CVE-2025-51534
XSS in Craws Openatlas ≤ 8.12.0
Raw vector
CVSS:3.1/AV:N/AC:L/PR:H/UI:R/S:C/C:H/I:H/A:NSummary
CVE-2025-51534 is a high-severity Cross-site Scripting (CWE-79) vulnerability in Craws Openatlas. Its CVSS base score is 8.1 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked at the 32th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
This vulnerability is AI-related — categorised as Other Platforms; in the Other ATLAS/OWASP Terms risk domain.
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-2025-51534 is a cross-site scripting (XSS) vulnerability in OpenAtlas version 8.11.0, a software product from the Austrian Archaeological Institute (ÖAI). The issue, classified under CWE-79, enables attackers to inject a crafted payload into the Name field, resulting in the execution of arbitrary web scripts or HTML. It carries a CVSS v3.1 base score of 8.1 (AV:N/AC:L/PR:H/UI:R/S:C/C:H/I:H/A:N), indicating high severity due to network accessibility, low complexity, and impacts on confidentiality and integrity with a changed scope.
The vulnerability can be exploited by attackers who possess high privileges (PR:H), such as authenticated users with elevated access in the OpenAtlas system. By injecting a malicious payload into the Name field, the attacker creates a stored XSS condition. This payload executes when another user with required privileges interacts with the affected content, such as viewing a delete button, requiring user interaction (UI:R) to trigger in the victim's browser context. Successful exploitation can compromise confidentiality and integrity at a high level, potentially allowing data theft or manipulation across scoped boundaries.
Advisories referenced in the CVE, primarily from sec4you-pentest.com, detail the stored nested XSS in the delete button context, as described at https://www.sec4you-pentest.com/schwachstelle/openatlas-stored-nested-xss-delete-button/ and related pages. These sources provide technical vulnerability information but do not specify patches or mitigations in the available CVE data.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-23512
Vulnerability Data
A cross-site scripting (XSS) vulnerability in Austrian Archaeological Institute (AI) OpenAtlas v8.11.0 allows attackers to execute arbitrary web scripts or HTML via injecting a crafted payload into the Name field.
- CWE(s)
AI Security AnalysisAI
- AI Category
- Other Platforms
- Risk Domain
- Other ATLAS/OWASP Terms
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: ai
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
—
—
—
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.