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Average Ratings 0 Ratings

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features
design
support

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Write a Review

Description

Devirt offers a specialized service for binary devirtualization and reverse engineering tailored for security researchers and malware analysts. Programs protected by tools like VMProtect and Themida obscure their internal logic by using private virtual machines. The Devirt service monitors the execution of these protected applications, meticulously reconstructing the state and control flow of the virtual machine, transforming that behavior into native functions, and validating them against the original code. Clients have the flexibility to select their desired output format, which may include an IDA database, annotated pseudocode, a comprehensive reverse engineering report, LLVM IR, or structured JSON. Each recovery is accompanied by a coverage ledger that distinguishes between code that has been validated under specified assumptions and code that remains unresolved, dependent on runtime conditions, or permanently limited, enabling analysts to pinpoint exactly where the evidence concludes. This structured approach enhances the analysis process, providing clarity and precision in understanding the devirtualized code.

Description

LibFuzzer serves as an in-process, coverage-guided engine for evolutionary fuzzing. By being linked directly with the library under examination, it injects fuzzed inputs through a designated entry point, or target function, allowing it to monitor the code paths that are executed while creating variations of the input data to enhance code coverage. The coverage data is obtained through LLVM’s SanitizerCoverage instrumentation, ensuring that users have detailed insights into the testing process. Notably, LibFuzzer continues to receive support, with critical bugs addressed as they arise. To begin utilizing LibFuzzer with a library, one must first create a fuzz target—this function receives a byte array and interacts with the API being tested in a meaningful way. Importantly, this fuzz target operates independently of LibFuzzer, which facilitates its use alongside other fuzzing tools such as AFL or Radamsa, thereby providing versatility in testing strategies. Furthermore, the ability to leverage multiple fuzzing engines can lead to more robust testing outcomes and clearer insights into the library's vulnerabilities.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

No images available

Screenshots View All

Integrations

Atheris No 
C No 
C++ No 
ClusterFuzz No 
Fuzzbuzz No 
Google ClusterFuzz No 
Jazzer No 

Integrations

Atheris Yes 
C Yes 
C++ Yes 
ClusterFuzz Yes 
Fuzzbuzz Yes 
Google ClusterFuzz Yes 
Jazzer Yes 

Pricing Details

No price information available.
Free Trial Yes 
Free Version Yes 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Deployment

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

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac No 
Linux Yes 
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) Yes 
In Person No 

Types of Training

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

Vendor Details

Company Name

Devirt

Founded

2026

Website

devirt.re

Vendor Details

Company Name

LLVM Project

Founded

2003

Website

llvm.org/docs/LibFuzzer.html

Product Features

Cybersecurity

AI / Machine Learning No 
Behavioral Analytics No 
Endpoint Management No 
IOC Verification No 
Incident Management No 
Tokenization No 
Vulnerability Scanning No 
Whitelisting / Blacklisting No 

Product Features

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