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websex_mass_assignment_probe

Tests for mass assignment by injecting sensitive fields like role or admin into create/update requests, then re-reading the object to confirm persistence.

Instructions

Over-posting: inject sensitive fields (role/admin/balance/flags) into create/update and verify persistence by re-reading the object. High-confidence on persisted sentinels.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
fieldsNo
methodNoPOST
headersYes
base_bodyNo
content_typeNoapplication/json
max_requestsNo
engagement_idYes
sentinel_valuesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.9/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must carry the full behavioral burden. It does disclose the mechanism (inject fields, re-read to confirm persistence) and hints at confidence scoring ('high-confidence on persisted sentinels'), but omits authorization prerequisites, that it actively mutates target state, rate/request limits implied by max_requests, and failure behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tight sentences, front-loaded with the technique and followed by the verification/confidence claim. No filler, though it is arguably too terse given the parameter surface it must cover.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists so return values needn't be explained, but for a mutating 9-parameter probe with zero annotation and zero schema-description coverage, the description is far too thin on prerequisites, request semantics, and safety context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% across 9 parameters, so the description must compensate and largely fails to. It loosely maps to 'fields' (role/admin/balance/flags) and 'method' (create/update), but url, headers, engagement_id, base_body, content_type, max_requests, and sentinel_values remain undocumented in both places.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific technique (over-posting / mass assignment), the exact action (inject sensitive fields into create/update), and the verification method (re-read the object). This distinguishes it reasonably from generic siblings like api_fuzz or http_repeater, though it never names a sibling explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains what the probe does but gives no guidance on when to reach for it versus adjacent probes (bfla_probe, idor_probe, logic_probe, api_fuzz) or raw http_request. No preconditions, no when-not-to-use, no exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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