CVE-2020-11023
XSS in Oracle Rest Data Services 11.2.0.4 … 19c
Raw vector
CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:C/C:H/I:L/A:NSummary
CVE-2020-11023 is a medium-severity Cross-site Scripting (CWE-79) vulnerability in Oracle Rest Data Services. Its CVSS base score is 6.9 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked in the top 0.3% of CVEs by exploit likelihood; CISA has added it to the Known Exploited Vulnerabilities catalog; a public proof-of-concept is referenced.
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-2020-11023 is a cross-site scripting vulnerability affecting jQuery versions from 1.0.3 up to but not including 3.5.0. It occurs when HTML containing <option> elements from untrusted sources is passed to DOM manipulation methods such as .html() or .append(), even if the input has been sanitized beforehand, allowing execution of untrusted code. The issue is tracked under CWE-79 and carries a CVSS 3.1 score of 6.9.
An attacker can supply crafted HTML containing <option> tags to an application that uses an affected jQuery version and feeds that input into the vulnerable DOM methods. Successful exploitation can result in execution of arbitrary script in the context of the affected page, potentially leading to theft of sensitive data or other actions within the victim's browser session.
The jQuery project released version 3.5.0 to address the flaw. Multiple openSUSE security advisories reference the update and recommend applying the patched jQuery release to resolve the exposure.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2020-0387
Vulnerability Data
In jQuery versions greater than or equal to 1.0.3 and before 3.5.0, passing HTML containing <option> elements from untrusted sources - even after sanitizing it - to one of jQuery's DOM manipulation methods (i.e. .html(), .append(), and others) may execute…
more
untrusted code. This problem is patched in jQuery 3.5.0.
- CWE(s)
- KEV Date Added
- 23 January 2025
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.1.2V1.3.2
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.
Penetration testing submits XSS payloads to web applications, detecting cross-site scripting flaws for subsequent remediation.
Validates web inputs to reject script-related content that could produce XSS.
Output validation against expected content can reject or sanitize script content in generated web pages, reducing XSS exploitability.
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 target introduction of XSS via coding standards/testing (mostly), yet the single broad outcome leaves many specific neutralization vectors unaddressed (partial).
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-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.
Requiring language-specific secure-coding standards and automated scanning during the SDLC catches missing output encoding or improper neutralization of untrusted data before the software reaches production.
Secure-coding standards, SAST scans and removal of insecure code samples together eliminate the failure to neutralize script content that produces cross-site scripting flaws.
Webpage malware scanning and block-listing of known malicious sites reduce the likelihood that reflected or stored script payloads reach a user’s browser.