php2shell-checker

Shannon is an open-source autonomous AI penetration-testing tool developed by Keygraph for web applications and APIs. It analyzes source code to map architecture, trust boundaries, data flows, interfaces, dependencies, and potential attack paths, then combines those candidates with live reconnaissance and specialized testing for injection, XSS, SSRF, authentication, and authorization. Exploitation agents use browser automation and command-line tools against a running application to produce reproducible proof-of-concept attacks; candidates that cannot be demonstrated are discarded, so only exploited vulnerabilities become findings. Shannon runs locally from the command line or in CI/CD, including GitHub Actions and GitLab CI/CD, and can test deployed staging or development environments on pull-request, release, or scheduled workflows. It produces evidence-rich PDF and Markdown reports plus JSON and SARIF 2.1.0 output, supports authenticated testing and resumable workspaces, and can gate a pipeline on proven vulnerabilities at configured severity levels. The open-source edition runs in an ephemeral Docker worker, mounts the target repository read-only, stores results locally, and uses credentials supplied for a selected model provider or compatible local endpoint. Shannon is licensed under AGPL-3.0. It actively executes exploits and may mutate application state, so the project requires authorization and recommends sandboxed, staging, or local environments rather than production systems.

Codex Security is an OpenAI CLI and TypeScript SDK for finding, validating, and fixing security vulnerabilities in authorized code repositories. It scans directories and codebases, including repository changes, uses AI-assisted analysis to trace attack paths and apply custom threat models, validates findings, and can generate reviewable patches and exports in SARIF, JSON, and CSV formats. The CLI supports CI use with an API key and can stop builds at a selected severity threshold. The package also supports configurable deep scans, worker and subagent counts, time limits, containerized bulk scans, and a preview findings service. The service stores findings and embeddings in SQLite, provides paginated listings and a read-only dashboard, identifies potential duplicates through embedding similarity, and allows completed findings to be published and deduplicated through the CLI or SDK. It requires Node.js 22.13.0 or later and Python 3.10 or later, and can use OpenAI or other documented inference providers.

Bashka is a command-line safety guard for the `curl ... | bash` installation pattern. It parses incoming shell scripts, scores them against checks for credential theft, data exfiltration, reverse shells, destructive commands, insecure downloads, persistence, obfuscation, and other hazards, and can follow forwarded or nested scripts so each layer is reviewed before execution. It can also provide the script for manual or AI-assisted analysis. Bashka records software installed through it in an installation registry, including detected binaries and created directories. Its commands can list and inspect recorded packages, rerun their installers, and remove tracked files. It supports configuration for review behavior, remote-script following, recursion depth, command limits, trusted domains, and interface style. The project is open source under the MIT license and is distributed as a shell-installed or prebuilt binary, including through Homebrew, Cargo, mise, and GitHub releases. Its documentation notes that static analysis cannot reliably detect every behavior in a Turing-complete shell script, that direct paths such as `/bin/bash` bypass its PATH shim, and that the registry cannot manage files whose installation locations it cannot detect.

SkillSpector is an open-source security scanner for AI agent skills, developed by NVIDIA. It scans Git repositories, URLs, ZIP archives, directories, and individual skill files before installation, looking for prompt injection, data exfiltration, privilege escalation, supply-chain issues, dangerous code, MCP permission problems, tool poisoning, and other malicious patterns. Its two-stage pipeline combines static analysis—including regex, Python AST, taint tracking, YARA signatures, and OSV.dev dependency lookups—with optional LLM-based semantic evaluation. It produces terminal, JSON, Markdown, or SARIF reports containing findings, severity labels, a 0–100 risk score, and installation recommendations. Baselines can suppress accepted findings, and the CLI can be used in CI or install gates through exit codes and machine-readable output. SkillSpector can also run as an MCP server callable by compatible agents. It does not execute scanned skills or sandbox them; optional LLM analysis sends eligible file contents to the configured provider, while dependency checks query OSV.dev. The project is distributed under the Apache License 2.0 and is part of NVIDIA's Verified Skills pipeline.

AgentGuard is a web-based scanner for AI-agent Skills, including SKILL.md instructions. It combines deterministic pattern checks with AI-assisted analysis to identify capabilities and risks such as shell-command execution, file-system access, environment-variable and credential access, network requests, external downloads, suspicious URLs, obfuscated instructions, prompt-injection patterns, and destructive operations. It produces a trust report with security and quality scores, a risk rating, detected capabilities, findings, explanations, and recommendations. The scanner is free to use, requires no account, accepts up to 80,000 characters of Skill text, and is designed for analysis before installation.