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CVE-2026-42945 – NGINX Heap Buffer Overflow via Malicious HTTP Requests in ngx_http_rewrite_module

NGINX Plus and NGINX Open Source contain a heap buffer overflow vulnerability in the ngx_http_rewrite_module module. The flaw is triggered when a rewrite directive is followed by a rewrite, if, or set directive combined with an unnamed PCRE capture group (e.g., $1, $2) and a replacement string containing a question mark (?). An unauthenticated remote attacker can exploit this condition by sending crafted HTTP requests, causing the NGINX worker process to crash; on systems with ASLR disabled, arbitrary code execution is possible.

Patched versions: NGINX Open Source 1.31.0 (or 1.30.1 on the 1.30.x branch); NGINX Plus R37, R36 P4, or R32 P6.

Why there are no Confirmed Findings: A reliable exploitability test for this vulnerability would crash the target’s NGINX worker process, which is disruptive to production traffic. For this reason IONIX does not actively probe for this issue and cannot surface Confirmed Findings.

Recommended action: NGINX servers do not always expose their version in HTTP response headers, so the absence of a version banner does not mean a host is safe. Customers should inventory every NGINX instance (internet-facing and internal), check the installed version directly on the host, and upgrade any version below the patched releases listed above. Configurations using rewrite directives with unnamed PCRE capture groups and ? in the replacement string should be treated as highest priority.

References

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How IONIX’s External Exposure Management Platform Detects and Validates
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1

Map your entire attack surface (continously)

IONIX uses multi-factor discovery methods, including DNS analysis, certificate mapping, metadata inspection, and more, to automatically map every internet-facing asset across your environment. This includes cloud instances, third-party platforms, shadow IT, and even forgotten infrastructure that traditional tools miss.

2

Monitor for new CVEs

Dozens of threat intel feeds using agentic technology are continuously analyzed to detect the appearance of proof-of-concept code, exploit kits, and indicators of active targeting. IONIX goes further by applying AI to proactively evaluate whether emerging vulnerabilities are likely to be exploited, even before PoCs go public.

3

Identify Potential External Exposures

Not all CVEs matter. IONIX filters vulnerabilities by asking attacker-centric questions: Can it be reached from the internet? Does it require authentication? Is it being exploited in the wild? This dramatically reduces noise and focuses teams on threats that can actually be weaponized.

4

Create Safe, Scalable Exploit Validations

IONIX transforms real-world PoCs into safe, non-intrusive test payloads that can be run in production environments without disruption. These simulations are precisely targeted to the systems that are vulnerable, ensuring rapid validation without unnecessary load.

5

Execute Exploit Validations

By combining context about software stack, versioning, exposure status, and reachability, IONIX ensures that only the right payloads are executed against the right assets, maximizing efficiency and minimizing risk.

6

Drive Fast and Actionable Remediation

Results are routed through integrations with ticketing, SOAR, and SIEM tools. Issues are written in plain language, bundled into remediation clusters, and prioritized based on asset criticality, exploitability, and blast radius. This shortens mean time to remediation (MTTR) and empowers teams to act with confidence.

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