Cysa-Alert-Triage-Lab - Built a defensive security portfolio lab using syn

项目说明

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Sysmon Encoded PowerShell Triage Lab

Captured attack-simulation telemetry + detection tuning + Splunk SPL + reproducible

!Python
![ public telemetry]()
!Telemetry
!Focus
!Integrity
!MITRE

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Fi re path

1. the pinned source, license, and SHA-256.
2. Read the generated four-event timeline to see why two events escalate and two stay as context.
3. Compare the broad and tuned SPL searches with the detection rationale.
4. Finish with the analyst report and its stated limits.

It is a four-event dataset, so nobody needs to pretend there is a haystack just to make the needle look impressive.

What changed in 2

The main case uses captured Windows Sysmon telemetry from the official
Splunk Attack Data project instead of
fabricated authentication, web, and endpoint CSVs. The telemetry was generated
in Splunk Attack Range during a controlled attack simulation.

The original HarborCare synthetic scenario remains in the repository as legacy
learning material, but it is not the e source for the current 4-to-2
detection-tuning result.

In result

The pinned dataset contains four Sysmon Event ID 1 process-creation records from
host ar-win-3:

This is the useful analyst lesson: a broad rule helps find activity, while a
tuned rule adds enough context to prioritize the events that deser.

E and reproducibility

| E | Location |
|---|---|
| Unmodified public Sysmon log | data/public/splunk_attack_data/explorer_spawns_windows-sysmon.log |
| Pro, pinned commit, and SHA-256 | data/public/splunk_attack_data/PRO.md |
| Python XML | src/y.py |
| Automated tests | tests/test_public_telemetry.py |
| Generated results | outputs/public_telemetry_summary.json and .md |
| Splunk searches | splunk/queries/ |
| Splunk import and e runbook | docs/splunk_setup.md |
| Analyst triage report | docs/real_telemetry_triage_report.md |
| Detection rationale | rules/encoded_powershell_detection.md |

Run the

No external Python packages are required.

Splunk workflow

The splunk/queries/ directory contains four searches that in the data,
find broad Explorer child-process candidates, detect padded encoded PowerShell,
and build a confidence-labeled timeline. Follow docs/splunk_setup.md to load
the file into a user-controlled Splunk lab.

The Python result has been reproduced and is tested in CI. The SPL searches are
provided for real SIEM , but this repository does not claim that the
current en executed Splunk or produced screenshots that do not yet exist.

Skills demonstrated

Data pro and license

The public telemetry is copied unchanged from splunk/attack_data at commit
64cb82f9a703a9e5e91aa39c9b0998d838dc632d. It is licensed under Apache 2.0.
Attribution, the pinned source, and the hash are documented in
data/public/splunk_attack_data/PRO.md; the license text is retained in
licenses/SPLUNK_ATTACK_DATA_APACHE-2.0.txt.

Limitations

项目信息

开发语言：Python

Star 数：1

技术要点

该项目属于防护思路方向的开源资源，代码结构清晰，适合安全研究人员学习参考。项目围绕Built a defensive security portfolio lab using synthetic auth, web, endpoint, asset, and vulnerability data to demonstrate alert triage, detection tuning, vulnerability prioritization, incident reporting, and plain-English security communication展开，提供了可运行的实现，对理解相关安全机制、工具原理与攻防技术具有较高的研究价值。

从技术实现角度看，此类项目的核心在于对底层原理的深入理解与工程化落地。开发者在研究过程中可以结合官方文档与社区讨论，梳理项目的初始化流程、核心模块职责与数据流转，逐步掌握其中的技术细节与设计思路。

使用与学习建议

1. 下载源码压缩包，解压到本地环境。

2. 根据项目类型准备对应的运行环境与依赖。

3. 按照 README 中的步骤完成配置与部署。

4. 在隔离的测试环境中运行验证，避免影响生产系统。

免责声明

本资源来源于开源社区，仅供安全研究、技术学习与合法授权范围内的攻防演练使用，请勿用于任何非法或侵害他人权益的用途。使用本项目产生的一切后果由使用者自行承担。