AI Code Detector

Analyze HTML, JavaScript, and PHP code to determine if it was generated by AI tools

if (similarity > threshold) { return true; // plagiarism detected } function compareCode(a, b) { let similarity = 0;
AI Code Detector -AICodePlag Checker
Paste your code here to analyze whether it was generated by AI.

Key Features

Multi-Language Support

Detects AI-generated code in HTML, JavaScript, and PHP with language-specific analysis.

Pattern Recognition

Identifies AI signature patterns and common structures used by code generation models.

AI Code Detection

Identifies AI-generated scripts with precision.

Syntax Analysis

Examines syntax patterns to distinguish between human and AI-written code.

Machine Learning Algorithms

Uses trained models to improve detection accuracy.

Real-Time Analysis & Reports

Scan code snippets in seconds, not hours. Highlights suspicious lines and explains why.

About AI Code Detector

An AI Code Detector Tools designed to distinguish between code written by humans and code generated by artificial intelligence, which has become essential for maintaining code integrity in academic and professional settings. By analyzing patterns, syntax, and stylistic markers, it provides a percentage breakdown of AI-generated versus human-generated content. This tool is perfect for developers, educators, and organizations aiming to verify code originality and maintain integrity in software projects.

AICodePlag is a professional tool designed to identify whether programming languages code was generated by AI tools like ChatGPT, Claude, grok, deepseek or Gemini AI assistants.

Supported Languages

HTML
JavaScript
Java
Python
C
C++
Visual Basic
C#
PHP

Note: While our AICodePlag tool provides a high level of accuracy, no detection method is 100% perfect. Results should be used as guidance rather than definitive proof.

Understanding AI Code Detector Tool

Types of AI Code Detector Tools in 2025:

Choose the right AI generated code detector for your specific needs:

    ✔️Pattern-Based AI Code Detectors: Flag repetitive syntax or rigid structures common in AI-generated code with 85% accuracy
    ✔️Syntax-Focused Detectors: Detect deviations from human coding conventions (inconsistent formatting, variable naming)
    ✔️Statistical Detectors: Calculate AI probability using perplexity metrics (lower scores = likely AI-generated)
    ✔️Hybrid Detectors: Combine pattern recognition + statistical analysis for 92% accuracy (according to Stanford research)
    ✔️ Language-Specific AI Code Checkers: Tailored to specific languages like C++,Java,PHP or C#, offering deeper insights for niche use cases.

Benefits of Using the AI Code Detector Tool

    ✔️Verify Code Authenticity: Confirm whether code is human-written or AI-generated for academic integrity, open-source projects, or freelance work verification
    ✔️Save Valuable Time: Our recommended AI code detectors scan 10,000+ lines of code in seconds—eliminating tedious manual reviews
    ✔️Quality Control: Helps maintain high standards by detecting potentially generic or error-prone AI-generated code.
    ✔️Multi-Language Support: 'AICodePlag' checkers work with Python, JavaScript, Ruby, and more popular languages
    ✔️Free AI Code Detector Options Available Start with basic detection AICodePlag' tools at no cost

How AI Code Detectors Actually Work?

The code AI detector at AiCodePlag.com utilizes a multi-layered approach to identify AI-generated code with unprecedented accuracy. Our system analyzes:

  • 1️⃣ Structural Patterns:AI tends to generate code with recognizable patterns in formatting, variable naming conventions, and function structures. Our detector has been trained on millions of code samples to recognize these subtle patterns that often elude human reviewers.
  • 2️⃣ Comparison with Known AI-Generated Code Databases: By comparing against databases, tools identify similarities, as seen in Check If Code Uses AI | AI Generated Code Detector | Free AI tool.
  • 3️⃣ Using Perplexity and Burstiness Measures: Perplexity measures predictability, and burstiness assesses variability, with lower values ​​often indicating AI generation, as noted in How Do AI Detectors Work? | Methods & Reliability.
  • 4️⃣ Tokenization and Feature Extraction: The detector breaks code into smaller components (tokens) to identify patterns. It examines variable names, function structures, and indentation styles.
AI Detector Image

Can AI Detection Be Wrong?

Research suggests AI detection can err, with significant implications:

    1️⃣ False Positives and False Negatives: Human code might be flagged as AI, and AI code missed, as discussed in The Truth About AI Detectors - More Harm Than Good.
    2️⃣ Biases in Detection Algorithms: Non-native English speakers are often wrongly flagged, as seen in Can AI Detectors Be Wrong? A Comprehensive Analysis.
    3️⃣ Importance of Caution: Tools should be part of a broader assessment, not sole reliance, as highlighted in AI Detectors Don't Work. Here's What to Do Instead..

Who Benefits from Our Code AI Detector?

Research suggests AI detection can err, with significant implications:

    1️⃣ For Educators Maintain academic integrity by quickly identifying AI-generated code submissions. Our AI code detector helps ensure students are developing genuine coding skills.
    2️⃣ For Businesses:Verify the originality of code during hiring processes or when reviewing contractor submissions. Our code AI detector helps protect your intellectual property.
    3️⃣ For Developers Validate the authenticity of open-source contributions and ensure compliance with your organization's AI usage policies.
    4️⃣ For Interview Processes:Verify that coding challenge submissions represent a candidate's true abilities rather than the capabilities of an AI assistant. Our AI code detector helps hiring managers make more informed decisions about technical talent.

Limitations of AI Code Detectors

While powerful, these tools have constraints:

  • False Positives: Simple human code may be flagged as AI (e.g., basic Python scripts).
  • Bias Risks: Non-native English developers often face unfair flags due to rigid syntax checks.
  • Evolving AI Models: Newer systems like GPT-4 reduce detection accuracy by 12-15%.

Always combine tool results with manual review for critical projects.

The Future of AI-Generated Code Detection

As AI coding assistants continue to advance, detection technologies must evolve in parallel. At AiCodePlag.com, we're continuously improving our code AI detector thr

  • Collaborative research with academic institutions studying AI code patterns
  • Feedback loops from our user community to identify new detection challenges
  • Integration with emerging industry standards for AI attribution

Try Our Free AI Code Detector Today

Don't let AI-generated code compromise your projects. Our free AI code detector provides instant analysis with detailed reports.

Check out our comprehensive guide to AI detection in academia for more insights.

Frequently Asked Questions (FAQ)

Yes, AI Code Plag offers a free AI code detector with basic detection features across multiple programming languages.

AI Code Detectors can indeed be wrong, as they are provide high-probability assessments but are not infallible. These tools rely on algorithms and training data, which may have inherent biases or limitations

Educators, developers, researchers, and companies can all benefit from a Code AI Detector. Educators use it to ensure student originality, professionals maintain project integrity, and businesses leverage it for compliance and security across large codebases.

Most advanced tools support multiple languages, but coverage varies by platform.

Accuracy depends on the algorithm and dataset used.

Yes, but they are more effective with modern AI-generated code patterns.

Yes, advanced AI code detectors analyze syntax, structure, and common patterns found in AI-generated code.

While effective, these tools are not 100% accurate. They work best when combined with manual review.

Modify your code to introduce more human-like variations or provide context to the reviewer.

Yes, they are widely used in academia, development, and cybersecurity.

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