Protect proprietary code, embedded secrets, and credentials in AI tools.
Engineers paste code into AI tools every day to debug, refactor, or get a second pair of eyes, whether you're a solo developer or part of a large engineering org. LogosGuard swaps internal package names, hostnames, and identifiers for placeholders before the prompt is submitted, while embedded secrets and credentials are hard-blocked entirely. The AI still helps with the underlying engineering question. Your IP and your secrets stay inside your LogosGuard deployment.
Engineers will paste code into AI tools, that's part of how modern software gets built. The question is whether your proprietary code, internal architecture, and live credentials ride along with it.
Why this is structurally different from PII or PHI.
Source code is sensitive in a different way than PII or PHI. The risk is not one identifier; it is the cumulative exposure of how your systems are built. A single 50-line snippet looks innocent. The same engineer pasting 50 different snippets over six months can teach an external system more about your codebase than your competitors will ever learn through legitimate means.
There is also the embedded-secret problem. A pasted code snippet often contains a database URL, an API key, or a hardcoded token that was supposed to be in a config file. Those secrets are nominally rotatable, but they are also often forgotten, and they live in chat history far longer than the engineer remembers.
Common risk patterns.
- An engineer pastes a stack trace into Claude that includes a real database connection string.
- A backend developer pastes a 200-line function with an internal package name and authentication details.
- A new hire pastes a config file into ChatGPT to ask 'is this set up correctly?'.
- A devops engineer pastes a Terraform module that names internal AWS account roles.
- A frontend developer pastes a component with hardcoded test credentials still in place.
- An SRE pastes a log line with a basic-auth header that was supposed to be redacted weeks ago.
What LogosGuard detects in code.
LogosGuard treats code as a first-class data type. It detects structured secrets, API keys, OAuth tokens, private keys, database connection strings, cloud credentials, passwords, using format-aware patterns. It also detects markers that suggest proprietary or internal code: known internal package prefixes, internal hostname patterns, ARNs, and other signals that the code is from your organization rather than open-source. Admins can extend detection with allow- and deny-lists for repository-specific patterns.
Credential types LogosGuard catches out of the box.
- API keys (provider-prefixed: AWS, GCP, Azure, GitHub, Stripe, OpenAI, and others).
- OAuth access tokens and refresh tokens.
- Private keys (RSA, ECDSA, SSH).
- Database connection strings, including credentials in URLs.
- Cloud credentials (AWS access keys, GCP service account JSON, Azure secrets).
- Passwords and basic-auth headers.
- Webhook secrets and signing keys.
- Generic high-entropy strings that look like opaque secrets.
How LogosGuard handles code and credentials.
- 1
Detect
Scan the pasted block or uploaded file for embedded secrets, structured credentials, and proprietary code markers.
- 2
Coach
Show the engineer exactly which lines triggered the policy. Most engineers want to do the right thing once they see what is in the prompt.
- 3
Redact or block
Embedded secrets and credentials are a hard block. Proprietary code patterns trigger redact-or-warn, depending on team policy.
- 4
Log + flag for rotation
Record the event with policy decision and metadata. Treat credential detections as near-misses; your team should rotate the credential, even when blocked.
Recommended policy actions.
Most engineering organizations are comfortable with a layered approach. Embedded secrets and credentials are a hard block: there is no legitimate workflow that benefits from a real API key in an AI prompt. Proprietary code patterns are auto-redacted: internal package names like `acme.internal.auth.tokens` become `[INTERNAL_PACKAGE]`, internal hostnames like `vault-prod-1.acme.io` become `[INTERNAL_HOST]`, and the AI gets a generic shape it can still help with. General code without secrets and without internal markers passes through with a logged event. This keeps AI useful for engineering work while keeping IP and credentials out of the prompt.