Mongo Manager Free

• Outcome: Review
• Latest audit: Sep 16, 2026 · 10:31 AM UTC
• Version: 1.0.0

Overview

This MongoDB skill is mostly a guide, but it grants command execution and describes database create, modify, delete, reset, import, and export operations without clear safety controls.

Install only if you want an agent to help with MongoDB design and operations. Before allowing it to use `exec` or a real `MONGODB_URI`, require explicit confirmation for any write, delete, reset, import, or export action, verify the target database is not production unless intended, and use backups or dry runs where possible.

A.I.G

Vulnerability Patterns

• Insecure Dependencies: Introduces malicious components through unsafe dependency sources
• Skill Instruction Hijacking: Alters the agent's session goals or safety constraints when the skill loads
• Agent Memory Poisoning: Writes attacker-controlled rules into memory that affect later sessions
• Remote Payload Retrieval and Execution: Fetches external code whose behavior can change after review
• Embedded Malicious Code: Ships malicious scripts inside the skill and executes them locally

Findings (1)

T08 · Insecure Dependencies

Note

• Location: SKILL.md:306

Finding

Unpinned Third-Party Package Installation

Content

View full analysis

Vulnerability Details

File Location: SKILL.md:306
Vulnerability Type: Unpinned dependency installation
Risk Level: Low

shell

pip install pymongo

Technical Analysis

The documented installation command resolves and installs the latest version of pymongo available from the package index at execution time. It does not pin an audited version or verify package integrity with cryptographic hashes.

Consequently, installation results may change over time without any modification to the Skill. If the upstream package, release process, package index, or dependency chain is compromised, package-controlled build or installation logic could execute in the local environment. No evidence indicates that pymongo itself is malicious; this finding concerns the unsafe dependency-management practice.

Attack Path

1. An agent or user follows the dependency installation guidance in SKILL.md.
2. pip resolves the current package release and its dependency graph from the configured package index.
3. An attacker who has compromised an upstream release, dependency, maintainer account, or package-distribution channel supplies malicious package content.
4. pip downloads and installs that uncontrolled release.
5. Malicious build or installation logic executes with the privileges of the user running pip.

Impact Assessment

Successful exploitation could execute arbitrary code with the privileges of the invoking user. Potential effects include modification of the active Python environment, access to files and environment variables available to that user, theft of MongoDB connection credentials such as MONGODB_URI, and compromise of projects or processes using the affected environment.

The scope is limited by the invoking account's permissions. The documented dependency is optional, and exploitation requires compromise or malicious alteration of the package supply chain.

Remediation

View remediation

Remediation Suggestions

1. Pin pymongo to a reviewed, supported version instead of resolving the latest release dynamically.
2. Record dependencies in a requirements or lock file with cryptographic hashes.
3. Install with hash verification, for example:

shell

python -m pip install --require-hashes -r requirements.txt

4. Generate and review the complete transitive dependency lock before deployment.
5. Install dependencies inside a dedicated virtual environment or isolated container using a non-privileged account.
6. Use an approved package index or internal mirror with provenance, malware scanning, and access controls.
7. Periodically update pinned versions through a controlled review and vulnerability-scanning process.

SkillSpector

Vulnerability Patterns

• Excessive Agency: Unrestricted Tool Access, Autonomous Decision Making, Scope Creep
• Trigger Abuse: Overly Broad Trigger, Shadow Command Trigger, Keyword Baiting Trigger
• MCP Tool Poisoning: Hidden Instructions, Unicode Deception, Parameter Description Injection
• Prompt Injection: Instruction Override, Hidden Instructions, Exfiltration Commands
• Data Exfiltration: External Transmission, Env Variable Harvesting, File System Enumeration

Findings (4)

Intent-Code Divergence

Medium

• Category: Not specified by scanner
• Confidence: 97% confidence

Finding

The skill metadata says it is not suitable for database architecture decisions, but the body contains substantial Schema design guidance and explicit embed-vs-reference decision rules. This mismatch can cause the agent to invoke the skill in contexts the maintainer claims to exclude, leading to unsafe or low-governance architectural advice being presented as applicable guidance.

Content

No source excerpt is available for this finding.

Vague Triggers

Medium

• Category: Not specified by scanner
• Confidence: 94% confidence

Finding

The usage trigger is overly broad, including generic database operations, SQL queries, and data storage management, even though the skill is MongoDB-specific and not SQL-focused. Broad activation criteria increase the chance that an agent will select this skill in unrelated or partially related contexts, producing incorrect guidance or enabling risky operations through the listed tools.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium

• Category: Not specified by scanner
• Confidence: 92% confidence

Finding

The skill describes create, modify, delete, save, export, reset, and import operations and exposes exec capability, but it does not require confirmation, dry-run behavior, environment scoping, or rollback safeguards. In a database context, ambiguous operational instructions can lead an agent to perform destructive or irreversible actions against real data stores without sufficient user intent verification.

Content

No source excerpt is available for this finding.

Vague Triggers

Medium

• Category: Not specified by scanner
• Confidence: 93% confidence

Finding

The keyword coverage section enumerates very broad and ordinary terms such as Agent, Use, when, SQL, and storage-management phrases, which weakens trigger precision. In an agent ecosystem, such unconstrained matching can cause frequent accidental invocation and expand the operational reach of a skill that also advertises exec-based actions.

Content

No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.