Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:U/C:H/I:H/A:NSummary
CVE-2026-29082 is a high-severity Cross-site Scripting (CWE-79) vulnerability in Kestra Kestra. Its CVSS base score is 7.3 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked at the 14th 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 SA-11 (Developer Testing and Evaluation) and SI-10 (Information Input Validation) — 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-2026-29082 is a cross-site scripting (XSS) vulnerability (CWE-79) in Kestra, an event-driven orchestration platform. It affects versions 1.1.10 and prior, where the execution-file preview feature renders user-supplied Markdown (.md) files using markdown-it with the html:true option. The resulting HTML is then injected via Vue's v-html directive without any sanitization, enabling arbitrary script execution in the context of the preview page. The vulnerability carries a CVSS v3.1 base score of 7.3 (AV:N/AC:L/PR:L/UI:R/S:U/C:H/I:H/A:N).
An authenticated user with low privileges (PR:L) can exploit this vulnerability over the network (AV:N) by uploading a malicious .md file containing HTML/JavaScript payloads. Exploitation requires low attacker complexity (AC:L) and user interaction (UI:R), such as tricking a victim into previewing the file through Kestra's execution-file preview interface. Successful exploitation allows the attacker to achieve high-impact confidentiality and integrity violations (C:H/I:H), such as stealing session cookies, keystrokes, or other sensitive data from the victim's browser, or modifying the page content, with no availability impact (A:N) and no change in scope (S:U).
The GitHub security advisory (GHSA-r36c-83hm-pc8j) and release notes for v1.0.30 provide further details, though at the time of publication on 2026-03-06, no publicly available patches were reported. Security practitioners should monitor the Kestra repository for updates and consider disabling or restricting file preview functionality until mitigation is confirmed.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-10046
Vulnerability Data
Kestra is an event-driven orchestration platform. In versions from 1.1.10 and prior, Kestra’s execution-file preview renders user-supplied Markdown (.md) with markdown-it instantiated as html:true and injects the resulting HTML with Vue’s v-html without sanitisation. At time of publication, there are…
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no publicly available patches.
- 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
Mitigating Controls (NIST 800-53 r5) AI
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.
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.