cve.bz

CAPEC-261

Fuzzing for garnering other adjacent user/sensitive data

Medium severityDetailed pattern

An adversary who is authorized to send queries to a target sends variants of expected queries in the hope that these modified queries might return information (directly or indirectly through error logs) beyond what the expected set of queries should provide.

On this page

Many client applications use specific query templates when interacting with a server and often automatically fill in specific fields or attributes. If the server does not verify that the query matches one of the expected templates, an adversary who is allowed to send normal queries could modify their query to try to return additional information. The adversary may not know the names of fields to request or how other modifications will affect the server response, but by attempting multiple plausible variants, they might eventually trigger a server response that divulges sensitive information. Other possible outcomes include server crashes and resource consumption if the unexpected queries cause the server to enter an unstable state or perform excessive computation.

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Show the promptExplain the attack pattern CAPEC-261: Fuzzing for garnering other adjacent user/sensitive data: how it unfolds, what it needs and how to prevent and detect it in my systems. Use https://capec.mitre.org/data/definitions/261.html and https://cve.bz/cve/capec/261?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. [Observe communication and inputs] The fuzzing adversary observes the target system looking for inputs and communications between modules, subsystems, or systems.

      3 techniques
      • Network sniffing. Using a network sniffer such as wireshark, the adversary observes communications into and out of the target system.
      • Monitor API execution. Using a tool such as ktrace, strace, APISpy, or another debugging tool, the adversary observes the system calls and API calls that are made by the target system, and the nature of their parameters.
      • Observe inputs using web inspection tools (OWASP's WebScarab, Paros, TamperData, TamperIE, etc.)

  2. Experiment

    They probe what they found.

    1. [Generate fuzzed inputs] Given a fuzzing tool, a target input or protocol, and limits on time, complexity, and input variety, generate a list of inputs to try. Although fuzzing is random, it is not exhaustive. Parameters like length, composition, and how many variations to try are important to get the most cost-effective impact from the fuzzer.

      2 techniques
      • Boundary cases. Generate fuzz inputs that attack boundary cases of protocol fields, inputs, or other communications limits. Examples include 0xff and 0x00 for single-byte inputs. In binary situations, approach each bit of an individual field with on and off (e.g., 0x80).
      • Attempt arguments to system calls or APIs. The variations include payloads that, if they were successful, could lead to a compromise on the system.

    2. [Observe the outcome] Observe the outputs to the inputs fed into the system by fuzzers and see if there are any log or error messages that either provide user/sensitive data or give information about an expected template that could be used to produce this data.

  3. Exploit

    They carry out the attack.

    1. [Craft exploit payloads] If the logs did not reveal any user/sensitive data, an adversary will attempt to make the fuzzing inputs form to an expected template

      4 techniques
      • Create variants of expected templates that request additional information
      • Create variants that exclude limiting clauses
      • Create variants that alter fields taht identify the requester in order to subvert access controls
      • Repeat different fuzzing variants until sensitive information is divulged

Prerequisites

  • The server must assume that the queries it receives follow specific templates and/or have fields or attributes that follow specific procedures. The server must process queries that it receives without adequately checking or sanitizing queries to ensure they follow these templates.

Resources required

  • The attacker must have sufficient privileges to send queries to the targeted server. A normal client might limit the nature of these queries, so the attacker must either have a modified client or their own application which allows them to modify the expected queries.

Weaknesses it exploits

  • CWE-20 Improper Input Validation

Recent CVEs with these weaknesses

  1. 9.6CVE-2026-108186

    Improper Input Validation in Zoom Workplace for Windows may allow an unauthenticated user to conduct an escalation of privilege via network access.

  2. 4.9CVE-2026-105427

    Improper input validation in Ivanti EPMM before version 12.10.0.1, 12.9.0.3, and 12.8.0.5 allows a remote authenticated attacker with admin privileges to permanently disable all Apache HTTPS services resulting in denial of service.

  3. 6.7CVE-2026-105426

    Improper input validation in Ivanti EPMM before version 12.10.0.1, 12.9.0.3, and 12.8.0.5 allows a remote authenticated attacker with admin privileges to set arbitrary Linux kernel parameters as root.

  4. 4.3CVE-2026-123178

    An insufficient input validation vulnerability in the listed NETGEAR Orbi Models router allows an authenticated administrator connected to the local network to execute unauthorized commands and modify the router’s software and functionalit…

  5. 6.3CVE-2026-125871

    The sourcecache expansion module in MISP Modules (misp-modules) contains a Server-Side Request Forgery (SSRF) vulnerability. When a user with permission to create or modify attributes of type 'link' or 'url' submits an attribute value, the…

  6. 5.5CVE-2026-125703

    A flaw was found in the GStreamer gst-plugins-bad MXF plugin. Insufficient bounds checks when parsing crafted VANC data can cause an out-of-bounds read in the demuxer, while an incorrect buffer size calculation when muxing multiple ancilla…

  7. 5.3CVE-2026-125113

    The XRootD project provides a high-performance, fault-tolerant, and secure solution for handling large amounts of data distributed across multiple storage resources. Prior to version 5.9.2, XRootD's rpCheck() function in src/XrdXrootd/XrdX…

  8. 6.9CVE-2026-63634

    pympp is a Python SDK for the Machine Payments Protocol. Prior to version 0.9.1, when the server acts as the fee_payer, pympp validates calldata using eth_abi decoding, which is lenient about trailing bytes. The FeePayerPolicy caps gas_lim…

The newest records naming one of them. Each weakness's page lists them all.

Part of

Examples

A client that queries an employee database might have templates such that the user only supplies the target's…

A client that queries an employee database might have templates such that the user only supplies the target's name and the template dictates the fields to be returned (location, position in the company, phone number, etc.). If the server does not verify that the query matches one of the expected templates, an attacker who is allowed to send normal queries could modify their query to try to return additional information. For this example, additional information might include social security numbers or salaries.

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