Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:HCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2026-77524 is a critical-severity Improper Privilege Management (CWE-269) vulnerability. Its CVSS base score is 9.9 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique LSASS Memory (T1003.001); ranked at the 49th 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 AC-4 (Information Flow Enforcement) and SC-7 (Boundary Protection) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-101431
Vulnerability Data
KEDA is a Kubernetes-based Event Driven Autoscaling component. In version 2.20.2 and earlier, a namespace administrator who can create TriggerAuthentication and ScaledObject resources can set hashiCorpVault.address to a tenant-controlled endpoint and select Kubernetes authentication without an explicit credential. KEDA then…
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uses the operator pod's projected ServiceAccount token and sends it to that endpoint as a Vault login credential. The JWT-shape filter from the prior CVE-2025-68476 remediation accepts the operator token because its subject is a Kubernetes ServiceAccount, so the attacker can obtain the operator's cluster-wide permissions, including broad Secret reads and workload or admission-related operations. This vulnerability is fixed in 2.21.0.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.3.6V1.5.3V5.3.2V10.4.7
Mitigating Controls (NIST 800-53 r5) AI
Information flow enforcement can restrict which destinations the server is allowed to contact on behalf of users.
Boundary protection limits the network reach of server-initiated requests even if SSRF occurs.
Input validation directly stops untrusted URLs from being accepted and fetched without destination checks.
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.
Runtime monitoring of web applications and services can detect anomalous outbound requests indicative of SSRF.
Vulnerability identification processes can discover and record SSRF flaws in web applications.
Network segmentation and egress controls can limit the damage from successful SSRF requests.
Secure development practices directly include input validation and destination allow-listing that prevent SSRF.
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.
A.5.15 directly mandates determining access requirements, defining/enforcing topic-specific access control policy, assigning rights/restrictions by entity/role, consistency with classification, need-to-know, privileged access restrictions, segregation, formal authorization, and dynamic rules — which stops most improper privilege management from being exploitable; bounded remainder is flawed implementation of those rules (e.g. incorrect mapping or enforcement bugs).
A.5.18 directly governs the provisioning, review, modification and timely revocation of access rights (including for role changes, termination and privilege levels), which stops most improper privilege spheres from being exploitable even if the assignment flaw exists; the bounded remainder is flaws in the underlying enforcement mechanism itself (e.g. AC-3/A.8.3)
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.