CVE-2026-42047
Published: 07 May 2026
Description
Inngest is a platform for running event-driven and scheduled background functions with queueing, retries, and step orchestration. Versions 3.22.0 through 3.53.1 contain a vulnerability that allows unauthenticated remote attackers to exfiltrate environment variables from the host process via the serve()…
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HTTP handler. The serve() handler implements GET, POST, and PUT methods. Requests using PATCH, OPTIONS, or DELETE fall through to a generic handler that returns diagnostic information. A change introduced in v3.22.0 caused this diagnostic response to include the contents of process.env, exposing any secrets, API keys, or credentials present in the environment. An application is vulnerable if its serve() endpoint is reachable via PATCH, OPTIONS, or DELETE requests, which is common in setups like Next.js Pages Router or Express's app.use(...). Not affected are Next.js App Router handlers that export only GET, POST, and PUT, and applications using the connect worker method. This issue has been fixed in version 3.54.0. To work around this issue if upgrading is not immediately possible, restrict the serve() endpoint at the framework or reverse-proxy layer to accept only GET, POST, and PUT. The Inngest serve() endpoint does not require any other HTTP methods.
Likely Mitigating ControlsAI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Review and removal of nonpublic information from publicly accessible systems directly prevents exposure of sensitive data to unauthorized actors.
Data mining protection mechanisms detect and block unauthorized bulk extraction of sensitive data, directly mitigating exposure to unauthorized actors.
Documenting information locations and authorized users enables better protection against unauthorized exposure of sensitive data.
Shielding or other emanation protections directly prevent sensitive information from reaching unauthorized actors via electromagnetic signals.
Minimizing PII in testing/training/research directly reduces the volume of sensitive data present in environments where it could be exposed to unauthorized actors.
Categorization identifies sensitive data so that confidentiality protections commensurate with impact level are selected and documented.
Concealment techniques directly prevent real sensitive data from being exposed to adversaries.
Restricts error message visibility to authorized recipients, directly reducing unauthorized exposure of sensitive information.
Security SummaryAI
Automated synthesis unavailable for this CVE.
Details
- CWE(s)