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Average Ratings 0 Ratings

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ease
features
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support

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Description

Accent EXCEL Password Recovery (AccentEPR) is designed to effectively recover and eliminate passwords from Microsoft Excel files, supporting all versions ranging from Excel 6 to 2024, including Microsoft 365 formats such as .xls, .xlsx, .xlsm, and .xlsb. It can instantly bypass Sheet, Workbook, Modify, and VBA protections, regardless of the complexity of the passwords. The tool employs a CPU-optimized brute force method, finely tuned at the assembly level for both Intel and AMD processors to recover passwords necessary for opening files. Users can choose from three distinct attack strategies: brute force, positional mask, and dictionary with mutations. The use of masks can significantly reduce the search space when certain parts of the password are already known, while the dictionary mode allows for the combination of up to four wordlists, applying over 20 mutation rules to enhance the search process. Furthermore, the software intelligently automates attack scenarios by chaining different methods together. With features like auto-saving progress, it operates fully offline and is available with both a graphical user interface (GUI) and command line interface (CLI), making it suitable for use on Windows 11 and 10 operating systems. This versatility ensures that users can recover their passwords efficiently and securely, regardless of their technical expertise.

Description

Ffuf is a high-speed web fuzzer developed in Go that allows users to conduct scans on live hosts through various lessons and scenarios, which can be executed either locally via a Docker container or through an online hosted version. It offers virtual host discovery capabilities that operate independently of DNS records. To effectively utilize Ffuf, users need to provide a wordlist containing the inputs they want to test. You can specify one or multiple wordlists directly in the command line, and if you are using more than one, it's important to assign a custom keyword to manage them correctly. Ffuf processes the first entry of the initial wordlist against all entries in the subsequent wordlist, then moves on to the second entry of the first wordlist, repeating this process until all combinations have been tested. This method ensures thorough coverage of potential inputs, and there are numerous options available for further customizing the requests made during the fuzzing process. By leveraging these features, users can optimize their web vulnerability assessments effectively.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Docker
Go
JSON
Microsoft Access

Integrations

Docker
Go
JSON
Microsoft Access

Pricing Details

$40/month
Free Trial
Free Version

Pricing Details

Free
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Passcovery Co. Ltd.

Founded

2008

Website

passcovery.com

Vendor Details

Company Name

Ffuf

Website

github.com/ffuf/ffuf

Product Features

Product Features

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