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Security audit

ai-decision-log

Security checks for vulnerabilities and agentic risk

Overview

This is a local AI-decision logging utility with documentation and manifest mismatches, but no deceptive, network, credential, or background persistence behavior was found.

Before installing, treat this as a simple local logging helper. Use the script's --help output as authoritative, choose the ledger path deliberately, and avoid logging sensitive evidence unless local storage is acceptable. For production use, the publisher should align the schema and documentation and remove unnecessary broad tool declarations such as WebFetch.

Vulnerability Patterns
  • Skill Instruction HijackingAlters the agent's session goals or safety constraints when the skill loads
  • Agent Memory PoisoningWrites attacker-controlled rules into memory that affect later sessions
  • Remote Payload Retrieval and ExecutionFetches external code whose behavior can change after review
  • Embedded Malicious CodeShips malicious scripts inside the skill and executes them locally
  • Unauthorized Access and Privilege EscalationObtains permissions beyond the task's legitimate needs
Vulnerability Patterns
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
  • MCP Tool PoisoningHidden Instructions, Unicode Deception, Parameter Description Injection
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
  • Supply ChainUnpinned Dependencies, External Script Fetching, Obfuscated Code
Findings (5)

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
92% confidence
Finding

The file is written entirely in Chinese and presents itself as the agent-facing instruction manual, but it does not state that Chinese is optional, configurable, or limited to a justified region-specific context. Under the policy, forcing a specific language without user opt-in is a natural-language policy violation.

Content

No source excerpt is available for this finding.

Intent-Code Divergence

Medium
Category
Not specified by scanner
Confidence
96% confidence
Finding

The English usage section documents CLI flags like --decision-data, --time-stamp, and --generate-report, but the declared interface schema exposes different inputs such as command, decision, model, evidence, reviewer, file, and json. This mismatch can cause operators or calling agents to invoke the skill incorrectly, potentially omitting expected audit fields or generating incomplete records, which undermines governance and compliance assurances.

Content

No source excerpt is available for this finding.

Intent-Code Divergence

Medium
Category
Not specified by scanner
Confidence
96% confidence
Finding

The Chinese usage documentation repeats and expands behavior that conflicts with the declared interface, describing different flags and execution semantics than the schema above. In a compliance-focused logging skill, such ambiguity is security-relevant because it can lead to failed logging, missing human-review markers, or false assumptions that review coverage is being measured when it is not.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
95% confidence
Finding

The file’s natural-language content is entirely in Chinese and presents the skill description and instructions in that language without offering any language choice or documenting a justified locale restriction. This can violate language/locale policy when users or agents are not given an opt-in or alternative language.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Low
Category
Not specified by scanner
Confidence
77% confidence
Finding

The changelog explicitly states a 'Bilingual rewrite (full EN+ZH, English first)' and the document then leads with an English section before Chinese. This sets a language preference in the skill's natural-language presentation without indicating that users can choose their preferred language or locale.

Content

No source excerpt is available for this finding.