GHSA-pmv8-rq9r-6j72 CVE-2026-67312
Axios: Deep formToJSON Key Recursion Can Cause Denial of Service
- Severity
- 0.0 / 10
- High · CVSS 4.0
- Exploit chance (EPSS)
- 0.52%
- Chance of exploitation in the next 30 days. Higher than 44.27% of scored vulnerabilities.
- Known exploited
- No
- Not in CISA's catalog
- Weakness
- CWE-400 Uncontrolled Resource Consumption
- CWE-770 Allocation of Resources Without Limits or Throttling
- Fix
0.33.0- Upgrade axios to this version or later
Description
Summary
Axios versions starting with 0.28.0 contain uncontrolled recursion in formDataToJSON, which is exposed as axios.formToJSON() and used internally when axios serialises FormData with Content-Type: application/json.
If an application passes attacker-controlled FormData field names to this functionality, a field name with thousands of nested bracket segments can exhaust the JavaScript call stack and cause denial of service for that request or, in applications without appropriate error handling, process termination.
Impact
Applications are affected only when untrusted users can control FormData key names that are converted through axios.
Affected paths include direct use of axios.formToJSON() on untrusted FormData and axios requests in which attacker-controlled FormData is sent with Content-Type: application/json.
The observed failure is RangeError: Maximum call stack size exceeded. In local testing, this error is catchable, so process-wide crash depends on the consuming application's error handling and runtime behaviour.
Affected Functionality
Affected functionality:
axios.formToJSON(formData)- Named ESM export
formToJSON - Default
transformRequestbehaviour forFormDatawhenContent-Typecontainsapplication/json
Unaffected functionality:
- Normal multipart
FormDatasubmission without JSON serialisation toFormData, which already enforces amaxDepthguard- Axios versions
<=0.27.2, whereformDataToJSONwas not present
Technical Details
The vulnerable code is in lib/helpers/formDataToJSON.js.
parsePropPath() splits a field name such as a[x][x][x] into path segments. buildPath() then recursively processes one segment per call without enforcing a maximum depth:
const result = buildPath(path, value, target[name], index);
A key with thousands of bracket-delimited segments causes thousands of recursive calls and can exceed the JavaScript engine's call stack limit.
Relevant source locations:
lib/helpers/formDataToJSON.jscontains the unbounded recursivebuildPath().lib/axios.jsexposes the helper asaxios.formToJSON.index.jsexposesformToJSONas a named export.index.d.tsandindex.d.ctsdeclare the public API.lib/defaults/index.jscallsformDataToJSON(data)when JSON-serializingFormData.
The inverse helper, toFormData, already enforces maxDepth and throws AxiosError with ERR_FORM_DATA_DEPTH_EXCEEDED, but formDataToJSON does not have an equivalent guard.
Proof of Concept of Attack
import axios from 'axios';
const fd = new FormData();
fd.append('a' + '[x]'.repeat(15000), 'value');
try {
axios.formToJSON(fd);
console.log('not vulnerable');
} catch (e) {
console.log(`${e.constructor.name}: ${e.message}`);
}
Expected result on affected versions:
RangeError: Maximum call stack size exceeded
The same condition can be reached via an axios request transformation when attacker-controlled FormData is sent with Content-Type: application/json.
Workarounds
Applications can reject or normalise untrusted form field names before calling axios.formToJSON().
Applications can avoid sending untrusted FormData through axios as JSON unless JSON conversion is required.
Applications should catch errors around formToJSON() or axios requests that transform untrusted FormData.
<details> <summary>Original Source</summary>
Summary
An uncontrolled recursion vulnerability in formDataToJSON allows any user who controls FormData input to crash a Node.js process with a single request. The function recurses once per bracket-delimited segment in a FormData key name with no depth limit, so a key like a[x][x][x]... with 15,000+ segments exhausts the call stack. This is a denial-of-service that kills the process via an unrecoverable RangeError. The inverse function toFormData already enforces a maxDepth limit (default 100) for exactly this reason — formDataToJSON lacks the equivalent guard.
Details
Vulnerable function: buildPath in lib/helpers/formDataToJSON.js, lines 50–82.
buildPath(path, value, target, index) is called recursively — once per segment in the parsed property path — with no depth check:
// lib/helpers/formDataToJSON.js, lines 50–82
function buildPath(path, value, target, index) {
let name = path[index++]; // advance one level
if (name === '__proto__') return true;
// ...
if (!isLast) {
// ...
const result = buildPath(path, value, target[name], index); // recurse — NO depth guard
// ...
}
}
The key is first split into segments by parsePropPath (line 17), which extracts every [segment] via regex. A key with 15,000 bracket pairs produces a 15,001-element array, causing 15,001 recursive calls — well beyond the V8 default stack limit (~10,000–15,000 frames).
formDataToJSON is a public API consumed two ways:
-
Directly by consumers — exported as
axios.formToJSON()(lib/axios.js:80), with TypeScript declarations in bothindex.d.ts:699andindex.d.cts:708, and documented in the API reference in four languages (docs/pages/advanced/api-reference.md). -
Internally by
transformRequest— called atlib/defaults/index.js:56when the request body isFormDataandContent-Typecontainsapplication/json:return hasJSONContentType ? JSON.stringify(formDataToJSON(data)) : data;
Contrast with toFormData: The inverse function (lib/helpers/toFormData.js:118) enforces maxDepth (default 100) and throws AxiosError with code ERR_FORM_DATA_DEPTH_EXCEEDED when exceeded. formDataToJSON has no equivalent protection.
PoC
Requires only Node.js and an unmodified axios v1.x install:
import formDataToJSON from 'axios/lib/helpers/formDataToJSON.js';
// Build a FormData with a single key containing 15,000 nested bracket segments
const fd = new FormData();
const key = "a" + "[x]".repeat(15000);
fd.append(key, "value");
try {
formDataToJSON(fd);
console.log("Not vulnerable");
} catch (e) {
console.log(e.constructor.name + ": " + e.message);
// RangeError: Maximum call stack size exceeded
}
Verified output on Node.js 22.22.3 against axios v1.16.1 (current v1.x HEAD):
RangeError: Maximum call stack size exceeded
The process crashes. In a server context (e.g., Express middleware calling axios.formToJSON() on an uploaded form), a single crafted request terminates the process.
Impact
Denial of Service (process crash). Any unauthenticated user who can submit FormData to a Node.js application that passes it through axios.formToJSON() — or that sends it as a JSON-serialized FormData body via axios — can crash the server process with a single request. The RangeError from stack exhaustion is unrecoverable in many contexts (it cannot be reliably caught when the stack is already full). No authentication or special privileges are required; the attacker only needs to control a FormData key name.
</details>
Affected versions
npm
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.
axios npm → 0.33.0
- npm
npm install axios@0.33.0- yarn
yarn add axios@0.33.0- pnpm
pnpm add axios@0.33.0
Severity breakdown
CVSS 4.0 0.0
CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N
- Attack vector
- Network
- Attack complexity
- Low
- Attack requirements
- Present
- Privileges required
- None
- User interaction
- None
- Confidentiality (vulnerable system)
- None
- Integrity (vulnerable system)
- None
- Availability (vulnerable system)
- Low
- Confidentiality (subsequent systems)
- None
- Integrity (subsequent systems)
- None
- Availability (subsequent systems)
- None
CVSS 3.1 7.5
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
- Attack vector
- Network
- Attack complexity
- Low
- Privileges required
- None
- User interaction
- None
- Scope
- Unchanged
- Confidentiality
- None
- Integrity
- None
- Availability
- High
Weakness
CWE-400: Uncontrolled Resource Consumption
The product does not properly control the allocation and maintenance of a limited resource.
How to prevent it
- Architecture and Design: Design throttling mechanisms into the system architecture. The best protection is to limit the amount of resources that an unauthorized user can cause to be expended. A strong authentication and access control model will help prevent such attacks from occurring in the first place. The login application should be protected against DoS attacks as much as possible. Limiting the database access, perhaps by caching result sets, can help minimize the resources expended. To further limit the potential for a DoS attack, consider tracking the rate of requests received from users and blocking requests that exceed a defined rate threshold.
- Architecture and Design: Mitigation of resource exhaustion attacks requires that the target system either: recognizes the attack and denies that user further access for a given amount of time, or uniformly throttles all requests in order to make it more difficult to consume resources more quickly than they can again be freed. The first of these solutions is an issue in itself though, since it may allow attackers to prevent the use of the system by a particular valid user. If the attacker impersonates the valid user, they may be able to prevent the user from accessing the server in question. The second solution is simply difficult to effectively institute -- and even when properly done, it does not provide a full solution. It simply makes the attack require more resources on the part of the attacker.
- Architecture and Design: Ensure that protocols have specific limits of scale placed on them.
- Implementation: Ensure that all failures in resource allocation place the system into a safe posture.
CWE-770: Allocation of Resources Without Limits or Throttling
The product allocates a reusable resource or group of resources on behalf of an actor without imposing any intended restrictions on the size or number of resources that can be allocated.
How to prevent it
- Requirements: Clearly specify the minimum and maximum expectations for capabilities, and dictate which behaviors are acceptable when resource allocation reaches limits.
- Architecture and Design: Limit the amount of resources that are accessible to unprivileged users. Set per-user limits for resources. Allow the system administrator to define these limits. Be careful to avoid CWE-410.
- Architecture and Design: Design throttling mechanisms into the system architecture. The best protection is to limit the amount of resources that an unauthorized user can cause to be expended. A strong authentication and access control model will help prevent such attacks from occurring in the first place, and it will help the administrator to identify who is committing the abuse. The login application should be protected against DoS attacks as much as possible. Limiting the database access, perhaps by caching result sets, can help minimize the resources expended. To further limit the potential for a DoS attack, consider tracking the rate of requests received from users and blocking requests that exceed a defined rate threshold.
- 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.
- Architecture and Design: For any security checks that are performed on the client side, ensure that these checks are duplicated on the server side, in order to avoid CWE-602. Attackers can bypass the client-side checks by modifying values after the checks have been performed, or by changing the client to remove the client-side checks entirely. Then, these modified values would be submitted to the server.
- Architecture and Design: Mitigation of resource exhaustion attacks requires that the target system either: recognizes the attack and denies that user further access for a given amount of time, typically by using increasing time delays uniformly throttles all requests in order to make it more difficult to consume resources more quickly than they can again be freed. The first of these solutions is an issue in itself though, since it may allow attackers to prevent the use of the system by a particular valid user. If the attacker impersonates the valid user, they may be able to prevent the user from accessing the server in question. The second solution can be difficult to effectively institute -- and even when properly done, it does not provide a full solution. It simply requires more resources on the part of the attacker.
- Architecture and Design: Ensure that protocols have specific limits of scale placed on them.
- Architecture and Design, Implementation: If the program must fail, ensure that it fails gracefully (fails closed). There may be a temptation to simply let the program fail poorly in cases such as low memory conditions, but an attacker may be able to assert control before the software has fully exited. Alternately, an uncontrolled failure could cause cascading problems with other downstream components; for example, the program could send a signal to a downstream process so the process immediately knows that a problem has occurred and has a better chance of recovery. Ensure that all failures in resource allocation place the system into a safe posture.
- Operation, Architecture and Design: Use quotas or other resource-limiting settings provided by the operating system or environment. For example, when managing system resources in POSIX, setrlimit() can be used to set limits for certain types of resources, and getrlimit() can determine how many resources are available. However, these functions are not available on all operating systems. When the current levels get close to the maximum that is defined for the application (see CWE-770), then limit the allocation of further resources to privileged users; alternately, begin releasing resources for less-privileged users. While this mitigation may protect the system from attack, it will not necessarily stop attackers from adversely impacting other users. Ensure that the application performs the appropriate error checks and error handling in case resources become unavailable (CWE-703).
References
Advisories
Packages
Other links
- github.com/axios/axios/security/advisories/GHSA-pmv8-rq9r-6j72
- github.com/axios/axios/pull/11000
- github.com/axios/axios/pull/11001
- github.com/axios/axios/commit/1417285c69344bbcc6420a021f67dee0c6fedb2d
- github.com/axios/axios/commit/32fc489632377d214db55bfa4e2c48486a7d7ce2
- github.com/axios/axios/releases/tag/v0.33.0
- github.com/axios/axios/releases/tag/v1.18.0
- vulncheck.com/advisories/axios-before-denial-of-service-via-formtojson
Timeline
- Published
- Last updated by the source
- Latest EPSS score
Related advisories
| Advisory | Severity | Why it's related |
|---|---|---|
| GHSA-44g4-m2mj-wpvx Axios: CIDR-form NO_PROXY entries are ignored, causing proxy exclusion bypass for internal IP ranges | Medium | Also affects axios |
| GHSA-x97p-jq2g-jp4f Axios: Prototype Pollution Gadget in axios toFormData Options | High | Also affects axios |
| GHSA-vh66-26gq-q6x8 Axios: Prototype pollution gadget in fetch adapter can alter outbound requests | Medium | Also affects axios |
| GHSA-r4gj-5m52-g5wh Axios: maxRedirects: 0 is not enforced by the fetch adapter, allowing redirect-based SSRF | High | Also affects axios |
| GHSA-mghh-pgcx-3jjj Axios: ReDoS (O(N²)) in shouldBypassProxy host normalization, reachable via untrusted redirect Location | High | Also affects axios |
| GHSA-m8m8-qj5v-23w3 Axios: Node HTTP adapter prototype-pollution gadget allows request socket hijack via inherited createConnection | High | Also affects axios |
| GHSA-j8rh-479h-cp32 Axios: Header Injection via Inherited headers After Minimal Interceptor | Medium | Also affects axios |
| GHSA-c29m-xwm3-cm6r Axios: ReDoS in fromDataURI data: URL parser freezes the Node event loop (DoS) | High | Also affects axios |
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