GHSA-87f9-hvmw-gh4p CVE-2026-41159

Mermaid: Improper sanitization of configuration leads to CSS injection

Medium npm

Severity: 5.3 / 10; Medium · CVSS 4.0
Exploit chance (EPSS): 0.49%; Chance of exploitation in the next 30 days. Higher than 41.90% of scored vulnerabilities.
Known exploited: No; Not in CISA's catalog
Weakness: CWE-94 Improper Control of Generation of Code ('Code Injection')
Fix: 11.15.0; Upgrade mermaid to this version or later

Description

Impact

Mermaid's default configuration allows injecting CSS that applies outside of the Mermaid diagram via the fontFamily, themeCSS, and altFontFamily configuration options.

Live demo: mermaid.live

Example code:

%%{init: {"fontFamily": "x;a{b} :not(&){background:green !important} c{d}"}}%%
flowchart LR
    A --> B

The injected CSS exploits stylis's & (scope reference) handling. :not(&) escapes the #mermaid-xxx automatic scoping, applying styles to all page elements. Global at-rules (@font-face, @keyframes, @counter-style) are also injectable as stylis hoists them to top level.

This allows page defacement and DOM attribute exfiltration via CSS :has() selectors.

Patches

Workarounds

If you can't upgrade mermaid, you can set the secure config value in the mermaid config to avoid allowing diagrams to modify fontFamily, themeCSS, altFontFamily, and themeVariables.

Setting "securityLevel": "sandbox" will also prevent this.

Credits

Reported by @zsxsoft on behalf of @KeenSecurityLab

Affected versions

npm

Package	Vulnerable	Fixed in
mermaid	`>= 11.0.0-alpha.1, <= 11.14.0`	No fix yet
mermaid	`<= 10.9.5`	No fix yet
mermaid	`>= 11.0.0-alpha.1, < 11.15.0`	`11.15.0`
mermaid	`< 10.9.6`	`10.9.6`

How to fix

Move to the fixed version or later with your package manager, update the lockfile, and run your tests. If the package only arrives through another dependency, upgrade that dependency first. If none of its releases pulls a fixed version yet, force the version with your package manager's override.

mermaid npm → `11.15.0`

npm

npm install mermaid@11.15.0

yarn

yarn add mermaid@11.15.0

pnpm

pnpm add mermaid@11.15.0

Severity breakdown

CVSS 4.0 5.3

CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:N/VI:L/VA:N/SC:L/SI:L/SA:L

Attack vector: Network
Attack complexity: Low
Attack requirements: None
Privileges required: None
User interaction: Passive
Confidentiality (vulnerable system): None
Integrity (vulnerable system): Low
Availability (vulnerable system): None
Confidentiality (subsequent systems): Low
Integrity (subsequent systems): Low
Availability (subsequent systems): Low

CVSS 3.1 5.3

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L

Attack vector: Network
Attack complexity: Low
Privileges required: None
User interaction: None
Scope: Unchanged
Confidentiality: None
Integrity: None
Availability: Low

Weakness

CWE-94: Improper Control of Generation of Code ('Code Injection')

The product constructs all or part of a code segment using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the syntax or behavior of the intended code segment.

How to prevent it

Architecture and Design: Refactor your program so that you do not have to dynamically generate code.
Architecture and Design: Run your code in a "jail" or similar sandbox environment that enforces strict boundaries between the process and the operating system. This may effectively restrict which code can be executed by your product. Examples include the Unix chroot jail and AppArmor. In general, managed code may provide some protection. This may not be a feasible solution, and it only limits the impact to the operating system; the rest of your application may still be subject to compromise. Be careful to avoid CWE-243 and other weaknesses related to jails.
Implementation: Assume all input is malicious. Use an "accept known good" input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does. When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, "boat" may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as "red" or "blue." Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code's environment changes. This can give attackers enough room to bypass the intended validation. However, denylists can be useful for detecting potential attacks or determining which inputs are so malformed that they should be rejected outright. To reduce the likelihood of code injection, use stringent allowlists that limit which constructs are allowed. If you are dynamically constructing code that invokes a function, then verifying that the input is alphanumeric might be insufficient. An attacker might still be able to reference a dangerous function that you did not intend to allow, such as system(), exec(), or exit().
Testing: Use dynamic tools and techniques that interact with the product using large test suites with many diverse inputs, such as fuzz testing (fuzzing), robustness testing, and fault injection. The product's operation may slow down, but it should not become unstable, crash, or generate incorrect results.
Operation: Run the code in an environment that performs automatic taint propagation and prevents any command execution that uses tainted variables, such as Perl's "-T" switch. This will force the program to perform validation steps that remove the taint, although you must be careful to correctly validate your inputs so that you do not accidentally mark dangerous inputs as untainted (see CWE-183 and CWE-184).
Operation: Run the code in an environment that performs automatic taint propagation and prevents any command execution that uses tainted variables, such as Perl's "-T" switch. This will force the program to perform validation steps that remove the taint, although you must be careful to correctly validate your inputs so that you do not accidentally mark dangerous inputs as untainted (see CWE-183 and CWE-184).
Implementation: For Python programs, it is frequently encouraged to use the ast.literal_eval() function instead of eval, since it is intentionally designed to avoid executing code. However, an adversary could still cause excessive memory or stack consumption via deeply nested structures [REF-1372], so the python documentation discourages use of ast.literal_eval() on untrusted data [REF-1373].

References

Advisories

Fixes and patches

Packages

github.com/mermaid-js/mermaid

Timeline

May 11, 2026 Published
Sep 10, 2026 Last updated by the source
Nov 1, 2026 Latest EPSS score

Advisory	Severity	Why it's related
GHSA-rhh3-jpg6-66xh Mermaid radar diagrams are vulnerable to DoS	Medium	Also affects mermaid
GHSA-c4c3-pg64-4m4v Mermaid configuration APIs allow prototype pollution	Low	Also affects mermaid
GHSA-6x64-9x62-f2gx Mermaid allows CSS injection applying to sibling elements of the diagram	Medium	Also affects mermaid
GHSA-3rrr-jr9j-h3q3 Mermaid Architecture diagrams are vulnerable to prototype pollution	Medium	Also affects mermaid
GHSA-2v8p-3f2j-5mp7 Mermaid XY Charts are vulnerable to an infinite loop DoS	Medium	Also affects mermaid
GHSA-6m6c-36f7-fhxh Mermaid Gantt Charts are vulnerable to an Infinite Loop DoS	Medium	Also affects mermaid
GHSA-ghcm-xqfw-q4vr Mermaid: Improper sanitization of `classDef` in state diagrams leads to HTML injection	Medium	Also affects mermaid
GHSA-xcj9-5m2h-648r Mermaid: Improper sanitization of `classDefs` in diagrams leads to CSS injection	Medium	Also affects mermaid

Credits: KeenSecurityLab, aloisklink, zsxsoft

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