Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:NSummary
CVE-2026-15747 is a critical-severity Observable Response Discrepancy (CWE-204) vulnerability. Its CVSS base score is 9.1 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Account Discovery (T1087); ranked at the 17th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to IA-6 (Authentication Feedback) and SI-11 (Error Handling) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-44067
Vulnerability Data
Mojolicious versions from 4.59 before 9.48 for Perl expose a stable representation of the session CSRF token to a BREACH compression oracle. _csrf_token generates and caches one token per session and returns the same value on every call, and _csrf_field…
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places that value in a hidden `csrf_token` input. When a response carrying the token also echoes attacker-controlled input and is gzip-compressed, the chosen values and the resulting compressed lengths form a BREACH oracle. An attacker able to query it can recover the token and pass csrf_protect validation.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V13.4.5V3.3.2V3.5.1V10.2.1
Mitigating Controls (NIST 800-53 r5) AI
Obscuring authentication feedback directly stops one common source of observable response discrepancies.
Error handling explicitly requires messages that avoid revealing exploitable internal information.
Access enforcement requires verifying that state-changing requests originate from the authenticated user rather than a forged cross-site source.
Information flow enforcement can block responses that would otherwise disclose internal state to unauthorized parties.
Protecting session authenticity prevents attackers from replaying or forging authenticated requests via the victim's browser.
Boundary protection monitors and filters outbound responses that could leak internal state.
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 prevent introduction of inconsistent response behavior that leaks internal state.
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.
Security testing can detect observable response discrepancies before deployment.
Network security controls can enforce uniform responses and suppress observable discrepancies.
By denying access to phishing or malicious sites, the control lowers the likelihood that a user will be tricked into submitting a forged request that performs an unintended action on another site.
Secure SDLC practices include error-handling and response standardization to avoid information disclosure.
Application security requirements typically mandate consistent, non-revealing error messages.
Secure architecture principles discourage designs that leak internal state via differing responses.