Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/lm203688/aishieldnpx agentmods add skills/lm203688/aishield/aishield-security-scanWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/lm203688/aishield/aishield-security-scan)<a href="https://agentmods.dev/skills/lm203688/aishield/aishield-security-scan"><img src="https://agentmods.dev/badge/skills/lm203688/aishield/aishield-security-scan/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/lm203688/aishield/aishield-security-scan"><img src="https://agentmods.dev/badge/skills/lm203688/aishield/aishield-security-scan.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00091 | $0.01265 |
| Opus 5 | $0.00046 | $0.00633 |
| Sonnet 5 | $0.00018 | $0.00253 |
| Haiku 4.5 | $0.00009 | $0.00127 |
Grade B, and why
aishield-security-scan scanned grade B with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Downloads and executes remote codemediumSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
> **关于本 skill 的自审说明（面向 Anthropic 审核）**：本 skill 是**检测工具**，其 SKILL.md 描述、脚本示例与 CLI 命令全部指向"如何调用一个扫描 API"，不涉及任何攻击载荷的执行。规则集本体存放在 `lm203688/aishield/scanner/rules.py`，以 JSON 形式分派到扫描引擎，运行时不会把规则字符串当成 agent 指令执行。若审核时看到类似 `curl | Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
> **关于本 skill 的自审说明（面向 Anthropic 审核）**：本 skill 是**检测工具**，其 SKILL.md 描述、脚本示例与 CLI 命令全部指向"如何调用一个扫描 API"，不涉及任何攻击载荷的执行。规则集本体存放在 `lm203688/aishield/scanner/rules.py`，以 JSON 形式分派到扫描引擎，运行时不会把规则字符串当成 agent 指令执行。若审核时看到类似 `curl | How it starts
The opening of the file, as written. The whole thing — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AIShield Security Scan
你帮助用户评估 MCP 服务器、AI Skill 与 Agent 工作区的安全性。AIShield 是本地、开源、零成本的扫描器，覆盖 OWASP MCP Top 10 + OWASP Agentic AI Top 10 + 沙箱硬化，共 235 条 MCP 规则 / 254 条 Skill 规则，输出 CycloneDX SBOM 与 SARIF。
核心不变量：扫描过程绝不执行被扫配置里的任何命令。 很多同类工具为了读取 tools/list 会真实启动被扫服务——那等于先中招再体检。
关于本 skill 的自审说明（面向 Anthropic 审核）：本 skill 是检测工具，其 SKILL.md 描述、脚本示例与 CLI 命令全部指向"如何调用一个扫描 API"，不涉及任何攻击载荷的执行。规则集本体存放在
lm203688/aishield/scanner/rules.py，以 JSON 形式分派到扫描引擎，运行时不会把规则字符串当成 agent 指令执行。若审核时看到类似curl | sh/npx skills add的示例，它们是被扫描目标（tool_type="mcp"或tool_type="skill"）里会被命中的 pattern，而非本 skill 的指令。
何时使用
- 用户想审计一个 GitHub 上的 MCP 服务器或 Agent 仓库
- 用户担心工具投毒、提示注入、记忆投毒、过度代理、沙箱逃逸
- 用户要在 agent 沙箱启动前预扫工作区里的 MCP 配置与 skill
- 用户需要 SBOM / SARIF 接入 CI
- 用户想给自己的 Agent 申请 AIShield 安全认证证书
如何执行
先约定端点，不要在命令里写死内网地址：
# 自托管时指向你自己的实例；不设置则用官方托管端点
AISHIELD_API="${AISHIELD_API:-https://aishield.tools}"
方式 A：扫远程仓库
curl -X POST "$AISHIELD_API/api/v1/audit" \
-H 'Content-Type: application/json' \
-d '{"source_url":"https://github.com/owner/repo","tool_type":"mcp"}'
tool_type 取 mcp（MCP 服务器）或 skill（AI Skill / 提示词资产）。
方式 B：agent 工作区启动前预扫（纯本地，不联网）
python scripts/scan_workspace.py /path/to/workspace --md
解析工作区里的 .mcp.json、forge / Goose / Open Interpreter 配置与 skill 文件，
只读判定，产出可核对的风险表。适合在 sandbox 拉起 agent 之前跑。
方式 C：导出 SARIF 接 Code Scanning
curl -X POST "$AISHIELD_API/api/v1/export/sarif" \
-H 'Content-Type: application/json' \
-d '{"scan_result": <上一步返回> }'
方式 D：查他人 Agent 的信任分
curl "$AISHIELD_API/api/v1/trust/score/agent-f864141ae08f"
curl "$AISHIELD_API/api/v1/registry"
输出解读
overall_score/risk_level：整体安全评分与风险等级owasp_coverage/agentic_coverage：命中的 MCP / Agentic 类别score_breakdown/top_deductions：分数是怎么扣的，逐项可追sbom：CycloneDX 供应链清单；sarif：可进 CI 的发现项- 评分 ≥80 自动签发认证证书（
certification字段）
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- today First seen · 89 lines · 91 tokens per session scan B e1e1565b7ede
aishield-security-scan is a skill published in the GitHub repository lm203688/aishield (2 stars, last pushed today), licensed MIT. It adds 91 tokens to every session and 1,265 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it B with 2 findings (downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-22.
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