External Control of Assumed-Immutable Web Parameter

Description

This vulnerability occurs when a web application incorrectly trusts data that appears to be fixed or hidden from the user, such as values in hidden form fields, cookies, or URL parameters. Because this data is actually controllable by the client, attackers can modify it to bypass security checks or corrupt application logic.

Extended Description

Web applications often make a critical mistake: they assume that data sent to the client in hidden fields, cookies, or parameters will be returned unchanged. Since all client-side data can be tampered with, this false sense of security leads to improper validation. Attackers exploit this by modifying these assumed-immutable values to escalate privileges, manipulate prices, alter user sessions, or corrupt backend data flows. The core issue is the server's over-reliance on client-provided data for making security decisions. To prevent this, always validate and authorize all user input on the server, regardless of its perceived source or immutability. Treat hidden fields and cookies as untrusted input, just like any other form field. Implementing proper server-side session management and using cryptographic signatures for critical data can help enforce integrity. Managing these validation rules across a complex application is challenging; an ASPM platform like Plexicus can automatically detect these trust violations via DAST and SAST, and its AI can suggest precise code fixes to enforce server-side validation, streamlining remediation.

Common Consequences 1

Scope: Integrity

Impact: Modify Application Data

Without appropriate protection mechanisms, the client can easily tamper with cookies and similar web data. Reliance on the cookies without detailed validation can lead to problems such as SQL injection. If you use cookie values for security related decisions on the server side, manipulating the cookies might lead to violations of security policies such as authentication bypassing, user impersonation and privilege escalation. In addition, storing sensitive data in the cookie without appropriate protection can also lead to disclosure of sensitive user data, especially data stored in persistent cookies.

Detection Methods 1

Automated Static AnalysisHigh

Automated static analysis, commonly referred to as Static Application Security Testing (SAST), can find some instances of this weakness by analyzing source code (or binary/compiled code) without having to execute it. Typically, this is done by building a model of data flow and control flow, then searching for potentially-vulnerable patterns that connect "sources" (origins of input) with "sinks" (destinations where the data interacts with external components, a lower layer such as the OS, etc.)

Potential Mitigations 2

Phase: Implementation

Strategy: Input Validation

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.

Phase: Implementation

Strategy: Input Validation

Inputs should be decoded and canonicalized to the application's current internal representation before being validated (Incorrect Behavior Order: Validate Before Canonicalize). Make sure that the application does not decode the same input twice (Double Decoding of the Same Data). Such errors could be used to bypass allowlist validation schemes by introducing dangerous inputs after they have been checked.

Demonstrative Examples 2

In this example, a web application uses the value of a hidden form field (accountID) without having done any input validation because it was assumed to be immutable.

Code Example:Bad
Java
java

Hidden fields should not be trusted as secure parameters.

An attacker can intercept and alter hidden fields in a post to the server as easily as user input fields. An attacker can simply parse the HTML for the substring:

Code Example:Bad
HTML
html

or even just "hidden". Hidden field values displayed later in the session, such as on the following page, can open a site up to cross-site scripting attacks.

Observed Examples 13

CVE-2002-0108Forum product allows spoofed messages of other users via hidden form fields for name and e-mail address.

CVE-2000-0253Shopping cart allows price modification via hidden form field.

CVE-2000-0254Shopping cart allows price modification via hidden form field.

CVE-2000-0926Shopping cart allows price modification via hidden form field.

CVE-2000-0101Shopping cart allows price modification via hidden form field.

CVE-2000-0102Shopping cart allows price modification via hidden form field.

CVE-2000-0758Allows admin access by modifying value of form field.

CVE-2002-1880Read messages by modifying message ID parameter.

CVE-2000-1234Send email to arbitrary users by modifying email parameter.

CVE-2005-1652Authentication bypass by setting a parameter.

CVE-2005-1784Product does not check authorization for configuration change admin script, leading to password theft via modified e-mail address field.

CVE-2005-2314Logic error leads to password disclosure.

CVE-2005-1682Modification of message number parameter allows attackers to read other people's messages.

References 2

24 Deadly Sins of Software Security

Michael Howard, David LeBlanc, and John Viega

McGraw-Hill

2010

ID: REF-44

The Art of Software Security Assessment

Mark Dowd, John McDonald, and Justin Schuh

Addison Wesley

2006

ID: REF-62

Applicable Platforms

Languages:

Not Language-Specific : Undetermined

Modes of Introduction

Implementation

Related Attack Patterns

Alternate Terms

Assumed-Immutable Parameter Tampering

Related Weaknesses

ChildOf:

External Control of Critical State Data (CWE-642)

ChildOf:

Modification of Assumed-Immutable Data (MAID) (CWE-471)

Taxonomy Mapping

PLOVER
OWASP Top Ten 2007
OWASP Top Ten 2004

Notes

RelationshipThis is a primary weakness for many other weaknesses and functional consequences, including XSS, SQL injection, path disclosure, and file inclusion.

TheoreticalThis is a technology-specific MAID problem.