Cross-Site Request Forgery (CSRF)

Description

Cross-Site Request Forgery (CSRF) happens when a web application cannot reliably tell if a user actually intended to submit a request, allowing an attacker to trick a user's browser into performing unwanted actions on their behalf.

Extended Description

Imagine you're logged into your bank's website in one tab. In another tab, you click a malicious link or visit a booby-trapped site. That malicious page can silently send a request to your bank's site—like a funds transfer—using your existing, logged-in session. Because your browser automatically includes your session cookies, the bank sees the request as legitimate and coming from you, even though you never intended to send it. To prevent this, applications must verify that state-changing requests (like logins, transfers, or profile updates) are deliberate. The most common and effective defense is to use anti-CSRF tokens: unique, secret values embedded in forms or requests that the server validates. Other protections include checking the `Origin` or `Referer` headers for same-origin requests, or requiring re-authentication for sensitive operations. Without these guards, attackers can exploit a user's trust in a site to perform actions without their consent.

Common Consequences 1

Scope: ConfidentialityIntegrityAvailabilityNon-RepudiationAccess Control

Impact: Gain Privileges or Assume IdentityBypass Protection MechanismRead Application DataModify Application DataDoS: Crash, Exit, or Restart

The consequences will vary depending on the nature of the functionality that is vulnerable to CSRF. An attacker could trick a client into making an unintentional request to the web server via a URL, image load, XMLHttpRequest, etc., which would then be treated as an authentic request from the client - effectively performing any operations as the victim, leading to an exposure of data, unintended code execution, etc. If the victim is an administrator or privileged user, the consequences may include obtaining complete control over the web application - deleting or stealing data, uninstalling the product, or using it to launch other attacks against all of the product's users. Because the attacker has the identity of the victim, the scope of CSRF is limited only by the victim's privileges.

Detection Methods 9

Manual AnalysisHigh

This weakness can be detected using tools and techniques that require manual (human) analysis, such as penetration testing, threat modeling, and interactive tools that allow the tester to record and modify an active session. Specifically, manual analysis can be useful for finding this weakness, and for minimizing false positives assuming an understanding of business logic. However, it might not achieve desired code coverage within limited time constraints. For black-box analysis, if credentials are not known for privileged accounts, then the most security-critical portions of the application may not receive sufficient attention. Consider using OWASP CSRFTester to identify potential issues and aid in manual analysis.

Automated Static AnalysisLimited

CSRF is currently difficult to detect reliably using automated techniques. This is because each application has its own implicit security policy that dictates which requests can be influenced by an outsider and automatically performed on behalf of a user, versus which requests require strong confidence that the user intends to make the request. For example, a keyword search of the public portion of a web site is typically expected to be encoded within a link that can be launched automatically when the user clicks on the link.

Automated Static Analysis - Binary or BytecodeSOAR Partial

According to SOAR [REF-1479], the following detection techniques may be useful: ``` Cost effective for partial coverage: ``` Bytecode Weakness Analysis - including disassembler + source code weakness analysis Binary Weakness Analysis - including disassembler + source code weakness analysis

Manual Static Analysis - Binary or BytecodeSOAR Partial

According to SOAR [REF-1479], the following detection techniques may be useful: ``` Cost effective for partial coverage: ``` Binary / Bytecode disassembler - then use manual analysis for vulnerabilities & anomalies

Dynamic Analysis with Automated Results InterpretationHigh

According to SOAR [REF-1479], the following detection techniques may be useful: ``` Highly cost effective: ``` Web Application Scanner

Dynamic Analysis with Manual Results InterpretationHigh

According to SOAR [REF-1479], the following detection techniques may be useful: ``` Highly cost effective: ``` Fuzz Tester Framework-based Fuzzer

Manual Static Analysis - Source CodeSOAR Partial

According to SOAR [REF-1479], the following detection techniques may be useful: ``` Cost effective for partial coverage: ``` Focused Manual Spotcheck - Focused manual analysis of source Manual Source Code Review (not inspections)

Automated Static Analysis - Source CodeSOAR Partial

According to SOAR [REF-1479], the following detection techniques may be useful: ``` Cost effective for partial coverage: ``` Source code Weakness Analyzer Context-configured Source Code Weakness Analyzer

Architecture or Design ReviewSOAR Partial

According to SOAR [REF-1479], the following detection techniques may be useful: ``` Cost effective for partial coverage: ``` Inspection (IEEE 1028 standard) (can apply to requirements, design, source code, etc.) Formal Methods / Correct-By-Construction

Potential Mitigations 7