Echo v4's opt-in Decompress middleware exposed a gzip-decoded request stream without limiting its expanded size. A small compressed request could therefore produce a very large decoded body. Handlers that read or bind that body could consume excessive memory or CPU, and repeated or concurrent requests could cause denial of service.
The middleware is not enabled by default. A limit on the compressed request size alone does not bound the decompressed size. Applications that already apply an effective body limit after decompression have reduced exposure.
Echo v4 versions through v4.16.0 are affected. Upgrade to v4.16.1.
The patch adds DecompressConfig.MaxDecompressedSize, defaulting to 100 MiB when zero. A value of -1 explicitly disables the limit. Reading beyond the cap returns ErrStatusRequestEntityTooLarge (HTTP 413), including through JSON and XML binding. Bodies exactly at the configured limit remain valid. Streaming enforcement requires callers to handle body-read errors.
Disable gzip request decompression on exposed routes, or place BodyLimit after Decompress so the application limit applies to decoded bytes. Apply suitable request deadlines and concurrency limits as well.
Reported by @q490107865. The exact-limit behavior incorporates @Shubham-Padkonde's work in #3136.
| Software | Affected versions |
|---|---|
github.com/labstack/echo/v4
|
>= 4.0.0, < 4.16.1 |
A vulnerability database tells you what is broken. Attack surface management tells you where it is running: it discovers your internet-facing assets and flags the ones affected by issues like this one.
What is attack surface management? →A security vulnerability is a weakness in software, hardware, or configuration that can be exploited to compromise confidentiality, integrity, or availability. Many vulnerabilities are tracked as CVEs (Common Vulnerabilities and Exposures), which provide a standardized identifier so teams can coordinate patching, mitigation, and risk assessment across tools and vendors.
CVSS (Common Vulnerability Scoring System) estimates technical severity, but it doesn't automatically equal business risk. Prioritize using context like internet exposure, affected asset criticality, known exploitation (proof-of-concept or in-the-wild), and whether compensating controls exist. A "Medium" CVSS on an exposed, production system can be more urgent than a "Critical" on an isolated, non-production host.
A vulnerability is the underlying weakness. An exploit is the method or code used to take advantage of it. A zero-day is a vulnerability that is unknown to the vendor or has no publicly available fix when attackers begin using it. In practice, risk increases sharply when exploitation becomes reliable or widespread.
Recurring findings usually come from incomplete Asset Discovery, inconsistent patch management, inherited images, and configuration drift. In modern environments, you also need to watch the software supply chain: dependencies, containers, build pipelines, and third-party services can reintroduce the same weakness even after you patch a single host. Unknown or unmanaged assets (often called Shadow IT) are a common reason the same issues resurface.
Use a simple, repeatable triage model: focus first on externally exposed assets, high-value systems (identity, VPN, email, production), vulnerabilities with known exploits, and issues that enable remote code execution or privilege escalation. Then enforce patch SLAs and track progress using consistent metrics so remediation is steady, not reactive.
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