A humble MOSS alternative that also catches
AI and web plagiarism.
Stanford MOSS is a great free tool, and we have a lot of respect for it. Codequiry is a small, modern MOSS alternative for the cases it was never built for: spotting AI-generated code, matching against the open web (GitHub, Stack Overflow), and comparing peer submissions, across 65+ languages with clean JSON results.
Three kinds of plagiarism, one quiet API
MOSS does peer-to-peer comparison really well. We built Codequiry for the gaps that opened up since 1994: AI-generated code, code copied from the open web, and getting all of it back as clean JSON.
AI-generated code detection
Students and candidates increasingly lean on ChatGPT, Claude, Copilot, and Gemini. Codequiry looks for the structural and stylistic fingerprints of machine-written code and flags submissions that read as AI-generated, so you can take a closer look. It is a signal to review, offered honestly, not a verdict.
Web & repository matching
Checks submissions against a large index of public code, including GitHub, Stack Overflow, LeetCode, tutorials, and forums, to catch copying that offline tools simply cannot see.
Peer-to-peer similarity
The classic MOSS-style check: compare every submission in a batch against the others to surface students or teammates who shared code.
Clean JSON REST API
Similarity scores, matched line ranges, and source URLs in structured JSON. Parse it in any language, store it anywhere, automate the rest.
Zeus™ Hyper engine
Semantic analysis reads what code does, not just how it looks, so renaming variables, reordering statements, or reformatting does not slip past it.
SDKs, webhooks & CI/CD friendly
SDKs for Node.js, Python, PHP, and Java, plus signed webhooks for async results. It fits comfortably alongside Canvas, Blackboard, Moodle, GitHub Actions, GitLab CI, and Jenkins, whether you are grading homework or reviewing pull requests.
What is source code plagiarism, and how does an API detect it?
Source code plagiarism occurs when programmers copy, modify, or disguise code from other sources without proper attribution. In academic settings, this includes students copying homework assignments, sharing solutions, or using code from GitHub, Stack Overflow, or online tutorials without permission.
Code plagiarism detection tools analyze source code to identify similarities between submissions. Unlike text plagiarism checkers, code plagiarism detectors must understand programming language syntax, variable naming, code structure, and algorithmic patterns to accurately identify copied code, even when it has been modified.
Common code obfuscation techniques include renaming variables and functions, reordering statements, adding dead code, changing formatting, and restructuring loops. Codequiry's Zeus™ Hyper engine aims to see through these changes by analyzing what the code does rather than just how it reads. And with so much code now written with AI assistants, detection increasingly means asking a second question too: was this written by a person, or generated by a model?
What is Stanford MOSS?
MOSS (Measure of Software Similarity) is a free code plagiarism detection system developed at Stanford University by Alex Aiken. Since 1994 it has been the trusted standard for spotting copying between programming assignments, and it is genuinely good at that job.
MOSS works by converting source code into fingerprints using a technique called "winnowing" and comparing them to find overlaps. It is excellent for peer-to-peer comparison. A few things sit outside what it was designed to do, and that is simply where a tool like Codequiry can help:
- No AI-generated code signal
- Compares peers only, no web matching
- Returns HTML pages, not a JSON API
- No SDKs or webhooks for automation
- Email-based submission workflow
When people reach for a MOSS alternative, and what we humbly add
MOSS pioneered fingerprint-based detection in 1994 and still does peer comparison beautifully. Codequiry is not here to replace that legacy, just to cover the newer ground: AI-generated code, the open web, and a modern JSON API.
Where MOSS shines
- Free and well-loved by educators
- Strong peer-to-peer comparison
- Proven winnowing fingerprints
- Trusted for 30+ years
- A sensible first stop for classrooms
What Codequiry adds
- AI-generated code detection
- Web matching (GitHub, Stack Overflow)
- Clean JSON API responses
- Zeus™ Hyper anti-obfuscation
- SDKs for Node, Python, PHP, Java
- 65+ programming languages
A good fit for
- Universities: CS courses, academic integrity
- Bootcamps: Checking homework at scale
- Contests: Hackathon & competition judging
- Hiring: Take-home and interview review
- Enterprise: IP protection & code audits
- CI/CD: Pull request checks
An honest side-by-side comparison
Each of these tools is good at something. Here is a fair look at what they cover so you can pick the right one, or use more than one together.
| Capability | Codequiry | Stanford MOSS | JPlag | DoloS |
|---|---|---|---|---|
| AI-Generated Code Detection | Yes | No | No | No |
| JSON API Responses | Yes | HTML only | Partial | Partial |
| Web & Repository Matching | Yes | Offline | Offline | Offline |
| Anti-Obfuscation Detection | Advanced | Basic | Basic | Basic |
| SDKs & Webhooks | Full | None | Limited | Limited |
| 65+ Language Support | Yes | Some | Some | Some |
| Hosted API & Free Trial | Yes | Self-serve | Self-host | Self-host |
Integrate code plagiarism detection in minutes
Four REST calls: create, upload, start, and get results. Authenticated with a single API key, results returned as structured JSON. No XML, no HTML scraping, no waiting on email.
const response = await fetch('https://codequiry.com/api/v1/check/create', { method: 'POST', headers: { 'Accept': 'application/json', 'apikey': process.env.CODEQUIRY_API_KEY }, body: JSON.stringify({ name: 'Assignment 1', language: 'python' }) }); const { check_id } = await response.json(); // Upload files, then start with web + AI detection on, // and read similarity, web matches, and AI flags as JSON.
Source code plagiarism detection for 65+ programming languages
From Python homework and Java capstones to Rust, Go, Swift, and Solidity, the Codequiry API understands them all, with automatic language detection for mixed-language projects.
Python
Java
JavaScript
C / C++
Rust
Go
Swift
Ruby
Also supported: TypeScript, Kotlin, Scala, PHP, C#, MATLAB, R, Perl, Haskell, OCaml, Erlang, Elixir, Lua, Dart, Julia, Fortran, COBOL, Assembly, SQL, Shell/Bash, PowerShell, and 30+ more.
Where teams quietly put Codequiry to work
From university CS departments to enterprise code audits, a few of the everyday places code, AI, and web plagiarism checking earns its keep.
Academic Integrity in CS Education
Computer Science professors use code plagiarism detection to identify copied programming assignments, shared homework solutions, and code from online sources. Codequiry integrates with LMS platforms like Canvas, Blackboard, and Moodle to automate the checking process.
Programming Contest Validation
Hackathons, coding competitions, and online judges use source code similarity detection to ensure submissions are original. Codequiry's web matching catches participants who copy solutions from GitHub, LeetCode, or previous contest archives.
Technical Interview Screening
Hiring platforms use code plagiarism APIs to review take-home tests and coding challenges. Spot candidates who copy from the web, share answers between rounds, or quietly paste in AI-generated solutions.
Enterprise IP Protection
Legal and security teams audit codebases to identify copied code, license violations, and potential IP theft. Codequiry helps enterprises protect proprietary algorithms and detect unauthorized code reuse in contractor deliverables.
Bootcamp & MOOC Assessment
Coding bootcamps and online learning platforms ensure students complete assignments independently. Automated plagiarism detection at scale, so you can check thousands of submissions per week without manual review.
CI/CD Pipeline Integration
DevOps teams add code similarity checks to pull request workflows. Automatically flag suspicious commits, detect accidental license violations, and ensure code originality before merging to main branches.
MOSS alternative, AI & code plagiarism API FAQ
What is a good Stanford MOSS alternative?
Codequiry is a modern, approachable MOSS alternative for code plagiarism detection. Where MOSS focuses on peer-to-peer comparison, Codequiry adds AI-generated code detection, web-scale matching, JSON API responses, anti-obfuscation via Zeus™ Hyper, and 65+ languages, with SDKs and webhooks for automation. Many teams use both.
Can Codequiry detect AI-generated code?
Yes. Codequiry looks for the structural and stylistic patterns common to code written by AI assistants like ChatGPT, Claude, Copilot, and Gemini, and flags submissions that read as AI-generated. We treat it as an honest signal worth reviewing, not a final verdict, so a human always makes the call.
How does source code plagiarism detection work?
Source code plagiarism detection works by tokenizing code into structural patterns, then comparing these patterns across submissions. Codequiry's Zeus™ Hyper uses 6-dimensional semantic analysis to understand code meaning, detecting plagiarism even when variables are renamed, code is reformatted, or statements are reordered.
Is this Stanford's MOSS service?
No. Codequiry is an independent alternative to Stanford MOSS, built from scratch with modern technology. While MOSS was pioneering in 1994, Codequiry offers significant improvements: JSON APIs, web matching, advanced anti-obfuscation, webhooks, and 65+ language support.
What programming languages are supported?
Codequiry supports 65+ programming languages including Python, Java, C/C++, JavaScript, TypeScript, Go, Rust, Swift, Kotlin, Ruby, PHP, C#, Scala, MATLAB, R, Haskell, and many more. Language auto-detection is included for mixed-language projects.
How accurate is code plagiarism detection?
No detector is perfect, and we would not claim otherwise. Codequiry's Zeus™ Hyper engine is built to catch common obfuscation like variable renaming, code reordering, dead code, and formatting changes, and it gives you clear similarity scores and matched ranges. The final judgment is always yours, the tool just helps you find what to look at.
Can I detect code copied from GitHub or Stack Overflow?
Yes. Unlike MOSS and other offline tools, Codequiry includes web-scale matching that searches billions of indexed sources including GitHub repositories, Stack Overflow answers, online tutorials, forum posts, and code hosting platforms.
How does Codequiry compare to JPlag and DoloS?
JPlag and DoloS are excellent open-source, self-hosted tools for peer comparison. Codequiry covers different ground: AI-generated code detection, web matching beyond the submitted set, JSON API responses, and webhooks for async workflows. They are all reasonable MOSS alternatives, and Codequiry leans toward hosted API integration.
What's the pricing for code plagiarism detection?
Codequiry plans start at $79/month. All plans include web scanning, JSON results, SDKs, and priority support. Enterprise plans add SSO, dedicated infrastructure, and custom SLAs. Cancel anytime.
Can I integrate with my LMS or CI/CD pipeline?
Absolutely. Codequiry provides a REST API with SDKs for Node.js, Python, PHP, and Java. Webhooks notify your systems when results are ready. Integrate with Canvas, Blackboard, Moodle, GitHub Actions, GitLab CI, Jenkins, or any custom workflow.
How fast is the plagiarism analysis?
Most checks finish in a couple of minutes, even with 100+ submissions, because work runs in parallel across our infrastructure. For larger batches you can use webhooks so your systems are notified the moment results are ready, no polling required.
MOSS alternatives in 2026: choosing the right code plagiarism detector
When looking at alternatives to Stanford MOSS, educators and developers usually weigh JPlag, DoloS, and Codequiry. Each has its own strengths for source code plagiarism detection, and the best choice depends on what you need to catch.
JPlag is an open-source tool from KIT focused on pair-wise comparison. DoloS uses AST analysis for structural comparison. Both are solid, self-hosted, offline tools without web matching or AI detection.
Codequiry takes an API-first approach and adds the newer pieces: AI-generated code detection, web-scale matching, JSON responses, and Zeus™ Hyper anti-obfuscation. If you need those, it is worth a look.
Quick Comparison
We still appreciate MOSS, but adding Codequiry's API let us catch things we'd been missing for years, students copying from GitHub gists and old Stack Overflow answers, and more recently work that was clearly AI-generated. The JSON response let us wire it into our LMS in an afternoon.
A humble MOSS alternative, ready when you need more.
If MOSS covers your needs, that is genuinely great. If you also want to catch AI-generated code and web copying, professors, bootcamps, hiring platforms, and engineering teams use Codequiry's API for exactly that. Get a key, send your first request, read the results as JSON.