CVE-2025-7783
ADVISORY - githubSummary
Summary
form-data uses Math.random()
to select a boundary value for multipart form-encoded data. This can lead to a security issue if an attacker:
- can observe other values produced by Math.random in the target application, and
- can control one field of a request made using form-data
Because the values of Math.random() are pseudo-random and predictable (see: https://blog.securityevaluators.com/hacking-the-javascript-lottery-80cc437e3b7f), an attacker who can observe a few sequential values can determine the state of the PRNG and predict future values, includes those used to generate form-data's boundary value. The allows the attacker to craft a value that contains a boundary value, allowing them to inject additional parameters into the request.
This is largely the same vulnerability as was recently found in undici
by parrot409
-- I'm not affiliated with that researcher but want to give credit where credit is due! My PoC is largely based on their work.
Details
The culprit is this line here: https://github.com/form-data/form-data/blob/426ba9ac440f95d1998dac9a5cd8d738043b048f/lib/form_data.js#L347
An attacker who is able to predict the output of Math.random() can predict this boundary value, and craft a payload that contains the boundary value, followed by another, fully attacker-controlled field. This is roughly equivalent to any sort of improper escaping vulnerability, with the caveat that the attacker must find a way to observe other Math.random() values generated by the application to solve for the state of the PRNG. However, Math.random() is used in all sorts of places that might be visible to an attacker (including by form-data itself, if the attacker can arrange for the vulnerable application to make a request to an attacker-controlled server using form-data, such as a user-controlled webhook -- the attacker could observe the boundary values from those requests to observe the Math.random() outputs). A common example would be a x-request-id
header added by the server. These sorts of headers are often used for distributed tracing, to correlate errors across the frontend and backend. Math.random()
is a fine place to get these sorts of IDs (in fact, opentelemetry uses Math.random for this purpose)
PoC
PoC here: https://github.com/benweissmann/CVE-2025-7783-poc
Instructions are in that repo. It's based on the PoC from https://hackerone.com/reports/2913312 but simplified somewhat; the vulnerable application has a more direct side-channel from which to observe Math.random() values (a separate endpoint that happens to include a randomly-generated request ID).
Impact
For an application to be vulnerable, it must:
- Use
form-data
to send data including user-controlled data to some other system. The attacker must be able to do something malicious by adding extra parameters (that were not intended to be user-controlled) to this request. Depending on the target system's handling of repeated parameters, the attacker might be able to overwrite values in addition to appending values (some multipart form handlers deal with repeats by overwriting values instead of representing them as an array) - Reveal values of Math.random(). It's easiest if the attacker can observe multiple sequential values, but more complex math could recover the PRNG state to some degree of confidence with non-sequential values.
If an application is vulnerable, this allows an attacker to make arbitrary requests to internal systems.
Common Weakness Enumeration (CWE)
Use of Insufficiently Random Values
Use of Insufficiently Random Values
GitHub
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CVSS SCORE
9.4criticalPackage | Type | OS Name | OS Version | Affected Ranges | Fix Versions |
---|---|---|---|---|---|
form-data | npm | - | - | >=4.0.0,<4.0.4 | 4.0.4 |
form-data | npm | - | - | <2.5.4 | 2.5.4 |
form-data | npm | - | - | >=3.0.0,<3.0.4 | 3.0.4 |
CVSS:4 Severity and metrics
The CVSS metrics represent different qualitative aspects of a vulnerability that impact the overall score, as defined by the CVSS Specification.
The vulnerable component is bound to the network stack, but the attack is limited at the protocol level to a logically adjacent topology. This can mean an attack must be launched from the same shared physical (e.g., Bluetooth or IEEE 802.11) or logical (e.g., local IP subnet) network, or from within a secure or otherwise limited administrative domain (e.g., MPLS, secure VPN to an administrative network zone). One example of an Adjacent attack would be an ARP (IPv4) or neighbor discovery (IPv6) flood leading to a denial of service on the local LAN segment (e.g., CVE-2013-6014).
A successful attack depends on conditions beyond the attacker's control, requiring investing a measurable amount of effort in research, preparation, or execution against the vulnerable component before a successful attack.
The successful attack does not depend on the deployment and execution conditions of the vulnerable system. The attacker can expect to be able to reach the vulnerability and execute the exploit under all or most instances of the vulnerability.
The attacker is unauthenticated prior to attack, and therefore does not require any access to settings or files of the vulnerable system to carry out an attack.
The vulnerable system can be exploited without interaction from any human user, other than the attacker. Examples include: a remote attacker is able to send packets to a target system a locally authenticated attacker executes code to elevate privileges.
There is a total loss of confidentiality, resulting in all information within the Vulnerable System being divulged to the attacker. Alternatively, access to only some restricted information is obtained, but the disclosed information presents a direct, serious impact. For example, an attacker steals the administrator's password, or private encryption keys of a web server.
There is a total loss of confidentiality, resulting in all resources within the Subsequent System being divulged to the attacker. Alternatively, access to only some restricted information is obtained, but the disclosed information presents a direct, serious impact. For example, an attacker steals the administrator's password, or private encryption keys of a web server.
There is a total loss of integrity, or a complete loss of protection. For example, the attacker is able to modify any/all files protected by the Vulnerable System. Alternatively, only some files can be modified, but malicious modification would present a direct, serious consequence to the Vulnerable System.
There is a total loss of integrity, or a complete loss of protection. For example, the attacker is able to modify any/all files protected by the Subsequent System. Alternatively, only some files can be modified, but malicious modification would present a direct, serious consequence to the Subsequent System.
There is no impact to availability within the Vulnerable System.
There is no impact to availability within the Subsequent System or all availability impact is constrained to the Vulnerable System.
NIST
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CVSS SCORE
9.4criticalDebian
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Ubuntu
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CVSS SCORE
N/AmediumChainguard
CGA-33jw-22px-525h
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Chainguard
CGA-35hh-78jw-8mmq
-
Chainguard
CGA-3ppj-394x-84fc
-
Chainguard
CGA-573v-r77h-q9g9
-
Chainguard
CGA-89jc-64x6-7p8r
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Chainguard
CGA-9m6x-qcrx-9xfj
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Chainguard
CGA-cvhq-qgx3-vfx9
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Chainguard
CGA-f3gm-jqqm-vg4v
-
Chainguard
CGA-ffx2-8r2v-jj75
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Chainguard
CGA-g2fp-rgfq-2hjj
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Chainguard
CGA-h6v7-23w8-2vw8
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Chainguard
CGA-mp9r-pq3p-q3qc
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Chainguard
CGA-pcqg-rp64-6jqw
-
Chainguard
CGA-pgwm-362h-3mjh
-
Chainguard
CGA-qvfw-fcfj-g5xq
-
Chainguard
CGA-rvcj-gcgm-25q3
-
Chainguard
CGA-xvgg-cqm9-vxh5
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