic risk

Overview

The skill mostly performs the advertised model benchmark, but it needs Review because it can expose credentials to an unofficial mirror and has under-scoped local/API controls.

Install only if you are comfortable with this skill using model API keys, making outbound benchmark calls, and writing full completions/results locally. Do not run make_data.py with HF_TOKEN unless the mirror behavior is fixed or you use a fine-grained read-only token you are prepared to revoke. Prefer official package/data sources, watch API cost/quota, and stop the local Web UI when finished.

Vulnerability Patterns
  • Insecure DependenciesIntroduces malicious components through unsafe dependency sources
  • Insecure Skill Coding PracticesFinds exploitable flaws such as hardcoded secrets or command injection
  • 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
Findings (4)

T09 · Insecure Skill Coding Practices

Error
Location
make_data.py:27
Finding

Hugging Face access token is transmitted to an unofficial mirror

Content
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Remediation
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T09 · Insecure Skill Coding Practices

Warning
Location
serve.py:202
Finding

Unauthenticated loopback endpoint permits browser-driven benchmark execution

Content
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Remediation
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T09 · Insecure Skill Coding Practices

Warning
Location
web/index.html:236
Finding

DOM-based cross-site scripting through unescaped configuration and result values

Content
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{s.color=BOOK_COLORS[i%BOOK_COLORS.length];suiteMeta[s.kind]=s;}); $('hero-line').innerHTML= `被测模型 · ${CFG.model}`+ `thinking ${CFG.no_thinking?'关':'开'}`+ `并发 ${CFG.concurrency}`; $('books').innerHTML=CFG.suites.map(s=>`
${s.ref_pct!=null?`
官方参考 ${s.ref_pct}%
`:''} ${bookSVG(s.color[0],s.color[1])}
${s.name}
共 ${s.count} 题
${'★'.repeat(s.stars)}${'☆'.repeat(5-s.stars)}
`).join(''); } ``` Result and dataset-derived values are also inserted into HTML: ```javascript for(const[kind,arr]of Object.entries(groups)){ const meta=suiteMeta[kind]||{}; html+=`
${meta.name||kind} · ${arr.length} 题
`; for(const[k,v]of arr){ const changed=prevItems[k]&&prevItems[k].status!==v.status; const ch=v.status==='ok'?'✓':v.status==='miss'?'✗':v.status==='error'?'!':'·'; html+=`
${ch}
`; } html+='
'; } $('arena').innerHTML=html; ``` Score labels are handled similarly: ```javascript scores+=`${meta.name||k}
${ok}/${n} ${pct.toFixed(1)}%
`; $('r-scores').innerHTML=scores; ``` ### Technical Analysis The UI interpolates values into HTML strings and assigns them through `innerHTML` without HTML or attribute encoding. Sources include: - `model`, suite names, counts, stars, and referen ...[truncated 1739 chars]
Remediation
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T08 · Insecure Dependencies

Note
Location
SKILL.md:69
Finding

Runtime dependencies are installed without version or integrity pinning

Content
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Remediation
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Vulnerability Patterns
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Trigger AbuseOverly Broad Trigger, Shadow Command Trigger, Keyword Baiting Trigger
  • 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 (9)

Ssd 2

High
Category
Not specified by scanner
Confidence
99% confidence
Finding

The skill explicitly recommends using a forged 'User-Agent: curl/8.0.1' to bypass an intermediary WAF block. That is an evasion technique intended to circumvent an access-control or abuse-detection mechanism, and it can facilitate unauthorized or policy-violating requests against third-party infrastructure.

Content

No source excerpt is available for this finding.

Undeclared Tool Scope

Medium
Category
MCP Least Privilege
Confidence
94% confidence
Finding

The skill instructs the agent to use environment variables, read local config files, create directories, write result files, access the network, and execute shell commands, but it does not declare any explicit tool or permission scope. That mismatch increases the chance the skill will be invoked with broader capabilities than users expect, enabling unintended access to secrets such as API keys or modification of local files.

Content

No source excerpt is available for this finding.

Vague Triggers

Medium
Category
Not specified by scanner
Confidence
95% confidence
Finding

The trigger phrases are broad enough to match common user wording like 'benchmark this endpoint' or '智力测试', which can cause the skill to activate in contexts the user did not intend. Over-triggering is dangerous because this skill performs sensitive actions such as reading local configuration, using API keys, running shell commands, and contacting external endpoints.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
95% confidence
Finding

The entire skill documentation is written in Chinese, and there is no indication that the user may choose another language or that the skill is intentionally limited to a Chinese-speaking audience. Under the stated policy, forcing a specific language without opt-in is a natural-language policy violation.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
93% confidence
Finding

The entire skill file is written in Chinese and includes mandatory wording such as '每次报告必须复述', but it does not offer any language or locale choice to the user. Under the stated policy, forcing a specific language without user opt-in is a natural-language policy violation unless the locale constraint is explicitly justified, which is not present here.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
90% confidence
Finding

The script creates a client and submits jobs through run_one using model kimi-k3, which strongly indicates outbound API calls transmitting question content and possibly related metadata. The file does not include a visible warning, confirmation, or comment disclosing that data is sent to an external service.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
95% confidence
Finding

The document declares lang="zh-CN", and the visible UI text throughout the page is fixed in Chinese, which indicates the skill experience is constrained to a specific language/locale. The file does not present an opt-in, language selector, or justification that this is a region-specific tool, so this conflicts with the policy against forcing a locale without user choice.

Content

No source excerpt is available for this finding.

Missing User Warnings

Low
Category
Not specified by scanner
Confidence
80% confidence
Finding

This code creates a timestamped JSONL file under the results directory, which is a file-write operation. While the script's purpose implies rerunning tasks, there is no explicit warning in the docstring or before the write that a new output file will be created.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Low
Category
Not specified by scanner
Confidence
92% confidence
Finding

The file’s user-facing documentation and runtime guidance are entirely in Chinese, including usage instructions and operational messages, with no indication that another language is supported. Under the language/locale policy, forcing a specific language without user opt-in is a natural-language policy concern.

Content

No source excerpt is available for this finding.