CVE-2024-21281
Oracle Banking Liquidity Management 14.7.0.6.0
Raw vector
CVSS:3.1/AV:N/AC:H/PR:H/UI:R/S:U/C:L/I:H/A:LCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2024-21281 is a medium-severity HTTP Request/Response Smuggling (CWE-444) vulnerability in Oracle Banking Liquidity Management. Its CVSS base score is 5.3 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique LSASS Memory (T1003.001); ranked at the 23th 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 SC-7 (Boundary Protection) and SI-10 (Information Input Validation) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-18994
Vulnerability Data
Vulnerability in the Oracle Banking Liquidity Management product of Oracle Financial Services Applications (component: Infrastructure). The supported version that is affected is 14.7.0.6.0. Difficult to exploit vulnerability allows high privileged attacker with network access via HTTP to compromise Oracle Banking…
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Liquidity Management. Successful attacks require human interaction from a person other than the attacker. Successful attacks of this vulnerability can result in unauthorized creation, deletion or modification access to critical data or all Oracle Banking Liquidity Management accessible data as well as unauthorized read access to a subset of Oracle Banking Liquidity Management accessible data and unauthorized ability to cause a partial denial of service (partial DOS) of Oracle Banking Liquidity Management. CVSS 3.1 Base Score 5.3 (Confidentiality, Integrity and Availability impacts). CVSS Vector: (CVSS:3.1/AV:N/AC:H/PR:H/UI:R/S:U/C:L/I:H/A:L).
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V4.1.3V4.2.4V1.5.3V4.1.1
Mitigating Controls (NIST 800-53 r5) AI
Boundary protection at external interfaces can enforce consistent HTTP request/response parsing rules between intermediaries and endpoints.
Validating HTTP inputs at the intermediary prevents malformed messages from being interpreted inconsistently downstream.
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.
Network monitoring can detect smuggling attempts via anomalous HTTP traffic or logs, while eliminating the inconsistency directly aids detection of such events.
Network protections can enforce consistent HTTP proxy/firewall behavior to block smuggling, and removing the weakness helps prevent unauthorized access via request smuggling.
Configuration management can enforce uniform HTTP parsing rules across intermediaries, directly mitigating inconsistent interpretation.
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.