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CF SX-security-audit

全方位安全审计技能。检查文件权限、环境变量、依赖漏洞、配置文件、网络端口、Git 安全、Shell 安全、macOS 安全、密钥检测等。支持 CLI 参数、JSON 输出、配置文件。当用户要求"安全检查"、"漏洞扫描"、"权限检查"、"安全审计"时使用此技能。

ClawHub Agent Skills author: 13256659129 v1.0.0 MIT-0 12 files · 3 scripts body ≈ 858 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process F 28/100 · Will not run — References files that are not bundled: references/permissions.md, references/secrets-detection.md, references/dependency-audit.md

IntegrationSoftware developmentInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
C
69/100
safety, quality, tests
Safety 60%
82
Quality 40%
50
Run on models
none yet
Process rating
F
28/100
Will not run
References files that are not bundled: references/permissions.md, references/secrets-detection.md, references/dependency-audit.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: SX-security-audit (ClawHub)

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Exfiltration medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

Secrets in code medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The files contain someone else's key or token. If it is live, your agent will call third-party services under a stranger's identity; if it was revoked, the skill's scripts simply fail. Such a key often arrives with the author's whole workspace, personal data included.

For the author

The key is visible to everyone who downloaded the skill and has likely been copied by catalog-scanning bots already. Revoke it now, check bills and access logs, then reissue.

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 6

✓ No critical or high findings

Medium and low: 6
  • medium Exfiltration exfil-secret-in-url scripts/checkin_reminder.sh:19
    Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (quoted — discussed, not commanded)
    curl -s -X POST "https://qyapi.weixin.qq.com/cgi-bin/webhook/send?key=…" \
    quoted
  • medium Exfiltration net-credential-use scripts/checkin_reminder.sh:19
    Credential used in a network call (verify the destination is the intended service)
    curl -s -X POST "https://qyapi.weixin.qq.com/cgi-bin/webhook/send?key=…" \
  • medium Secrets in code secret-private-key SKILL.md:72
    Private key material (key header without key body; documentation table row)
    | Private Key | `-----BEGIN PRIVATE KEY----- …
    header onlytable
  • low Secrets in code secret-password-literal code-security.md:92
    Hard-coded password / key literal (may be an example) (placeholder value)
    const apiKey = "sk-p…...";
    placeholder
  • low Secrets in code secret-aws-key secrets-detection.md:11
    AWS access key ID (placeholder value)
    | AWS Access Key | `AKIA[0-9A-Z]{16}` | `AKIA…PLE` |
    placeholder
  • low Secrets in code secret-github-token secrets-detection.md:12
    GitHub token (placeholder value)
    | GitHub Token (classic) | `ghp_[a-zA-Z0-9]{36}` | `ghp_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx` |
    placeholder

Files scanned: 12. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning missing-ref reference to a missing file: references/permissions.md
  • warning missing-ref reference to a missing file: references/secrets-detection.md
  • warning missing-ref reference to a missing file: references/dependency-audit.md
  • warning missing-ref reference to a missing file: references/code-security.md

Process rating: all ten parameters 28/100

Will not run. References files that are not bundled: references/permissions.md, references/secrets-detection.md, references/dependency-audit.md
  • 0Tools and files. 4 referenced file(s) missing: references/permissions.md, references/secrets-detection.md, references/dependency-audit.md
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 1 mutating operations with no state check
  • 40Consistency. Frontmatter name (SX-security-audit) differs from the folder (references)
  • 100Steps. 47 steps
  • 100Execution cost. Instruction body is 858 tokens
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -215 emoji in the instructions: noise for the model
  • -33 of 5 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 130: enough signal without eating the budget
  • +4Structure: 31 headings
  • +3Step-by-step instructions: 47 items
  • +4Has examples (8 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 50.

External checks

ClawHub: suspicious
The main security-audit tool is plausible, but the package also contains undisclosed unrelated scripts that can send chat messages and process payment files.
LLM: suspicious (high) · VirusTotal: · 29 May 2026