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 killvxk/cybersecurity-skills-zh --skill analyzing-active-directory-acl-abusegit clone --depth 1 https://github.com/killvxk/cybersecurity-skills-zhWrote 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/killvxk/cybersecurity-skills-zh/analyzing-active-directory-acl-abuse)<a href="https://agentmods.dev/skills/killvxk/cybersecurity-skills-zh/analyzing-active-directory-acl-abuse"><img src="https://agentmods.dev/badge/skills/killvxk/cybersecurity-skills-zh/analyzing-active-directory-acl-abuse/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/killvxk/cybersecurity-skills-zh/analyzing-active-directory-acl-abuse"><img src="https://agentmods.dev/badge/skills/killvxk/cybersecurity-skills-zh/analyzing-active-directory-acl-abuse.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 | $0.00042 | $0.00941 |
| Opus 5 | $0.00021 | $0.00470 |
| Sonnet 5 | $0.00008 | $0.00188 |
| Haiku 4.5 | $0.00004 | $0.00094 |
Grade A, and why
analyzing-active-directory-acl-abuse scanned grade A with 0 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 11d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
概述
活动目录(Active Directory)访问控制列表(ACL)通过包含访问控制条目(ACE)的自主访问控制列表(DACL)来定义 AD 对象的权限。配置错误的 ACE 可能赋予非特权用户对敏感对象(如 Domain Admins 组、域控制器或 GPO)的危险权限,包括 GenericAll(完全控制)、WriteDACL(修改权限)、WriteOwner(获取所有权)和 GenericWrite(修改属性)。
本技能使用 ldap3 Python 库连接到域控制器,查询包含 nTSecurityDescriptor 属性的对象,将二进制安全描述符解析为 SDDL(安全描述符定义语言)格式,并识别向非管理员主体授予危险权限的 ACE。这些配置错误正是 BloodHound 等工具发现的基于 ACL 的攻击路径的基础。
前置条件
- Python 3.9 或更高版本,并安装 ldap3 库(
pip install ldap3) - 具有 AD 对象读取权限的域用户凭据
- 域控制器端口 389(LDAP)或 636(LDAPS)的网络连接
- 了解 Active Directory 安全模型和 SDDL 格式
步骤
-
连接域控制器:使用 ldap3 通过 NTLM 或简单身份验证建立 LDAP 连接。在生产环境中使用 LDAPS(端口 636)进行加密连接。
-
查询目标对象:搜索目标 OU 或整个域,获取包括用户、组、计算机和 OU 在内的对象。请求
nTSecurityDescriptor、distinguishedName、objectClass和sAMAccountName属性。 -
解析安全描述符:将二进制 nTSecurityDescriptor 转换为 SDDL 字符串表示。解析 DACL 中的每个 ACE,提取受托人 SID、访问掩码和 ACE 类型(允许/拒绝)。
-
将 SID 解析为主体:通过对域的 LDAP 查询,将安全标识符(SID)映射为可读的账户名。识别内置组的已知 SID。
-
检查危险权限:将每个 ACE 的访问掩码与危险权限位掩码进行比较:GenericAll(0x10000000)、WriteDACL(0x00040000)、WriteOwner(0x00080000)、GenericWrite(0x40000000),以及针对特定扩展权限的 WriteProperty。
-
过滤非管理员受托人:排除预期的管理员受托人(Domain Admins、Enterprise Admins、SYSTEM、Administrators),并标记非特权用户或组持有危险权限的 ACE。
-
映射攻击路径:对于每个发现,记录潜在的攻击链(例如,对用户的 GenericAll 允许重置密码,对组的 WriteDACL 允许将自身添加到组中)。
-
生成修复报告:输出包含所有危险 ACE、受影响对象、非管理员受托人及建议修复步骤的 JSON 报告。
预期输出
{
"domain": "corp.example.com",
"objects_scanned": 1247,
"dangerous_aces_found": 8,
"findings": [
{
"severity": "critical",
"target_object": "CN=Domain Admins,CN=Users,DC=corp,DC=example,DC=com",
"target_type": "group",
"trustee": "CORP\\helpdesk-team",
"permission": "GenericAll",
"access_mask": "0x10000000",
"ace_type": "ACCESS_ALLOWED",
"attack_path": "GenericAll on Domain Admins group allows adding arbitrary members",
"remediation": "Remove GenericAll ACE for helpdesk-team on Domain Admins"
}
]
}
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 65 lines · 42 tokens per session scan A 4f4ca25ecaf2
analyzing-active-directory-acl-abuse is a skill published in the GitHub repository killvxk/cybersecurity-skills-zh (44 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 42 tokens to every session and 941 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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analyzing-active-directory-acl-abuse
Detect dangerous ACL misconfigurations in Active Directory using ldap3 to identify GenericAll, WriteDACL, and WriteOwner abuse paths.
analyzing-active-directory-acl-abuse
Detect dangerous ACL misconfigurations in Active Directory using ldap3 to identify GenericAll, WriteDACL, and WriteOwner abuse paths.
analyzing-active-directory-acl-abuse
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analyzing-active-directory-acl-abuse
Detect dangerous ACL misconfigurations in Active Directory using ldap3 to identify GenericAll, WriteDACL, and WriteOwner abuse paths.
analyzing-active-directory-acl-abuse
Detect dangerous ACL misconfigurations in Active Directory using ldap3 to identify GenericAll, WriteDACL, and WriteOwner abuse paths.
analyzing-active-directory-acl-abuse
Detect dangerous ACL misconfigurations in Active Directory using ldap3 to identify GenericAll, WriteDACL, and WriteOwner abuse paths.