Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:LCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2023-45128 is a critical-severity Improper Input Validation (CWE-20) vulnerability in Gofiber Fiber. Its CVSS base score is 10.0 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Data Obfuscation (T1001); ranked at the 23th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-2708
Vulnerability Data
Fiber is an express inspired web framework written in Go. A Cross-Site Request Forgery (CSRF) vulnerability has been identified in the application, which allows an attacker to inject arbitrary values and forge malicious requests on behalf of a user. This…
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vulnerability can allow an attacker to inject arbitrary values without any authentication, or perform various malicious actions on behalf of an authenticated user, potentially compromising the security and integrity of the application. The vulnerability is caused by improper validation and enforcement of CSRF tokens within the application. This issue has been addressed in version 2.50.0 and users are advised to upgrade. Users should take additional security measures like captchas or Two-Factor Authentication (2FA) and set Session cookies with SameSite=Lax or SameSite=Secure, and the Secure and HttpOnly attributes as defense in depth measures. There are no known workarounds for this vulnerability.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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- 1 hardening rule · 1 OS baseline
V3.3.2V3.5.1V10.2.1
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Security testing and developer training directly verify and enforce proper input validation, reducing exploitability of injection and malformed-data weaknesses.
Awareness training educates users on avoiding untrusted links and actions that can be exploited via CSRF.
Requiring user re-entry of credentials for sensitive actions prevents automated forgery of requests without active user participation.
Prevents reliance on untrusted matching results for security-relevant decisions by enforcing verification and contest procedures.
Security testing and evaluation at multiple SDLC stages directly detects missing or flawed input validation, with the required remediation process ensuring fixes are applied.
Providing authoritative attributes with the data reduces the need for security decisions to rely on untrusted external inputs.
Directly implements checks on information inputs to reject invalid data before processing.
Detects anomalous request patterns consistent with cross-site request forgery.
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.
Proper management of identities/credentials reduces the chance that security decisions will be driven by untrusted inputs.
Strong authentication mechanisms reduce reliance on unvalidated cookies for identity and access decisions.
Cookies commonly carry identity assertions; requiring their protection, conveyance, and verification directly eliminates the weakness.
Enforcing access policy and least privilege limits damage from cookie misuse but does not address cookie validation itself.
Integrity protections for data-at-rest can apply to cookie stores but do not cover validation during use.
Cryptographic integrity for data-in-transit directly mitigates tampering of cookies sent over the network.
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.
Hardening callouts derived
DISA STIG baselines are authored against specific weaknesses. Where this CVE cites a broad weakness class, the mapping is not asserted at that abstraction (owner ruling, 2026-09-25: grade only at Base and below), so no rule is shown here rather than a rule shown against the wrong grain.
- No fine-grained STIG row for CWE-20, a class-level weakness, and none of its children carries one either.