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JNISleuth-MCP

JNISleuth-MCP

by nighthawkk
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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extract_jni_onload_strings

Extracts stack-constructed and XOR-decrypted strings from .init_array and JNI_OnLoad in Android native libraries to reveal hidden indicators during reverse engineering.

Instructions

Dumps stack-constructed and XOR-decrypted strings inside .init_array and JNI_OnLoad.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "so_name": "<so_name>"
    },
    "name": "extract_jni_onload_strings"
  }
}

Input Schema

NameRequiredDescriptionDefault
so_nameYes
apk_pathNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.6/5.0
Behavior2/5

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

With no annotations and no output schema, the description carries the full burden of behavioral disclosure. It mentions that strings are stack-constructed and XOR-decrypted, but does not explain return format, permissions, side effects, or how the required `so_name` and optional `apk_path` are used.

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?

The description is a single front-loaded sentence with no filler, so it is structurally efficient. Its brevity contributes to under-specification, but that is better assessed under contextual completeness.

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?

This is a specialized binary/JNI analysis tool with no annotations, no output schema, and zero parameter documentation. The one-sentence description identifies the targets but omits essential context such as parameter roles, output shape, prerequisites, and relationship to sibling deobfuscation tools.

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

Parameters1/5

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

Schema description coverage is 0%, so the description must compensate by explaining the two parameters. It does not mention `so_name` or `apk_path` at all, leaving both parameters semantically undocumented.

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?

The description uses a specific verb, "Dumps," and names the exact artifact type: stack-constructed and XOR-decrypted strings inside `.init_array` and `JNI_OnLoad`. This makes the tool's purpose clear, though it does not explicitly differentiate it from the sibling `deobfuscate_jni_strings`.

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 states what the tool extracts but gives no guidance on when to use it versus alternatives such as `deobfuscate_jni_strings`. There are no prerequisites, exclusions, or routing cues for the agent.

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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