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关联漏洞

介绍

As requested, I have now demonstrated both vulnerabilities (BA2022 & BA2015) with practical exploitation scenarios and PoC evidence, which shows how an attacker could abuse these issues in a real-world context.
📌 1. [BA2022] Weak Hash in Code Signing – SHA-1 Exploitation Demonstration
Although the original CyberGhostVPNSetup.exe appears signed and trusted, I have successfully created a fake installer (fakeCyberGhost.exe) using a self-signed certificate with SHA-1 hashing.
✅ Technical Proof:
Used OpenSSL to generate a fake CA and SHA-1 certificate
Signed a fake binary using signtool.exe with that certificate
Windows still marked it as “Signed” (see sigcheck output)
Signature chain was accepted despite being forged with SHA-1
🔥 Security Impact:
This shows that an attacker could:
Forge a malicious payload using a SHA-1-based certificate chain
Mimic the CyberGhost vendor name and product
Trick users into installing malware disguised as a trusted installer
This kind of issue is highly relevant in supply chain attacks and APT-level scenarios, especially in environments that do not enforce strict trust validation or SmartScreen policies.
 
 
![image](https://github.com/user-attachments/assets/51cce04d-8b3e-40fd-a0dd-64f674284bcf)

![image](https://github.com/user-attachments/assets/2f8f7d7c-8e7a-49d6-899d-cf6112e335c1)

 ![image](https://github.com/user-attachments/assets/2d623130-4142-462e-ad60-e34933093a35)

![image](https://github.com/user-attachments/assets/eea7e8cb-ae92-4571-95e8-2c2688085385)




📌 2. [BA2015] Missing High Entropy ASLR – Predictable Memory Layout
I have used WinDbg to run CyberGhostVPNSetup.exe multiple times and observed that the binary consistently loads into low-memory base addresses, such as:
0x00C90000
0x00630000
On 64-bit systems, properly compiled binaries should load into high-memory randomized regions (e.g., 0x00007FF6xxxx0000) when High Entropy ASLR is enabled.
✅ Technical Proof:
WinDbg output shows low, non-randomized base addresses
Confirms that /HIGHENTROPYVA is not in use
Therefore, attackers can predict memory layout
Increases success of ROP (Return-Oriented Programming) and memory corruption exploits

  ![image](https://github.com/user-attachments/assets/7f43e0e2-a6c5-4766-9cc5-941870953a31)

![image](https://github.com/user-attachments/assets/acc01ae7-b614-4ca6-894e-81d4b5e703a8)



💥 Combined Business Risk
These two weaknesses, when combined, create a dangerous scenario:
Trust Bypass: The SHA-1 signature flaw allows an attacker to sign a fake binary that Windows accepts as “Signed”
Exploit Reliability: The predictable memory layout increases exploitability of memory-based vulnerabilities
Supply Chain Threat: End users are at risk of installing malware that appears legitimate
📎 Supporting Evidence
Attached screenshots of:
SHA-1 forged certificate creation and signing
Sigcheck verification (shows “Signed” despite fake cert)
WinDbg memory base address outputs proving ASLR weakness
Each step has been performed on a clean Windows environment using official tools (BinSkim, WinDbg, signtool, OpenSSL)
✅ Conclusion
This is not just a theoretical misconfiguration — it is a practical attack vector that shows how a motivated adversary could bypass trust and memory protections. The attached PoCs directly demonstrate real-world exploitability.

文件快照

 [4.0K]  /data/pocs/bc26c6ceb99216155475b327c0b532b497f10f8d
├── [4.1M]  cve.pdf
└── [3.3K]  README.md

0 directories, 2 files

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