Skip to content

GHSA-pmv8-rq9r-6j72 CVE-2026-67312

Axios: Deep formToJSON Key Recursion Can Cause Denial of Service

High npm
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 transformRequest behaviour for FormData when Content-Type contains application/json

Unaffected functionality:

  • Normal multipart FormData submission without JSON serialisation
  • toFormData, which already enforces a maxDepth guard
  • Axios versions <=0.27.2, where formDataToJSON was 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.js contains the unbounded recursive buildPath().
  • lib/axios.js exposes the helper as axios.formToJSON.
  • index.js exposes formToJSON as a named export.
  • index.d.ts and index.d.cts declare the public API.
  • lib/defaults/index.js calls formDataToJSON(data) when JSON-serializing FormData.

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:

  1. Directly by consumers — exported as axios.formToJSON() (lib/axios.js:80), with TypeScript declarations in both index.d.ts:699 and index.d.cts:708, and documented in the API reference in four languages (docs/pages/advanced/api-reference.md).

  2. Internally by transformRequest — called at lib/defaults/index.js:56 when the request body is FormData and Content-Type contains application/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

PackageVulnerableFixed in
axios
>= 0.28.0, < 0.33.0
0.33.0
axios
>= 1.0.0, < 1.18.0
1.18.0

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

Timeline

  1. Published
  2. Last updated by the source
  3. Latest EPSS score
AdvisorySeverityWhy 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
Is this in your code?

MergeHarbor checks every repository's dependencies against this database, ranks what matters by exploitability and reachability, routes it to the owning team and opens the fix pull request.

Check your repos with MergeHarbor