Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

OSS-Fuzz provides ongoing fuzz testing for open source applications, a method renowned for identifying programming flaws. Such flaws, including buffer overflow vulnerabilities, can pose significant security risks. Through the implementation of guided in-process fuzzing on Chrome components, Google has discovered thousands of security weaknesses and stability issues, and now aims to extend this beneficial service to the open source community. The primary objective of OSS-Fuzz is to enhance the security and stability of frequently used open source software by integrating advanced fuzzing methodologies with a scalable and distributed framework. For projects that are ineligible for OSS-Fuzz, there are alternatives available, such as running personal instances of ClusterFuzz or ClusterFuzzLite. At present, OSS-Fuzz is compatible with languages including C/C++, Rust, Go, Python, and Java/JVM, with the possibility of supporting additional languages that are compatible with LLVM. Furthermore, OSS-Fuzz facilitates fuzzing for both x86_64 and i386 architecture builds, ensuring a broad range of applications can benefit from this innovative testing approach. With this initiative, we hope to build a safer software ecosystem for all users.

Description

SDRR was created to fulfill nearly all of your saturation needs, offering an extensive array of controls that allow you to tailor the saturation's character to your exact preferences. This versatile tool features four primary modes—TUBE, DIGI, FUZZ, and DESK—that respond dynamically to your input signal. Each mode showcases its distinct crosstalk behavior, which can either be turned off or accentuated to suit your requirements. Additionally, SDRR includes a one-of-a-kind RMS level difference metering mode that simplifies the process of level matching. This powerful plugin can serve multiple purposes: acting as a saturation unit, a compressor, an EQ, a bit-crusher, a subtle stereo widener, or even imparting movement to your tracks through the DRIFT control. With SDRR, you can enhance your music by adding warmth, depth, and character. Moreover, be sure to explore the complimentary IVGI, which functions as SDRR's smaller counterpart, drawing inspiration from the DESK mode. SDRR is compatible with both macOS and Windows, all bundled into a single license for your convenience. This makes it an exceptionally valuable addition to any producer's toolkit.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Atheris Yes 
C Yes 
C++ Yes 
ClusterFuzz Yes 
GitHub Yes 
Go Yes 
Google Cloud Storage Yes 
Java Yes 
Python Yes 
Rust Yes 

Integrations

Atheris No 
C No 
C++ No 
ClusterFuzz No 
GitHub No 
Go No 
Google Cloud Storage No 
Java No 
Python No 
Rust No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

€23 one-time payment
Free Trial No 
Free Version No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Google

Country

United States

Website

github.com/google/oss-fuzz

Vendor Details

Company Name

Klanghelm

Founded

2011

Country

Germany

Website

klanghelm.com/contents/products/SDRR.html

Product Features

Product Features

Alternatives

Alternatives

Klanghelm DC1A Reviews

Klanghelm DC1A

Klanghelm
ClusterFuzz Reviews

ClusterFuzz

Google
LibFuzzer Reviews

LibFuzzer

LLVM Project
Klanghelm DC8C Reviews

Klanghelm DC8C

Klanghelm