Whether an AI code detector stores your code depends on the service and its current privacy terms.
Before uploading a snippet, check how the provider handles submitted content, account data, and deletion—and remember that an AI authorship score is not proof of who wrote the code.
What does it mean for a detector to store your code?
“Store” can refer to several different things.
A service may temporarily process code to produce a result, keep it in application logs, retain it in an account’s scan history, or preserve it longer for troubleshooting or product improvement.
These practices are not interchangeable, and a provider may treat each type of data differently.
There is no universal retention rule for AI code detectors.
Policies vary by provider, account type, and settings, and terms can change.
A detector’s results page may not explain data handling in detail, so read the privacy policy and terms of service that apply when you submit code.
What privacy details should you check?
Look for clear answers to these questions before pasting source code into a third-party website:
- What content is collected? Check whether the policy covers submitted code, prompts, filenames, scan results, or other metadata.
- How long is it retained? Look for separate retention periods for submitted content, logs, and saved scan history.
- Why is it used? Determine whether content is processed only to return a result or may also be used for analytics, service improvement, or model training.
- Who can access it? Check for disclosures about employees, contractors, subprocessors, and other service providers.
- Can you delete it? Find out whether deletion is available, what it covers, and whether copies in backups or logs follow a different schedule.
- Where is it handled? If location matters to you or your organization, review any information about storage regions and international transfers.
Do not assume that a “free” scan is anonymous or that account deletion immediately removes every copy.
Likewise, a statement that a service does not train on submissions does not by itself explain logging, retention, or access by service providers.
Does an AI detector need to keep code to analyze it?
Not necessarily.
A detector can process submitted text and return a result without offering a lasting scan history.
However, the technical process alone does not establish what the provider actually retains.
Only the service’s current disclosures or a direct response from the provider can clarify its practices.
Be cautious with broad claims such as “your code is never stored” unless they appear in terms that apply to your use of the service and define what “stored” means.
For confidential or regulated work, ask the provider specific questions and follow your organization’s approved tools and data-handling rules.
How can you reduce the risk before submitting code?
If you decide to use an online detector, minimize what you share.
Submit only the smallest relevant excerpt, remove secrets and identifying details, and avoid uploading an entire repository when a short sample will do.
- Remove API keys, passwords, tokens, private URLs, and connection strings.
- Replace real names, customer data, internal paths, and proprietary identifiers with placeholders.
- Do not include unrelated files, comments, documentation, or configuration data.
- Check whether the code belongs to an employer, client, school, or open-source project with specific submission rules.
- Use an approved local or organization-managed option if you are not permitted to send the code to an external service.
Redaction can lower exposure, but it does not make a submission risk-free.
Code may remain identifiable through its structure, unusual logic, comments, or surrounding context.
Does code privacy depend on the kind of detector?
AI authorship classification and code similarity checking are different tasks.
An AI detector estimates whether code resembles patterns associated with generated output.
A similarity or plagiarism tool compares code with other material, such as public repositories or submitted work.
Their data needs and comparison sources can differ, so check the privacy terms for the specific tool and feature you plan to use.
Do not infer that a writing detector’s policy or capability applies to a source-code feature.
Turnitin says its AI writing model does not reliably detect code.
Its AI writing report should not be confused with source-code similarity tools, which address a separate question.
Codespy is a relevant external source-code detector.
If considering it or another provider, consult its current privacy policy and terms directly; a product’s relevance to code detection does not establish how it retains or uses submissions.
This article does not report firsthand testing or endorse a particular service.
Can a detector’s score prove who wrote the code?
No.
An AI authorship score is an estimate, not a record of the code’s origin.
A result cannot establish by itself whether a person used an AI assistant, copied code, or wrote a particular passage.
False positives and false negatives are possible, and results should be interpreted alongside other evidence and context.
Code similarity is also not the same as proof of misconduct.
Similar code may arise from common patterns, shared libraries, templates, coursework requirements, or independently written solutions.
Any decision about authorship or policy compliance should account for the tool’s limits and the relevant context.
Policies vary among schools, employers, clients, and platforms.
What should you do if the policy is unclear?
If you cannot determine whether a provider retains submissions, treat the code as potentially disclosed to that service.
Ask the provider whether code is logged, for how long, whether it is used for training or service improvement, and how deletion works.
For sensitive code, do not submit it until you have an answer that satisfies the applicable rules.
Keep a copy of the privacy terms or settings that apply at the time of use if you need to document your review.
Recheck them before future uploads, since providers may update their practices.