Raw vector
CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:C/C:H/I:L/A:NCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2023-28117 is a high-severity Insertion of Sensitive Information Into Sent Data (CWE-201) vulnerability in Sentry Sentry Software Development Kit. Its CVSS base score is 7.6 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Protocol or Service Impersonation (T1001.003); ranked at the 50th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-0828
Vulnerability Data
Sentry SDK is the official Python SDK for Sentry, real-time crash reporting software. When using the Django integration of versions prior to 1.14.0 of the Sentry SDK in a specific configuration it is possible to leak sensitive cookies values, including…
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the session cookie to Sentry. These sensitive cookies could then be used by someone with access to your Sentry issues to impersonate or escalate their privileges within your application. In order for these sensitive values to be leaked, the Sentry SDK configuration must have `sendDefaultPII` set to `True`; one must use a custom name for either `SESSION_COOKIE_NAME` or `CSRF_COOKIE_NAME` in one's Django settings; and one must not be configured in one's organization or project settings to use Sentry's data scrubbing features to account for the custom cookie names. As of version 1.14.0, the Django integration of the `sentry-sdk` will detect the custom cookie names based on one's Django settings and will remove the values from the payload before sending the data to Sentry. As a workaround, use the SDK's filtering mechanism to remove the cookies from the payload that is sent to Sentry. For error events, this can be done with the `before_send` callback method and for performance related events (transactions) one can use the `before_send_transaction` callback method. Those who want to handle filtering of these values on the server-side can also use Sentry's advanced data scrubbing feature to account for the custom cookie names. Look for the `$http.cookies`, `$http.headers`, `$request.cookies`, or `$request.headers` fields to target with a scrubbing rule.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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- 1 hardening rule · 1 OS baseline
V14.2.3V16.5.1
Likely Mitigating Controls AI
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.
Detects error messages that leak sensitive information as evidence of disclosure.
The control directly mitigates generation of error messages containing sensitive authentication details by requiring obscured feedback instead of verbose responses.
Misdirection allows generation of misleading error messages that withhold or falsify sensitive details.
Explicitly requires error messages to avoid including sensitive or exploitable details while still supporting corrective action.
Validation ensures error messages contain only expected, non-sensitive content and blocks leakage via verbose errors.
Fail-safe procedures can be defined to suppress or sanitize error output, reducing generation of messages that contain sensitive information.
Embedding taints allows detection when sensitive data is inserted into outbound or sent data streams.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Monitoring runtime data flows and outputs can detect sensitive data being transmitted.
Protecting data-in-transit can include filtering or encrypting to avoid exposing sensitive content.
Protecting data-in-use includes removing confidential values before they are processed or sent.
Secure SDLC practices directly prevent insertion of sensitive data into application outputs and messages.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Classification identifies sensitive data so it is not inadvertently transmitted.
Labelling makes sensitive data visible to developers and prevents accidental inclusion in outbound messages.