Search Results for "output"

Nikto is an open-source web server scanner that performs comprehensive tests to detect potentially dangerous files, outdated server software, and configuration issues. It’s widely used by penetration testers and security professionals for auditing web applications and infrastructure. Nikto supports multiple output formats and can integrate with other tools for automated scanning workflows.

...Checks for misconfigurations across all major (and some minor) cloud providers. Applies (and embellishes) user-defined Rego policies. Supports multiple output formats: CLI, JSON, SARIF, CSV, CheckStyle, and JUnit. Configurable (via CLI flags and/or config file). Very fast, capable of quickly scanning huge repositories. Plugins for popular IDEs available (JetBrains, VSCode and Vim).

Flan Scan is a lightweight open-source network vulnerability scanner designed to make it easy to detect exposed services, open ports, and associated vulnerabilities across IP ranges or network segments as part of security audit and compliance workflows. It is essentially a thin wrapper around the widely-used Nmap scanner, augmenting it with scripts and tooling that transform raw Nmap output into vulnerability-focused reports that map detected services to known CVEs, making results more actionable for administrators and auditors. Flan Scan supports automated builds via Docker and can be deployed in containers or Kubernetes clusters, allowing organizations to run scans consistently across distributed environments. Users provide target IPs or CIDR ranges, and the tool orchestrates Nmap scans with version detection and the “vulners” NSE script, collects results, and outputs aggregated reports in formats like LaTeX, markdown, or JSON.

Brakeman is a free vulnerability scanner specifically designed for Ruby on Rails applications. It statically analyzes Rails application code to find security issues at any stage of development. Brakeman now uses the parallel gem to read and parse files in parallel. By default, parallel will split the reading/parsing into a number of separate processes based on number of CPUs. In testing, this has dramatically improved speed for large code bases, around 35% reduction in overall scan time....