Raw vector
CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:HSummary
CVE-2023-2317 is a high-severity Cross-site Scripting (CWE-79) vulnerability in Typora Typora. Its CVSS base score is 8.6 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked in the top 19% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV 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-2023-2317 is a DOM-based cross-site scripting vulnerability in the updater/update.html component of Typora versions prior to 1.6.7 on Windows and Linux. The flaw permits a crafted Markdown file to execute arbitrary JavaScript within the context of the Typora main window by loading the typora://app/typemark/updater/update.html resource through an <embed> tag.
An attacker can exploit the issue when a user either opens a malicious Markdown file directly in Typora or copies and pastes content originating from a malicious webpage. Successful exploitation grants the attacker the ability to run code with high impact on confidentiality, integrity, and availability, consistent with the reported CVSS 8.6 score.
Public references indicate that Typora resolved the vulnerability in release 1.6.7, as documented in the vendor's "What's New" notes, while the Star Labs advisory provides technical details on the root cause and reproduction steps. The associated EPSS score has remained flat at 0.4928 with no material increase observed after disclosure.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-33821
Vulnerability Data
DOM-based XSS in updater/update.html in Typora before 1.6.7 on Windows and Linux allows a crafted markdown file to run arbitrary JavaScript code in the context of Typora main window via loading typora://app/typemark/updater/update.html in <embed> tag. This vulnerability can be exploited…
more
if a user opens a malicious markdown file in Typora, or copies text from a malicious webpage and paste it into Typora.
- CWE(s)
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.