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CAPEC-54

Query System for Information

Low severityHigh likelihoodStandard pattern

An adversary, aware of an application's location (and possibly authorized to use the application), probes an application's structure and evaluates its robustness by submitting requests and examining responses. Often, this is accomplished by sending variants of expected queries in the hope that these modified queries might return information beyond what the expected set of queries would provide.

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Show the promptExplain the attack pattern CAPEC-54: Query System for Information: how it unfolds, what it needs and how to prevent and detect it in my systems. Use https://capec.mitre.org/data/definitions/54.html and https://cve.bz/cve/capec/54?via=ask-ai-copy, which lists recent CVEs with the weaknesses it exploits. Cite the sources.

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How the attack unfolds

  1. Explore

    The attacker looks for a way in.

    1. [Determine parameters] Determine all user-controllable parameters of the application either by probing or by finding documentation

  2. Experiment

    They probe what they found.

    1. [Cause error condition] Inject each parameter with content that causes an error condition to manifest

    2. [Modify parameters] Modify the content of each parameter according to observed error conditions

  3. Exploit

    They carry out the attack.

    1. [Follow up attack] Once the above steps have been repeated with enough parameters, the application will be sufficiently mapped out. The adversary can then launch a desired attack (for example, Blind SQL Injection)

Prerequisites

  • This class of attacks does not strictly require authorized access to the application. As Attackers use this attack process to classify, map, and identify vulnerable aspects of an application, it simply requires hypotheses to be verified, interaction with the application, and time to conduct trial-and-error activities.

Skills required

  • Medium skill

    Although fuzzing parameters is not difficult, and often possible with automated fuzzers, interpreting the error conditions and modifying the parameters so as to move further in the process of mapping the application requires detailed knowledge of target platform, the languages and packages used as well as software design.

Resources required

  • The Attacker needs the ability to probe application functionality and provide it erroneous directives or data without triggering intrusion detection schemes or making enough of an impact on application logging that steps are taken against the adversary.

    The Attack does not need special hardware, software, skills, or access.

Signs of an attack

  • Repeated errors generated by the same piece of code are an indication, although it requires careful monitoring of the application and its associated error logs, if any.

Consequences

What a successful attack can lead to
ImpactAffectsNote
Read DataConfidentiality

Mitigations

  • Application designers can construct a 'code book' for error messages. When using a code book, application error messages aren't generated in string or stack trace form, but are cataloged and replaced with a unique (often integer-based) value 'coding' for the error. Such a technique will require helpdesk and hosting personnel to use a 'code book' or similar mapping to decode application errors/logs in order to respond to them normally.

  • Application designers can wrap application functionality (preferably through the underlying framework) in an output encoding scheme that obscures or cleanses error messages to prevent such attacks. Such a technique is often used in conjunction with the above 'code book' suggestion.

Weaknesses it exploits

  • CWE-209 Generation of Error Message Containing Sensitive Information

Recent CVEs with these weaknesses

  1. 7.5CVE-2026-120012

    SAP Cloud SDK for AI (Node.js) could inadvertently include sensitive authentication credentials in error messages generated by certain internal operations under specific failure conditions. An attacker with low privileges and access to app…

  2. 2.3CVE-2026-123373

    compose-lint is a Docker Compose security linter that identifies dangerous misconfigurations before deployment. From 0.2.0 until 0.25.0, compose-lint follows a project-controlled symbolic link used as the Compose file outside the project. …

  3. 2.3CVE-2026-123371

    compose-lint is a Docker Compose security linter that identifies dangerous misconfigurations before deployment. From 0.2.0 until 0.32.0, compose-lint automatically follows a .compose-lint.yml policy-file symbolic link outside the project a…

  4. 5.3CVE-2026-119613

    Generation of Error Message Containing Sensitive Information vulnerability in ash-project ash_ai allows a caller of an AshAi tool to read internal error details, including module names and data values, by making a tool call fail. AshAi.To…

  5. 4.3CVE-2026-17215

    IBM API Connect 10.0.8.0 through 10.0.8.12 and 12.1.0.0 through 12.1.1.2 could allow a remote authenticated attacker to obtain sensitive information due to verbose error messages. Error responses contain more information about the system t…

  6. 5.4CVE-2026-17114

    IBM API Connect 10.0.8.0 through 10.0.8.12 and 12.1.0.0 through 12.1.1.2 could allow a remote authenticated attacker to obtain sensitive information and cause a denial of service due to the generation of error messages containing sensitive…

  7. 5.3CVE-2026-17098

    IBM API Connect 10.0.8.0 through 10.0.8.12 and 12.1.0.0 through 12.1.1.2 could allow a remote attacker to obtain sensitive information due to verbose error messages.

  8. 10.0CVE-2026-73101

    Generation of Error Message Containing Sensitive Information vulnerability in Apache Juneau. The REST server sends the internal exception class and message to clients in a "Thrown" response header on every error response, and can include …

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Part of
More specific patterns

Examples

Blind SQL injection is an example of this technique, applied to successful exploit. See also: CVE-2006-4705

Blind SQL injection is an example of this technique, applied to successful exploit. See also: CVE-2006-4705

Attacker sends bad data at various servlets in a J2EE system, records returned exception stack traces, and ma…

Attacker sends bad data at various servlets in a J2EE system, records returned exception stack traces, and maps application functionality.

In addition, this technique allows attackers to correlate those servlets used with the underlying open source packages (and potentially version numbers) that provide them.

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