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🇷🇴 cristi

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Feb 1 • 8 tweets • 4 min read

SSRF via PDF? Now made easy.

(thread)

@jonasl

1. Go to @jonasl github and clone this repo. Can't paste the link, for some reason @twitter thinks it's malicious...

2. Copy Burp Collaborator URL to the clipboard.

3. Use as

4. Test file upload features with the generated PDFs.

5. PRO tip: On some endpoints, you need to provide base64 data.

You can use the search engine to find a PDF => Base64 converter. Use the base64 value in the input, usually via a POST request parameter.

6. Comment below if you know of other similar tools! Such as for images for example.

@cristivlad25

7. If you enjoyed this thread, there's much more to come! So, stay tuned.

Like, retweet, and follow me @cristivlad25 for more.

#pentesting #appsec #infosec #cybersecurity #hacking #bugbountytips #bugbounty #ethicalhacking

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More from @CristiVlad25

🇷🇴 cristi

@CristiVlad25

Jan 29

Privilege escalation in Windows using 4 tools for red teamers and pentesters.

(thread)

1. WinPEAS - it's a simple .exe script you can run as: winpeas.exe > outputfile.txt

Get it here: github.com/carlospolop/PE…

2. PrivescCheck - a powershell script

Get it here: github.com/itm4n/PrivescC…

Read 6 tweets

🇷🇴 cristi

@CristiVlad25

Jan 27

In this week's newsletter:

- building the next ChatGPT | Network Pentesting | Full-blown Winter -

(thread)

1. I'm talking about the 6 month learning plan to understand AI large language models from scratch - the stuff that #chatGPT is built on.

2. I'm also talking about the heavy workload of pentests and appsec assessments from this past week.

Read 5 tweets

🇷🇴 cristi

@CristiVlad25

Jan 26

Wanna build the next ChatGPT?

Here's a 6 month learning plan for AI large language models (LLMs) from scratch.

(thread)

@rasbt

1. Familiarize yourself with basic machine learning concepts and Python programming.

Books:

1.1. Introduction to Machine Learning with Python by Andreas Müller and Sarah Guido

1.2. Python Machine Learning by @rasbt

2. Learn about natural language processing (NLP) and its applications.

Books:

2.1. Speech and Language Processing by Daniel Jurafsky and James H. Martin

2.2. Natural Language Processing with Python by Steven Bird, Ewan Klein, and Edward Loper

Read 8 tweets