huawei-cloud-skill-audit

Audit Huawei Cloud skills for quality, security, and compliance using a three-check pipeline: skillspector (AI security), gitleaks (credential leak), and runtime_security (CWE 高危运行模式). Generates structured reports with issue details and fix strategies. Triggers include: "审计技能","技能审计","检查技能质量","扫描技能问题","技能安全审计", "audit skill","check skill quality","scan skills for issues","skill audit", "华为云技能审计","技能合规检查","skill gate","质量门禁","技能检查", "audit huawei cloud skill","verify skill compliance","技能质量检查","跑审计","安全扫描".

huaweicloudskill@huaweicloudskill

Install

openclaw skills install @huaweicloudskill/huawei-cloud-skill-audit

Huawei Cloud Skill Audit

Three-check security pipeline for auditing Huawei Cloud skills — security gate.

Step 0: Install skill-quality-cli (idempotent, skip if already installed)

先设置 AUDIT_DIR 为本 skill 安装目录的绝对路径(export AUDIT_DIR=/path/to/huawei-cloud-skill-audit, 示例: $HOME/.local/share/huawei-cloud-skill-audit), 后续所有命令统一用它, 禁止在被审计目录内使用相对路径执行本 skill 的脚本(防目录内恶意同名脚本劫持, 见 Core Commands 安全要求)。

bash

export AUDIT_DIR=/path/to/huawei-cloud-skill-audit   # 替换为实际安装目录
bash "$AUDIT_DIR/scripts/ensure_cli.sh"

⚠️ 强制要求: 本 skill 的任何 hcloud 命令必须用 skill-quality-cli run --skill-name huawei-cloud-skill-audit -- 包裹, 禁止裸调 hcloud。(Mandatory: bare hcloud calls are strictly forbidden.)

安装行为说明:

已装且可用 → 静默跳过; 未装 → 从华为云 OBS(HTTPS) 下载官方包(wrapper + ELF + Python fallback, low-GLIBC 兼容)安装到 ~/.local/bin/。

离线/安装失败 → stderr 打印 警告: 后跳过, 不阻塞业务流(但 wrapped 命令将 command not found, 正式场景必须保证安装成功)。

调试/离线场景可用裸命令 python3 "$AUDIT_DIR/scripts/skill_audit.py" ...(见 Core Commands 安全要求与统一说明)。

Overview

Scan a single Huawei Cloud skill directory or a folder of skills, run three security gates, and generate a structured report with issue details and fix strategies.

Three checks:

#	Tool	Check Content	Implementation
1	skillspector	AI skill security scanner: 52 rules / 609 patterns across 18 categories (prompt injection, data exfiltration, privilege escalation, supply chain, behavioral AST, taint tracking, MCP analysis, YARA)	Built-in (pure Python, 52 rules + AST analysis)
2	gitleaks	Credential leak scan: 43 rules detecting hardcoded API keys, passwords, private keys, tokens	Built-in (pure Python, 43 rules + Shannon entropy)
3	runtime_security	CWE high-risk runtime patterns: 36 rules (command injection, deserialization, credential theft, sandbox escape, persistence, destructive ops, mining) + 3 skill-quality rules (Q001-Q003)	Built-in (pure Python, level-independent, all rules always run)

规则数(52/609、43、36+3)以 scripts/checks/*rules.json 为准, 增删规则后请同步更新本表。

Dependency: Quality telemetry is collected automatically via skill-quality-cli (installed by scripts/ensure_cli.sh if absent; 安装/升级/禁用遥测的具体命令见 references/cli-installation-guide.md).

Prerequisites

Python 3.10+ — for the built-in skillspector and gitleaks checks
Node.js + npx — Optional; only needed for manual markdownlint-cli2 --fix during remediation
hcloud CLI — For Huawei Cloud service verification (optional, used in verification only)
Huawei Cloud AK/SK — Not required for audit itself, but needed if verifying skill functionality after audit

内置 / 外部二进制说明:

默认内置: skillspector 与 gitleaks 均为纯 Python 实现, 无需外部二进制或 pip 安装。
外部路径显式指定才生效: 传 --skillspector/--gitleaks <path> 时才使用外部二进制。
PATH 自动发现已禁用(2026-09-23, fail-closed): 不再从 PATH 探测, 避免 PATH 被注入同名恶意二进制静默接管审计。
外部二进制不校验签名/哈希: 请确保其来源可信(PATH 无同名二进制, 下载来源受控)。
默认行为: 不传 --skillspector/--gitleaks 时, 恒使用内置纯 Python 实现, 与 scan level 无关。

To skip fallback auto-install of external binaries, use --no-install flag.

Workflow

text

Input (skill path or folder)
    │
    ├── Discover Skills ──── Find SKILL.md in target or subdirectories
    │
    ├── Run Three Checks ────
    │   1. skillspector → AI security scan (52 rules, 609 patterns)
    │   2. gitleaks → Credential leak detection
    │   3. runtime_security → CWE high-risk runtime patterns (36 + 3 rules)
    │
    ├── Build Report ────
    │   Section 1: Scanned Skills
    │   Section 2: Issue Summary (by severity)
    │   Section 3: Issue Details (per-issue)
    │   Section 4: Fix Strategies (per rule/category)
    │
    └── Gate Verdict ──── PASS or FAIL

Scan Levels

Level	Analyzers	Speed	Use Case
`critical`	"critical" severity rules only (P5 harmful content)	Fast	Strictest gate
`high`	"critical" + "error" severity rules + AST (exec/eval/os.system/反序列化)	Fast	Block high-risk issues
`quick`	Pattern matching only (all static regex rules)	Fast	Quick pre-commit check
`standard`	All static analyzers (high 基础上放开 WARNING/INFO 级 AST + taint tracking)	Medium	CI/CD gate
`deep`	Standard + MCP analysis (least privilege, tool poisoning, rug pull)	Slower	Pre-release full audit

⚠️ 术语区分: 扫描档位名(critical/high/quick/standard/deep, 反引号)与规则 JSON 中的 severity 值("critical"/"high"/"medium"/"low", 引号)是两套值 —— 档位决定启用哪些分析器并过滤到哪些 severity 级别; severity 是单条规则的属性。同名不表示同一概念: 例如 critical 档过滤出 "critical" 级发现, high 档过滤出 "critical"+"error" 级发现。

Severity filtering applies only to SkillSpector (rule selection per scan level). gitleaks bundles only "critical"/"high" severity rules, so all of them run at every scan level. runtime_security is level-independent: all 39 rules (36 CWE + Q001-Q003) always run, and its CRITICAL findings always block the gate.

AST 分析在 high/standard/deep 均执行(high 为默认档, 必须带 AST, 否则 eval/exec/pickle.loads 等执行类检测可被直接绕过)。high 档楼层过滤保留 CRITICAL/ERROR 级发现(critical/high 为规则 JSON 中的 severity 值, 内部映射为 CRITICAL/ERROR), 因此默认档阻断: AST1/2/5/9/10(exec/eval/os.system/getattr 反射/反序列化全部 ERROR 级); WARNING 级(AST3/4/6/7: compile/subprocess/动态 import 等)仅在 standard/deep 可见。.py 解析失败不再静默——产出 ERROR 级 AST-SYNTAX 发现并阻断 gate(fail-closed, 防恶意写坏代码规避 AST)。

KooCLI Command Format Standard

This skill audits skill directories locally and does not directly invoke hcloud CLI commands. When verifying a skill's functionality after audit, the standard KooCLI format applies — the line below is an illustrative template, not a runnable command:

text

bash "$AUDIT_DIR/scripts/hcloud-run.sh" <Service> <Operation> --cli-region=<region> [--key=value ...]   # 强制入口：一切 hcloud 经 hcloud-run.sh 包装执行（hcloud-run.sh 内部自动经 skill-quality-cli run 包裹上报, 见 Step 0 强制要求）; hcloud 场景下用户只需调用 hcloud-run.sh, 不要手工再包一层 skill-quality-cli run

Core Commands

⚠️ 安全要求(必须遵守): 所有命令必须通过 绝对路径 引用本 skill 的 scripts/skill_audit.py。被审计的技能目录是不可信输入 —— 其中可能被预置恶意 scripts/skill_audit.py, 若在该目录内执行相对路径 python3 scripts/skill_audit.py, 审计会执行攻击者代码(RCE)。执行前先设置 AUDIT_DIR 为本 skill(huawei-cloud-skill-audit)的安装目录绝对路径: export AUDIT_DIR=/path/to/huawei-cloud-skill-audit(示例: $HOME/.local/share/huawei-cloud-skill-audit)。之后统一用 python3 "$AUDIT_DIR/scripts/skill_audit.py" ..., 并可用 --target . 指向你所在/任意被审计目录。

统一说明: 每个场景给出两条命令 —— ① wrapped 命令(skill-quality-cli run --skill-name huawei-cloud-skill-audit -- ...): 正式使用必须用它(质量上报); ② 裸命令(python3 "$AUDIT_DIR/scripts/skill_audit.py" ...): 仅调试/离线场景的等效直接执行, 正式使用请勿用裸命令。

Scan a single skill

bash

# 先按上述安全要求设置 AUDIT_DIR, 然后在任意目录执行(--target . 指向被审计目录)
skill-quality-cli run --skill-name huawei-cloud-skill-audit -- python3 "$AUDIT_DIR/scripts/skill_audit.py" --target .

Scan a folder of skills

bash

# --target 指向包含多个技能的父目录
skill-quality-cli run --skill-name huawei-cloud-skill-audit -- python3 "$AUDIT_DIR/scripts/skill_audit.py" --target ..

Scan with specific level

bash

skill-quality-cli run --skill-name huawei-cloud-skill-audit -- python3 "$AUDIT_DIR/scripts/skill_audit.py" --target .. --scan-level quick

Selective check execution

bash

skill-quality-cli run --skill-name huawei-cloud-skill-audit -- python3 "$AUDIT_DIR/scripts/skill_audit.py" --target .. --checks skillspector
skill-quality-cli run --skill-name huawei-cloud-skill-audit -- python3 "$AUDIT_DIR/scripts/skill_audit.py" --target .. --skip-checks gitleaks

Run with custom tool paths

Custom binary locations can be overridden with --skillspector, --gitleaks and --node-bin (see Parameter Confirmation; default auto-install location is ~/.local/bin/):

bash

skill-quality-cli run --skill-name huawei-cloud-skill-audit -- python3 "$AUDIT_DIR/scripts/skill_audit.py" --target .. --skillspector /path/to/skillspector --gitleaks /path/to/gitleaks --node-bin /path/to/node
# 等效直接执行（⚠️ 仅调试/离线场景, 正式使用请经 skill-quality-cli run 包裹以保证质量上报）
python3 "$AUDIT_DIR/scripts/skill_audit.py" --target .. --skillspector /path/to/skillspector --gitleaks /path/to/gitleaks --node-bin /path/to/node

Available --scan-level values: high (default), critical, quick, standard, deep. Available --checks: skillspector, gitleaks, runtime_security. Use --skip-checks to exclude specific checks.

Parameter Confirmation

Parameter	Required	Description	Example
`--target`	Yes	Single skill dir or parent folder of skills	`/path/to/skill-dir`
`--output-dir`	No	Report output directory (default: parent of target)	`--output-dir ./reports`
`--scan-level`	No	Scan depth: high/critical/quick/standard/deep (default: high)	`--scan-level deep`
`--checks`	No	Comma-separated checks to run (default: all); valid values are only `skillspector`, `gitleaks`, `runtime_security`. Mutually exclusive with `--skip-checks`	`--checks skillspector`
`--skillspector`	No	SkillSpector binary path override	`--skillspector ~/.local/bin/skillspector`
`--gitleaks`	No	gitleaks binary path override (auto-installs to ~/.local/bin when missing)	`--gitleaks ~/.local/bin/gitleaks`
`--skip-checks`	No	Comma-separated checks to skip; mutually exclusive with `--checks`	`--skip-checks gitleaks`
`--no-install`	No	Skip auto-install of tools	`--no-install`

Report Structure

Report is saved as skill-gate-report-<timestamp>.txt in the parent directory of the scanned path.

Input	Report saved to
`/repo/skills/huawei-cloud-ecs-manage`	`/repo/skills/skill-gate-report-<timestamp>.txt`
`/repo/skills`	`/repo/skill-gate-report-<timestamp>.txt`

Four sections:

Scanned Skills — list of all skills found
Issue Summary — count by severity (CRITICAL/ERROR/WARNING) with rule breakdown (INFO excluded)
Issue Details — per-issue: skill name, rule, line number, snippet, message
Fix Strategies — actionable remediation for each unique rule/category

Fix Strategies Reference

skillspector

Rule	Fix
P1-P8 (Prompt Injection / System Prompt Leakage)	Do not embed user-controllable input in system prompts; use template variables with explicit escaping
E1-E5 (Data Exfiltration)	Remove external URLs; use env vars for API endpoints; restrict network access in tool definitions
PE1-PE5 (Privilege Escalation)	Avoid sudo/root commands; use capability-based permissions; do not disable security controls
AST (Behavioral AST: AST1-AST7/9/10)	Replace exec()/eval() with safer alternatives; use importlib with allowlists
YR1-YR4 (YARA)	Remove reverse shell/webshell patterns; move server functionality to separate controlled service
SC1/SC2/SC3/SC7 (Supply Chain)	Pin dependency versions with hashes; update vulnerable dependencies
EA1-EA4 (Excessive Agency)	Scope tool permissions to the minimum required for the task
MP1-MP3, OH1-OH3 (Memory Poisoning / Output Handling)	Validate memory writes and tool output before use
RA1-RA2, AS1-AS3 (Rogue Agent / Agent Snooping)	Restrict agent delegation and session data access
SSRF1-SSRF3 (Server-Side Request Forgery)	Validate/allowlist external endpoints before requests
TM1-TM4 (Tool Misuse)	Validate tool parameters; never concatenate untrusted input into shell commands

gitleaks

Rule	Fix
private-key	Remove hardcoded private key; load from file or secret manager at runtime; add key file to `.gitignore`
(other rules)	Replace hardcoded credential with environment variable or secret manager reference; see https://gitleaks.io/docs/secrets

Remediation Workflow (audit -> fix -> verify)

After running the audit and getting a FAIL, follow this sequence:

Fix issues by hand — Apply the fixes from the report's Fix Strategies section, or the skillspector/gitleaks rule tables above.
Re-run the full audit to verify PASS.

Markdown style and SKILL.md spec issues are not audited by this skill; use external tools like markdownlint-cli2 --fix only if you need to fix markdown style separately.

CI/CD Integration

yaml

# CI 场景下 checkout 的仓库即本 skill 自身, 脚本来源可信, 相对路径无 RCE 风险
# (与 Core Commands 安全要求不冲突: 那里禁止的是在"被审计技能目录"内跑相对路径)
jobs:
  skill-gate:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-python@v5
        with:
          python-version: '3.12'
      - name: Run audit
        run: python3 scripts/skill_audit.py --target . --output-dir .
      - name: Upload report
        uses: actions/upload-artifact@v4
        if: always()
        with:
          name: skill-gate-report
          path: skill-gate-report-*.txt

Configuration Files

The built-in checks use their bundled rule sets — no external config required:

scripts/checks/skillspector_rules.json — skillspector rules (52 rules / 609 patterns)
scripts/checks/gitleaks_rules.json — gitleaks rules (43 rules)

.markdownlint.json and skillcheck.toml shipped with the skill directory are not consumed by this audit; they are only for external markdownlint/skillcheck tooling.

Security Scanning

Why skillspector static-only mode has limitations

skillspector runs with --no-llm mode (static analysis only). Gaps:

Analyzer	What it detects	What it MISSES in --no-llm mode
Pattern matching (P1-P8, E1-E5, PE1-PE5, EA1-EA4, MP1-MP3, OH1-OH3, RA1-RA2, AS1-AS3, SSRF1-SSRF3, TM1-TM4)	Prompt injection, data exfiltration, privilege escalation, agency/poisoning patterns	LLM-generated obfuscated variants
AST analysis (AST1-AST7/9/10)	exec()/eval() calls, dynamic imports, reflective getattr, unsafe deserialization	Runtime-evaluated strings
YARA rules (YR1-YR4)	Reverse shell, webshell patterns	Encoded/obfuscated payloads
Supply chain (SC1/SC2/SC3/SC7)	Vulnerable/pinned dependency issues	Transitive dependency exploits

Complementary tools

Tool	Detects	Install
skillspector (built-in, --no-llm)	Prompt injection, reverse shell, command injection, data exfiltration, privilege escalation, supply chain	Auto-installed
gitleaks (built-in)	43 rules: API keys, passwords, private keys, tokens	Auto-installed
gitcode-security-scanner	Generic keyword credentials, Chinese keywords, SQL injection, debug leakage	From DTSE-SKILL repo

Recommended: Run both huawei-cloud-skill-audit AND gitcode-security-scanner for complete coverage.

Output Format

Report is a plain text file with four sections (Scanned Skills, Issue Summary, Issue Details, Fix Strategies) followed by a Gate Verdict (PASS/FAIL).

Verification Method

Run audit

bash

# AUDIT_DIR 见 Core Commands 安全要求(本 skill 安装目录绝对路径)
skill-quality-cli run --skill-name huawei-cloud-skill-audit -- python3 "$AUDIT_DIR/scripts/skill_audit.py" --target .
# 等效直接执行（⚠️ 仅调试/离线场景, 正式使用请经 skill-quality-cli run 包裹以保证质量上报）
python3 "$AUDIT_DIR/scripts/skill_audit.py" --target .

Verify fix

bash

# Fix issues from the report's Fix Strategies section, then re-run audit
skill-quality-cli run --skill-name huawei-cloud-skill-audit -- python3 "$AUDIT_DIR/scripts/skill_audit.py" --target .
# 等效直接执行（⚠️ 仅调试/离线场景, 正式使用请经 skill-quality-cli run 包裹以保证质量上报）
python3 "$AUDIT_DIR/scripts/skill_audit.py" --target .

Check gate verdict

bash

# Gate Verdict: PASS = 无 CRITICAL/ERROR 发现(WARNING 带记录理由后可接受)
# Gate Verdict: FAIL = 存在 CRITICAL 或 ERROR 发现(与 references/verification-method.md、security-audit-guide.md 一致)

Reference Documents

references/iam-policies.md — IAM permissions required for skill audit
references/verification-method.md — Detailed verification procedures
references/acceptance-criteria.md — Acceptance criteria for audit PASS
references/security-audit-guide.md — Security audit guide and fix strategies
references/gitcode-security-scanner.md — Complementary scanner usage guide
scripts/ensure_cli.sh — Idempotent skill-quality-cli installer (auto-installs if absent)

Best Practices

Run audit before accepting any Huawei Cloud skill contribution
Fix issues per the report's Fix Strategies, then always re-run full audit to verify PASS
For large repos, scan individual skills one at a time to avoid huge reports
Run both huawei-cloud-skill-audit and gitcode-security-scanner for complete security coverage

Notes

This skill only generates audit reports and fix strategies; it never modifies any skill file automatically. Fixes are applied manually by the user per the report's Fix Strategies or the Remediation Workflow; re-run the audit to verify after fixing.
Three-check pipeline runs sequentially; each check is independent
API endpoints are strictly prohibited from being inferred
Credentials (AK/SK) are read from environment variables; hardcoding is prohibited
If AK/SK is missing for post-audit verification, prompt the user; do not skip
Resources created during testing must be tracked; output manual cleanup instructions if any remain
INFO-level issues are excluded from the report; only CRITICAL/ERROR/WARNING appear
gitleaks --no-git mode scans current file contents only, not git history
gitleaks does not detect Chinese keyword credentials; use gitcode-security-scanner for those

Edge Cases

Scenario	Handling
Skill directory does not exist	Report error and terminate
Target has no SKILL.md and no subdirs with SKILL.md	Report error: no skills found
Built-in rules file missing	Check skipped with warning (built-in rules JSON is the only default path; external auto-download is not performed — fail-closed)
Python version < 3.12	Built-in pure Python checks still work (Python 3.10+); external binaries not auto-detected (fail-closed), so no version-specific external fallback
Large repo produces huge report	Scan individual skills; use head/tail to read summary
gitleaks false positive	Add to .gitleaksignore file
skillspector exit code 1	Findings reported per rule severity; risk score is display-only, not a gate condition

Design Principles

Three-Check Pipeline — Each check is independent and contributes to the overall gate verdict
Auto-Install — Missing tools are installed automatically on first run
Chain Verification — All enabled checks must pass for gate verdict PASS
Agent-proof — Write operations require user confirmation; automatic gate bypassing is not allowed
Data-Driven — Report is structured text with clear severity levels and fix strategies
Batch Repeatable — Same skill can be audited repeatedly; each run writes a fresh timestamped report
Credential Security — No hardcoded AK/SK; read from environment variables
Least Privilege — IAM policies follow minimum required permissions