GHSA-8j8c-7jfh-h6hx
Code Injection in js-yaml
High
npm
- Severity
- High
- The publisher's own rating, not a CVSS score
- Exploit chance (EPSS)
- —
- No score published
- Known exploited
- No
- Not in CISA's catalog
- Weakness
- CWE-94 Improper Control of Generation of Code ('Code Injection')
- Fix
3.13.1- Upgrade js-yaml to this version or later
Description
Versions of js-yaml prior to 3.13.1 are vulnerable to Code Injection. The load() function may execute arbitrary code injected through a malicious YAML file. Objects that have toString as key, JavaScript code as value and are used as explicit mapping keys allow attackers to execute the supplied code through the load() function. The safeLoad() function is unaffected.
An example payload is
{ toString: !<tag:yaml.org,2002:js/function> 'function (){return Date.now()}' } : 1
which returns the object
{
"1553107949161": 1
}
Recommendation
Upgrade to version 3.13.1.
Affected versions
npm
| Package | Vulnerable | Fixed in |
|---|---|---|
| js-yaml | < 3.13.1 |
3.13.1 |
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.
js-yaml npm → 3.13.1
- npm
npm install js-yaml@3.13.1- yarn
yarn add js-yaml@3.13.1- pnpm
pnpm add js-yaml@3.13.1
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
Other links
Timeline
- Published
- Last updated by the source
Related advisories
| Advisory | Severity | Why it's related |
|---|---|---|
| GHSA-r3ph-w7gj-g6xm js-yaml: maxTotalMergeKeys does not limit CPU use for empty merge sources | Medium | Also affects js-yaml |
| GHSA-2883-xcg3-v3hh js-yaml: maxTotalMergeKeys does not limit CPU use for empty merge sources | High | Also affects js-yaml |
| GHSA-5p4m-2wfm-xmqj JS-YAML: Quadratic CPU consumption in !!omap resolution (3.x and 4.x) — CVE-2026-59870 fix not backported | High | Also affects js-yaml |
| GHSA-pm4m-ph32-ghv5 js-yaml: Exponential parsing time in flow collections leads to denial of service | High | Also affects js-yaml |
| GHSA-724g-mxrg-4qvm js-yaml: Quadratic-complexity (O(n^2)) DoS via !!omap tag in YAML11_SCHEMA | High | Also affects js-yaml |
| GHSA-52cp-r559-cp3m js-yaml: YAML merge-key chains can force quadratic CPU consumption | High | Also affects js-yaml |
| GHSA-g796-fgmg-93mv js-yaml: YAML merge-key chains can force quadratic CPU consumption in js-yaml | High | Also affects js-yaml |
| GHSA-h67p-54hq-rp68 JS-YAML: Quadratic-complexity DoS in merge key handling via repeated aliases | Medium | Also affects js-yaml |
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