local-skill-inventory-scanning
Scans the local machine's filesystem to enumerate dangerous AI agent skills and capabilities, analyzing tool definitions, function signatures, and executable permissions to identify security risks before deployment. Works by traversing configured skill directories, parsing skill metadata and schemas, and cross-referencing against a threat database of known dangerous operations (file system access, network calls, code execution). Detects skills that could be exploited via prompt injection or supply chain compromise.
Unique: Performs offline, filesystem-based skill enumeration with threat pattern matching against a curated dangerous-operations database, enabling detection of risky capabilities before they're exposed to untrusted LLM inputs — unlike cloud-based security scanners that require uploading agent configs
vs alternatives: Faster and more privacy-preserving than cloud-based agent security scanners because it runs entirely locally without transmitting skill definitions or configurations to external services
mcp-configuration-validation
Validates MCP (Model Context Protocol) server configurations for security misconfigurations, malformed schemas, and dangerous parameter bindings. Parses MCP config files, validates tool schemas against JSON Schema standards, checks for unsafe parameter types (shell commands, file paths), and detects overly-permissive tool definitions that could enable privilege escalation. Works by loading config files, performing static analysis on tool definitions, and cross-referencing against known MCP security patterns.
Unique: Performs schema-aware validation of MCP configurations with pattern matching for dangerous parameter types (shell commands, file paths, network operations), detecting unsafe tool bindings that standard JSON Schema validators would miss
vs alternatives: More comprehensive than generic JSON schema validators because it understands MCP-specific security patterns and dangerous tool categories, not just structural validity
prompt-injection-resistance-testing
Executes automated prompt injection attacks against configured agents to measure resistance and identify vulnerabilities. Generates adversarial prompts using known injection techniques (prompt breakout, jailbreak patterns, instruction override), sends them to the agent, and analyzes responses to detect if the agent was successfully manipulated into executing unintended actions or revealing sensitive information. Uses a library of injection payloads and pattern matching to detect successful exploits.
Unique: Executes a curated library of prompt injection payloads against live agents and analyzes responses using pattern matching to detect successful exploits, providing quantified vulnerability metrics rather than just binary pass/fail results
vs alternatives: More practical than manual red-teaming because it automates payload generation and response analysis, and more comprehensive than static analysis because it tests actual agent behavior under adversarial conditions
supply-chain-attack-monitoring
Monitors agent dependencies, MCP server sources, and skill packages for signs of supply chain compromise or malicious modifications. Tracks file hashes, version changes, and source integrity, comparing against known-good baselines and checking for suspicious modifications to skill definitions or MCP configs. Detects when dependencies have been updated with potentially malicious code, when MCP servers have been replaced with compromised versions, or when skill definitions have been altered unexpectedly.
Unique: Maintains cryptographic baselines of agent dependencies and MCP server files, detecting unauthorized modifications through hash comparison and version tracking, enabling detection of supply chain attacks that modify code after initial deployment
vs alternatives: More proactive than reactive incident response because it continuously monitors for changes rather than only detecting attacks after they've caused damage, and more comprehensive than package manager security because it tracks actual file integrity rather than just known CVEs
live-mcp-server-tool-poisoning-audit
Connects to running MCP servers and audits their exposed tools for poisoning, malicious behavior, or unexpected modifications. Introspects tool schemas, tests tool execution with benign inputs, analyzes tool responses for suspicious patterns, and compares against expected behavior baselines. Detects tools that have been replaced with malicious versions, tools with hidden parameters that could be exploited, or tools that execute unexpected side effects.
Unique: Performs runtime introspection and behavioral testing of live MCP server tools, comparing actual tool responses against expected baselines to detect poisoning attacks that modify tool behavior without changing tool schemas
vs alternatives: More effective than static configuration validation because it tests actual tool behavior at runtime, catching poisoning attacks that only manifest during execution rather than in configuration files
dangerous-operation-pattern-detection
Identifies skills and tools that perform dangerous operations (file system access, network calls, code execution, privilege escalation) by analyzing tool definitions, function signatures, and parameter types. Uses pattern matching against a curated database of dangerous operation categories and risk levels. Categorizes risks by severity and provides context about why each operation is dangerous and how it could be exploited.
Unique: Maintains a curated database of dangerous operation patterns (file I/O, network access, code execution, privilege escalation) and matches skill definitions against these patterns with severity scoring, providing context about exploitation risk for each detected operation
vs alternatives: More comprehensive than generic code analysis because it understands AI agent-specific attack vectors and dangerous operation categories, not just general code quality issues
security-report-generation
Aggregates findings from all scanning and testing modules into comprehensive security reports with executive summaries, detailed vulnerability listings, risk scoring, and remediation guidance. Generates reports in multiple formats (JSON, HTML, PDF) with customizable detail levels. Includes trend analysis if historical reports are available, showing security posture improvements or regressions over time.
Unique: Aggregates findings from multiple security scanning modules (skill inventory, MCP validation, prompt injection testing, supply chain monitoring, tool poisoning audits) into unified reports with risk scoring and trend analysis across time
vs alternatives: More comprehensive than individual scan reports because it correlates findings across multiple security dimensions and provides historical trend analysis, enabling better tracking of security improvements
cli-based-security-orchestration
Provides a command-line interface for orchestrating all agentseal security operations, enabling integration into CI/CD pipelines, scheduled security scans, and manual security audits. Supports subcommands for each security module (scan, validate, test, monitor, audit), configuration via CLI flags and config files, and exit codes that enable automated decision-making (fail CI/CD if vulnerabilities found). Enables scripting and automation of security workflows.
Unique: Provides a unified CLI interface for orchestrating multiple security scanning and testing modules with support for configuration files, exit codes for CI/CD integration, and structured output formats enabling automation and integration into existing security workflows
vs alternatives: More flexible than GUI-only tools because it enables scripting, CI/CD integration, and automation, and more comprehensive than single-purpose CLI tools because it orchestrates multiple security modules from one interface