Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:U/C:L/I:L/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-2025-24459 is a medium-severity Cross-site Scripting (CWE-79) vulnerability in Jetbrains Teamcity. Its CVSS base score is 4.6 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked in the top 14% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
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-2025-24459 is a reflected cross-site scripting (XSS) vulnerability, classified under CWE-79, affecting JetBrains TeamCity versions prior to 2024.12.1. The flaw exists on the Vault Connection page, where untrusted input is reflected without proper sanitization, enabling script injection. It carries a CVSS v3.1 base score of 4.6 (AV:N/AC:L/PR:L/UI:R/S:U/C:L/I:L/A:N), indicating moderate severity with network accessibility but requiring low privileges and user interaction.
Exploitation requires an authenticated attacker with low privileges (PR:L) to craft a malicious link or payload targeting the Vault Connection page. A victim user must interact by clicking the link or performing an action that triggers the reflection (UI:R), allowing the attacker's script to execute in the victim's browser context over the network (AV:N) with low complexity (AC:L). This results in low impacts on confidentiality and integrity (C:L/I:L), such as potential access to limited sensitive data or minor modifications within the session, with no availability impact (A:N).
JetBrains has mitigated this vulnerability in TeamCity 2024.12.1, as documented in their issues fixed advisory at https://www.jetbrains.com/privacy-security/issues-fixed/. Security practitioners should prioritize upgrading affected instances to this version or later to prevent exploitation.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-3721
Vulnerability Data
In JetBrains TeamCity before 2024.12.1 reflected XSS was possible on the Vault Connection page
- 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.