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/claude-skillWrote 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/claude-skill)<a href="https://agentmods.dev/skills/lm203688/aishield/claude-skill"><img src="https://agentmods.dev/badge/skills/lm203688/aishield/claude-skill.svg" alt="Measured on agentmods" 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 | $0.00995 |
| Opus 5 | $0.00046 | $0.00498 |
| Sonnet 5 | $0.00018 | $0.00199 |
| Haiku 4.5 | $0.00009 | $0.00100 |
Grade A, and why
aishield-security-scan scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -X POST "$AISHIELD_API/api/v1/audit" \ What it actually says
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 214 条 MCP 规则 / 220 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。
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)
注意事项
- Markdown 不等于文档:对 skill 类资产,
SKILL.md本身就是可执行载荷,AIShield 不会把其中的危险模式当"文档示例"降级处理。 - 语义分析为可选层:配置远程 LLM 需设置
AISHIELD_LLM_URL与AISHIELD_LLM_KEY;不设置则只跑规则引擎。 - 隔离与内容安全是两件事:容器 / 微 VM 沙箱管住"能做什么",AIShield 管住"读进来的东西该不该信"。两者互补。
- 报告与基准见 https://aishield.tools 与
docs/agent-security-benchmark-2026.md。
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.
- 7d ago First seen · 77 lines · 91 tokens per session scan A 944dd73894f9
aishield-security-scan is a skill published in the GitHub repository lm203688/aishield (2 stars, last pushed yesterday), licensed MIT. It adds 91 tokens to every session and 995 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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