CVE-2024-13255
Restful Web Services Project Restful Web Services 7.x-2.0 – 7.x-2.10
Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/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-2024-13255 is a high-severity Exposure of Sensitive Information Through Data Queries (CWE-202) vulnerability in Restful Web Services Project Restful Web Services. Its CVSS base score is 7.5 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Steganography (T1001.002); ranked at the 42th 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-23 (Data Mining Protection) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
CVE-2024-13255 is an Exposure of Sensitive Information Through Data Queries vulnerability in the Drupal RESTful Web Services module, enabling forceful browsing. This issue affects RESTful Web Services versions from 7.X-2.0 before 7.X-2.10. The vulnerability is classified under CWE-202 and has a CVSS v3.1 base score of 7.5 (AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N), indicating high confidentiality impact with no effect on integrity or availability.
Remote attackers require only network access and can exploit the vulnerability without privileges or user interaction due to its low attack complexity. Successful exploitation allows disclosure of sensitive information through crafted data queries targeting the RESTful endpoints.
The Drupal security advisory at https://www.drupal.org/sa-contrib-2024-019 details mitigation steps, with the issue resolved in RESTful Web Services version 7.X-2.10. Site administrators should update to this or later versions to address the vulnerability.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-51469
Vulnerability Data
Exposure of Sensitive Information Through Data Queries vulnerability in Drupal RESTful Web Services allows Forceful Browsing.This issue affects RESTful Web Services: from 7.X-2.0 before 7.X-2.10.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
AC-23 directly requires mechanisms to protect against unauthorized data mining and inference from statistical queries that would expose sensitive information.
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.
Behavior analytics on query activity can detect inference attempts but does not prevent exposure at query time.
Least-privilege query permissions directly limit the data an attacker can request or infer.
Protecting data-in-use reduces what remains available for inference via queries.
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 helps identify sensitive data that must be protected from inference attacks.
A.5.15 defines governance, policies, requirements and rules for access control (including need-to-know and classification consistency) but does not itself enforce, implement or act on those rules to stop statistical inference from data queries; per the owner's labeling rule, this is a dependency for other controls (e.g. actual access enforcement or DLP) rather than a prevention effect.
A.5.18 governs the provisioning, review, and revocation of authorized access rights; it has no bearing on whether an attacker can statistically infer confidential information from data queries, which is a disclosure weakness unrelated to access-right decisions.
Data masking prevents inference by obscuring sensitive values returned in query results.
DLP can detect and block queries or result sets that risk exposing sensitive information.
Logging query activity supports detection of inference attempts after the fact.