Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:NSummary
CVE-2024-47880 is a high-severity Cross-site Scripting (CWE-79) vulnerability in Openrefine Openrefine. Its CVSS base score is 8.1 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked at the 28th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
The strongest mitigations our analysis identified map to AC-4 (Information Flow Enforcement) and IA-3 (Device Identification and Authentication) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-2977
Vulnerability Data
OpenRefine is a free, open source tool for working with messy data. Prior to version 3.8.3, the `export-rows` command can be used in such a way that it reflects part of the request verbatim, with a Content-Type header also taken…
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from the request. An attacker could lead a user to a malicious page that submits a form POST that contains embedded JavaScript code. This code would then be included in the response, along with an attacker-controlled `Content-Type` header, and so potentially executed in the victim's browser as if it was part of OpenRefine. The attacker-provided code can do anything the user can do, including deleting projects, retrieving database passwords, or executing arbitrary Jython or Closure expressions, if those extensions are also present. The attacker must know a valid project ID of a project that contains at least one row. Version 3.8.3 fixes the issue.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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- 7 hardening rules · 4 OS baselines
V1.1.2V1.3.2
Mitigating Controls (NIST 800-53 r5) AI
Provenance tracking supplies the information needed to distinguish and prefer more-trusted sources, reducing the chance that a weaker source is chosen.
Information flow enforcement can require that data or decisions are taken only from explicitly approved, higher-trust sources rather than less-verified ones.
Device identification and authentication forces verification of the source before any data it supplies is used, eliminating reliance on unauthenticated inputs.
Developer testing and evaluation can discover missing or incorrect input neutralization through targeted web-application tests.
Input validation directly enforces neutralization of untrusted data before it reaches web output generation.
Output filtering can catch or sanitize unneutralized script content before it is served to users.
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.
Explicit authenticity/integrity checks before use directly reduce selection of a less-trusted source.
Secure SDLC practices directly target introduction of XSS via coding standards/testing (mostly), yet the single broad outcome leaves many specific neutralization vectors unaddressed (partial).
Correlating multiple sources can surface discrepancies that discourage reliance on the less-trusted one.
Protecting data-in-transit integrity helps ensure the more-trusted source is the one whose data is accepted.
Patching and EOL replacement can remediate known XSS instances in libraries or frameworks (partial) but do nothing to enforce input neutralization in application code (none).
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.
Secure architecture principles include trusted input channels and source verification mechanisms.
Secure-coding testing and automated code-analysis tools are applied to detect improper neutralization of script-related content during web-page generation.
Knowledge exchange on emerging attack techniques and patches reduces the likelihood that cross-site scripting flaws remain unaddressed in deployed applications.
Operational indicators of compromise for web-application attacks can be incorporated into WAF or input-filtering rules, lowering the likelihood that unsanitized data reaches the browser.
Network security controls can enforce trusted data paths and source validation, reducing reliance on unverified inputs.
Secure network services include source validation and integrity checks that help prevent acceptance of data from less-trusted origins.
Hardening callouts derived
Configuration rules from DISA STIG baselines that bear on weaknesses of the type cited by this CVE. Each rule is shown with the relationship its mapping actually records, against the CWE it was authored against. Derived via CVE→CWE over `controls_xwalks` (authoritative rows only; rows rated `none` are excluded).
Oracle Linux 8 (1 rule)
- V-248575 OL 8 must prevent the installation of software, patches, service packs, device drivers, or operating system components of local packages without verification they have been digitally signed using a certificate that is issued by a Certificate Authority (CA) that is recognized and approved by the organization. prevents CWE-348
Oracle Linux 9 (1 rule)
- V-271525 OL 9 must have GPG signature verification enabled for all software repositories. prevents CWE-348
RHEL 7 (1 rule)
- V-204447 The Red Hat Enterprise Linux operating system must prevent the installation of software, patches, service packs, device drivers, or operating system components from a repository without verification they have been digitally signed using a certificate that is issued by a Certificate Authority (CA) that is recognized and approved by the organization. prevents CWE-348