Security audit

fit-device-id-modifier

Security checks for vulnerabilities and agentic risk

Overview

This skill does what it says by creating modified copies of FIT ride files, but its simple binary editing can corrupt outputs or overwrite existing generated files.

Install only if you are comfortable running a local Python script that modifies copies of your FIT files. Use a virtual environment, pin or review fitparse, keep backups, and avoid running it on directories where existing _GM.fit files should be preserved.

A.I.G

Vulnerability Patterns

Insecure DependenciesIntroduces malicious components through unsafe dependency sources
Insecure Skill Coding PracticesFinds exploitable flaws such as hardcoded secrets or command injection
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

Findings (3)

T09 · Insecure Skill Coding Practices

Error

Location: scripts/modify_fit.py:52
Finding: Context-Free Binary Replacement Can Corrupt FIT Files
Content: View full analysis
Remediation: View remediation

T09 · Insecure Skill Coding Practices

Warning

Location: scripts/modify_fit.py:125
Finding: Unsafe Output Path Derivation and Silent File Overwrite
Content: View full analysis
Remediation: View remediation

T08 · Insecure Dependencies

Note

Location: SKILL.md:14
Finding: Unpinned Third-Party Dependency Installation
Content: View full analysis
Remediation: View remediation

SkillSpector

Vulnerability Patterns

Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
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
Excessive AgencyUnrestricted Tool Access, Autonomous Decision Making, Scope Creep

Findings (1)

Natural-Language Policy Violations

Medium

Category: Not specified by scanner
Confidence: 90% confidence
Finding: This file uses Chinese-only natural-language docstrings, comments, and user-facing print messages, including the main success and status outputs. That imposes a specific language on users without any opt-in, language selection mechanism, or documented justification that the skill is intended only for a Chinese-speaking context.
Content: No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.