Securewoof vs Promptfoo

Side-by-side comparison · Updated April 2026

 SecurewoofSecurewoofPromptfooPromptfoo
DescriptionSecureWoof provides an AI-powered malware scanner that leverages the SOREL-20M malware dataset to train RoBERTa and FastText models. When users upload an executable file, it undergoes a series of checks and transformations, including static Yara rules, unpacking with Retdec, decompiling with Ghidra, formatting with clang-tidy, embedding with FastText, and final evaluation by a RoBERTa transformer network. SecureWoof also offers a free public API for easy integration and use.Promptfoo is an open-source tool designed to ensure the security and reliability of LLM (Large Language Models) applications. It offers a comprehensive vulnerability scanner specifically tailored to each LLM product, providing customized probes for detecting PII leaks, unauthorized prompt manipulations, and other critical failures. With capabilities like caching, concurrency, and detailed vulnerability reports, Promptfoo allows developers to build, test, and refine LLM applications efficiently with test-driven development rather than trial-and-error.
CategorySecurityApplicationSecurityApplication
RatingNo reviewsNo reviews
PricingN/AN/A
Starting PriceN/AN/A
Use Cases
  • Cybersecurity Experts
  • Software Developers
  • IT Administrators
  • Researchers
  • Developers of LLM applications
  • Security Analysts
  • Open-Source Contributors
  • Large Organizations
Tags
Malware ScannerAISOREL-20MRobertaFastText
open-sourcesecurityreliabilityLLMvulnerability scanner
Features
AI-powered malware scanning
Trained on SOREL-20M dataset
Utilizes RoBERTa transformer network
Static Yara rule checking
Unpacking with Retdec
Decompiling with Ghidra
Formatting with clang-tidy
Embedding with FastText
Free public API available
Advanced detection capabilities
Open-source
Customized vulnerability probes
Detection of PII leaks
Protection against unauthorized prompt manipulations
Prevention of jailbreaks
Detailed vulnerability reports
Support for multiple LLM API providers
Local operation without cloud dependencies
Test-driven LLM development
Community-supported
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