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mlsql VS SkillRisk.org

Compare mlsql VS SkillRisk.org and see what are their differences

mlsql

Infer SQL queries from plain-text questions and table headers.

Rating
0 reviews
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Alternatives Is it good?
SkillRisk.org

Free Agent Skill Security Analyzer for Claude AI. Detect dangerous permissions, code execution vulnerabilities, and data leaks before deployment. Secure your AI agents today.

Rating
0 reviews
Pricing
Freemium $5 / Monthly
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Alternatives Is it good?
DisplaySwitcher
Switch your monitor’s video input and seamlessly transfer text and files! A Linux/macOS/Windows Desktop Application. sponsored
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Which is more popular?

Based on our record, mlsql seems to be more popular. It has been mentioned 2 times since March 2021.

social mentions
2 vs 0
LMS popularity
100% vs 0%
alternatives listed
1 vs 14

Base details

Website, pricing, platforms and company facts side by side.

mlsql
SkillRisk.org
Website github.com skillrisk.org
Pricing —
Freemium $5 / Monthly Official pricing
Platforms —
Web
Company — 1 - 9 employees · 2026
Listed in
Education LMS Online Learning Web App +1
Developer Tools Security & Privacy AI Security AI Agents AI +2

About mlsql and SkillRisk.org

In their own words, as submitted to SaaSHub.

mlsql
SkillRisk.org

No description of mlsql yet.

SkillRisk is a specialized security analysis tool designed for the AI Agent ecosystem, specifically focusing on Claude Code and Model Context Protocol (MCP) skills. As developers give AI agents more permissions (shell access, file manipulation), the risk of executing malicious code increases....

Read more about SkillRisk.org

Features and specs

What each product offers, as listed by its team.

mlsql 0 features
SkillRisk.org 3 features

No features have been listed yet.

  • Hook Hijacking Detection
    Identifies malicious PreToolUse hooks that attempt to execute silent background commands or install malware.
  • Permission Auditing
    Flags skills requesting excessive privileges (e.g., unnecessary root/sudo access or write permissions to sensitive directories).
  • Data Leak Prevention
    Scans for hardcoded API keys, credentials, and potential data exfiltration patterns.

Analysis

An editorial look at what each product does well and who it suits.

mlsql
SkillRisk.org

Overall verdict

  • MLSQL is a solid open-source unified platform that blends SQL with machine learning, making data engineering and ML workflows accessible through a single, declarative language. It's a good choice for teams looking to streamline big data and ML pipelines without switching between multiple tools.

Why this product is good

  • It unifies data processing and machine learning under a single SQL-like syntax, lowering the learning curve for data teams.
  • Built on top of Apache Spark, it leverages a proven distributed computing engine for handling large-scale data.
  • Open-source and actively developed, allowing customization and community-driven improvements.
  • Supports the full ML lifecycle including data preprocessing, training, and deployment within one workflow.
  • Reduces the need to context-switch between separate ETL, analytics, and ML tools.

Recommended for

  • Data engineers and data scientists who prefer SQL-centric workflows
  • Teams working with big data on Apache Spark
  • Organizations wanting to unify ETL and machine learning pipelines
  • Companies seeking an open-source alternative to fragmented ML tooling
  • Analysts looking to build ML models without deep programming expertise

Overall verdict

  • There is not enough verifiable public information available to confirm whether SkillRisk.org is a legitimate, reputable, or high-quality service, so caution and independent verification are strongly advised before using it.

Why this product is good

  • The site does not appear to have widely recognized reviews, ratings, or established reputation in mainstream sources.
  • Details about ownership, business registration, and operational transparency are unclear or unverified.
  • Users should verify security measures, privacy policies, and data handling practices before sharing personal or sensitive information.
  • Independent third-party validation and customer testimonials are limited or absent, making trust difficult to establish.

Recommended for

  • Users who have independently verified the site's legitimacy and security
  • People who cross-check the service against trusted reviews before committing
  • Cautious individuals willing to test with minimal personal data first
  • Those who have confirmed the site's ownership and privacy practices meet their standards

Category popularity

How often each product is chosen within a category, 0–100% relative to the other.

Score bands 0–20 21–40 41–50 51–60 61–100
mlsql
SkillRisk.org
100% 100%
LMS
0% 0%
0% 0%
Developer Tools
100% 100%
100% 100%
Web App
0% 0%
0% 0%
AI Security
100% 100%

Questions & Answers

As answered by people managing mlsql and SkillRisk.org.

What makes your product unique?

SkillRisk.org's answer:

SkillRisk is the first dedicated security scanner built specifically for the Claude Code and Model Context Protocol (MCP) ecosystem. Unlike general-purpose code linters, SkillRisk understands agent-specific attack vectors—such as PreToolUse hook hijacking, implicit permission leaks in JSON/YAML definitions, and data exfiltration patterns in MCP server configurations. It brings "Static Application Security Testing" (SAST) to the world of AI Agents.

Why should a person choose your product over its competitors?

SkillRisk.org's answer:

Most traditional security tools audit application code but ignore the configuration layer of AI agents. You should choose SkillRisk because: Context-Aware: It detects risks specific to AI agents (e.g., giving an LLM rm -rf permissions) that standard linters miss. Pre-Runtime Safety: It allows you to audit third-party skills before you install them, preventing supply chain attacks. Privacy-First: Our "Local-First" architecture ensures your skill definitions are analyzed in-memory and never stored on our servers.

How would you describe the primary audience of your product?

SkillRisk.org's answer:

Our primary audience includes AI Engineers, DevOps professionals, and software developers who are building autonomous agents using Claude Code or implementing MCP servers. It is a must-have tool for anyone integrating community-contributed skills or third-party tools into their agent's workflow.

What's the story behind your product?

SkillRisk.org's answer:

We built SkillRisk after realizing a terrifying gap in the AI workflow: developers scrutinize human code in Pull Requests but blindly copy-paste "Skills" that give AI agents shell access. After witnessing an incident where a malicious "Color Picker" skill silently exfiltrated credentials and caused $54,000 in cloud bills, we decided to build a "firewall" for AI skills. We treat Agent Skills as executable code that requires strict auditing.

Which are the primary technologies used for building your product?

SkillRisk.org's answer:

The platform utilizes a custom-built Static Analysis Engine specifically tuned for parsing JSON, YAML, and Markdown skill definitions. It employs strictly typed rule sets to detect logic vulnerabilities and permission scopes without executing the code. The web interface is designed for zero-persistence data processing to ensure maximum security.

Who are some of the biggest customers of your product?

SkillRisk.org's answer:

AI Engineers within the Anthropic developer community DevOps teams using Vercel Infrastructure developers at Nvidia Open source maintainers of MCP servers

User comments

Share your experience with using mlsql and SkillRisk.org. For example, how are they different and which one is better?

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Social recommendations and mentions

Recommendations tracked on public social media and blogs since March 2021.

mlsql 2 mentions
SkillRisk.org 0 mentions
  • Download the files from Docker Container and locally edit them
    I am working on a project that requires me to take user input (as English) and return SQL queries. We will eventually be working with multiple datasets, which is why the valuenet over at https://github.com/paulfitz/mlsql ended up being... Source: over 4 years ago
  • Clone and edit Docker Projects hosted on Github
    I found this great resource here: https://github.com/paulfitz/mlsql. Source: almost 5 years ago

Tracking SkillRisk.org since Jan 2026.

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