Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:NSummary
CVE-2025-14483 is a medium-severity Insertion of Sensitive Information Into Sent Data (CWE-201) vulnerability in Ibm Sterling B2B Integrator. Its CVSS base score is 4.3 (Medium).
Operationally, ranked at the 15th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to AC-4 (Information Flow Enforcement) and SI-15 (Information Output Filtering) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-208662
Vulnerability Data
IBM Sterling B2B Integrator and IBM Sterling File Gateway 6.1.0.0 through 6.1.2.7_2, 6.2.0.0 through 6.2.0.5_1, 6.2.1.0 through 6.2.1.1_1, and 6.2.2.0 could disclose sensitive host information to authenticated users in responses that could be used in further attacks against the system.
- CWE(s)
Related Threats
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
Mitigating Controls (NIST 800-53 r5) AI
Directly enforces policy on what sensitive host data may be included in application responses sent to authenticated users.
Filters outbound responses to remove or mask sensitive host information before it reaches users.
Monitors application outputs specifically for unintended disclosure of sensitive host data.
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.
Secure SDLC practices directly prevent insertion of sensitive data into application outputs and messages.
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.
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.
Data-masking techniques can prevent sensitive values from appearing in transmitted payloads.
Classification identifies sensitive data so it is not inadvertently transmitted.
Labelling makes sensitive data visible to developers and prevents accidental inclusion in outbound messages.
Information-transfer rules directly govern what data may be sent to external parties.
PII-protection requirements reduce the chance of sending personal data to unauthorized recipients.
DLP controls inspect and block outbound flows that contain sensitive information.