NYC

AgentDB Memory Patterns

Fail

Audited by Gen Agent Trust Hub on Feb 17, 2026

Risk Level: HIGHEXTERNAL_DOWNLOADSREMOTE_CODE_EXECUTIONCOMMAND_EXECUTION
Full Analysis
  • EXTERNAL_DOWNLOADS (HIGH): The skill extensively uses npx agentdb@latest for initialization, querying, and performance benchmarking. This pattern fetches and executes the most recent version of the agentdb package from the npm registry. Since the package is not from a trusted organization (as defined in the TRUST-SCOPE-RULE), this constitutes downloading and executing unverifiable remote code.
  • REMOTE_CODE_EXECUTION (HIGH): Instructions for setting up the MCP server (claude mcp add agentdb npx agentdb@latest mcp) create a persistent remote execution vector. Whenever the agent uses this tool, it will execute code downloaded on-the-fly from the npm registry.
  • COMMAND_EXECUTION (MEDIUM): The skill provides numerous CLI commands that interact with the local file system (migrate --source, init ./agents.db, export ./backup.json). If the dynamically downloaded agentdb package were compromised, these commands would grant an attacker full access to read or write local files.
  • DYNAMIC_EXECUTION (MEDIUM): The create-plugin functionality allows the agent to generate and potentially load new logic based on templates (e.g., decision-transformer). This dynamic assembly of logic from external templates increases the attack surface for malicious code injection.
  • INDIRECT_PROMPT_INJECTION (LOW): This skill has a significant ingestion surface as it stores conversation data as 'patterns' and retrieves them to 'synthesize context'.
  • Ingestion points: adapter.insertPattern and adapter.retrieveWithReasoning in SKILL.md.
  • Boundary markers: Absent. No evidence of delimiters or instructions to the LLM to ignore embedded commands in retrieved memory.
  • Capability inventory: The skill has file system access (via CLI) and network-adjacent capabilities (via MCP/npx).
  • Sanitization: Absent. Data is stored and retrieved as raw JSON strings without visible escaping.
Recommendations
  • AI detected serious security threats
Audit Metadata
Risk Level
HIGH
Analyzed
Feb 17, 2026, 06:24 PM