When Infostealer Logs Contain Tokens Instead of Passwords

A password-only import rule can make a security feed look clean while discarding the finding that deserves attention. If your pipeline rejects every record without a password, it is making a decision about exposure before it knows what kind of authentication material was stolen.

That matters for AI coding tools. In research published on October 30, 2026, SpyCloud examined recovered WardenStealer and Aoki logs containing AI-tool credentials and configuration data. Its researchers reported OAuth access and refresh tokens, API keys and session material. They also found ordinary configuration and instruction files alongside authentication data. The report describes collected evidence; it does not establish that every recovered token remains usable today.

For developers consuming infostealer logs, the engineering question is specific: can a token finding reach an analyst without first pretending to be a username-and-password pair?

A token finding through a password-only pipeline

Consider a constructed example. An authorized source-file review identifies an OAuth refresh token in an AI coding tool’s credentials file. Internal asset records link the device to a developer workstation called Build-17. No browser password accompanies this finding, and nobody has checked whether the token is still accepted.

The intake service summarizes it like this:

Device: Build-17
Material identified: OAuth refresh token
Password: not supplied
Evidence: restricted source-file reference
Current validity: unknown

A rule equivalent to “if password is empty, discard” ends the investigation at intake. The analyst receives nothing. A dashboard can still report successful processing because the service fetched and examined the item without encountering an error.

The repair is to separate the password-login route from the exposure intake. A token finding enters a token-review route, with its evidence reference and device association. Password-login records continue through their own checks. An unclassified file goes to review rather than acquiring a token label from its filename.

The result for Build-17 should be an investigation item saying: “OAuth refresh token identified in source material; password not supplied; current validity unknown.” That tells the reviewer what was observed and which question remains open.

What your API filter actually excludes

Webz.io’s Data Breaches API documents a has_password filter. Setting has_password=true selects records containing a password. That is useful for a task specifically concerned with exposed passwords. It is a poor default for an investigation intended to cover other authentication material.

The query is only one place to inspect. An application can fetch a broader result set and then lose the same records through a required database column, a transformation that assumes password_type is always populated, or a serializer that omits unfamiliar categories. Follow the finding from retrieval to the analyst’s screen.

Webz.io’s Data Breach Detection API supplies structured breach and infostealer data with account, device and source context. Its record documentation describes source-file information where a plan includes it. Use that context to support the investigation, and check what your integration is entitled to receive before designing around raw files or token-specific details.

In the Build-17 example, the token classification comes from the authorized source-file review. A record identifying the workstation does not automatically establish what every file on it contained. Preserve that link between the classification and its evidence.

An instruction file is a different finding

SpyCloud’s researchers also observed instruction and configuration files in the recovered material. That distinction affects the importer: a file associated with an AI tool is not necessarily an authentication secret.

For Build-17, imagine the review instead finds only an instruction file and no token value. The output should change to “AI-tool configuration exposed; authentication material not established.” Sending both findings through an identical “active token stolen” alert would create an unsupported claim.

Even a correctly identified refresh token needs a response appropriate to its issuer. OAuth’s token revocation standard defines revocation separately from password authentication. The investigation should identify the account owner and the provider’s supported revocation procedure; a completed password reset alone should not close that task.

Test the finding that used to disappear

Before changing production, replay the Build-17 example through the complete intake path using a dummy value. The expected result is one token-review item with its evidence reference, no fabricated password and no claim of current validity. Check the analyst-facing message as well as the stored record.

Then replay the configuration-only version. It should remain distinguishable from the token finding. A third run with unavailable source material should retain the unresolved classification, rather than inventing the missing contents.

These tests address a different question from the number of records fetched or saved. Success means the right finding reaches the right review path. If Build-17 disappears again after a schema or export change, the test should fail at that delivery boundary.