Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:NSummary
CVE-2025-60378 is a high-severity Cross-site Scripting (CWE-79) vulnerability in Fairsketch Rise Ultimate Project Manager. Its CVSS base score is 8.1 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked in the top 40% of CVEs by exploit likelihood; 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-2025-60378 is a stored HTML injection vulnerability (CWE-79) in RISE Ultimate Project Manager & CRM. Published on 2025-10-10, it allows authenticated users to inject arbitrary HTML into invoices and messages. The injected content renders in emails, PDFs, and messaging/chat modules distributed to clients or team members. The vulnerability carries a CVSS v3.1 base score of 8.1 (AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N), indicating high severity due to its potential for confidentially and integrity impacts.
Attackers require only low-privileged authenticated access to exploit this remotely with low complexity and no user interaction. They can inject malicious HTML that executes when rendered for recipients, enabling phishing, credential theft, and business email compromise. Automated recurring invoices and messaging features exacerbate the threat by repeatedly distributing the payload to multiple recipients.
Mitigation guidance and additional details are available in vendor resources at http://rise.com and the GitHub repository https://github.com/ajansha/CVE-2025-60378.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-33722
Vulnerability Data
Stored HTML injection in RISE Ultimate Project Manager & CRM allows authenticated users to inject arbitrary HTML into invoices and messages. Injected content renders in emails, PDFs, and messaging/chat modules sent to clients or team members, enabling phishing, credential theft,…
more
and business email compromise. Automated recurring invoices and messaging amplify the risk by distributing malicious content to multiple recipients.
- 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.