CVE-2026-13763
Amazon Application Load Balancer
Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:N/SC:H/SI:H/SA:H/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:XCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2026-13763 is a high-severity HTTP Request/Response Smuggling (CWE-444) vulnerability in Amazon Application Load Balancer. Its CVSS base score is 7.9 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 49% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to SC-7 (Boundary Protection) and SI-10 (Information Input Validation) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-40221
Vulnerability Data
Inconsistent interpretation of HTTP/2 requests in AWS Application Load Balancer with AWS WAF enabled might allow remote actors to bypass AWS WAF managed rule body inspection via crafted HTTP/2 requests that fragment the request body across frames so that only…
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a partial body is inspected. This issue only impacts HTTP/2 ALB target groups. To remediate this issue, customers should enable the "Inspect after sufficient data" target group configuration associated to an ALB load balancer. Refer to: ( https://docs.aws.amazon.com/elasticloadbalancing/latest/application/edit-target-group-attributes.html#waf-http2-inspection )
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V4.1.3V4.2.4V1.5.3V4.1.1
Mitigating Controls (NIST 800-53 r5) AI
Boundary protection at external interfaces can enforce consistent HTTP request/response parsing rules between intermediaries and endpoints.
Validating HTTP inputs at the intermediary prevents malformed messages from being interpreted inconsistently downstream.
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.
Network monitoring can detect smuggling attempts via anomalous HTTP traffic or logs, while eliminating the inconsistency directly aids detection of such events.
Network protections can enforce consistent HTTP proxy/firewall behavior to block smuggling, and removing the weakness helps prevent unauthorized access via request smuggling.
Configuration management can enforce uniform HTTP parsing rules across intermediaries, directly mitigating inconsistent interpretation.
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.
Network security controls can enforce consistent HTTP parsing and proxy behavior that mitigates request smuggling.
Secure network services include hardening proxies and gateways against inconsistent HTTP interpretation.
Secure SDLC practices require threat modeling and testing for HTTP parsing inconsistencies in intermediaries.
Application security requirements can mandate strict HTTP message validation and canonicalization.
Secure architecture principles include consistent protocol handling and defense-in-depth for proxies.
Secure coding standards can require strict HTTP header and request validation to prevent smuggling.