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Detect obfuscation patterns

detect_obfuscation
Read-only

Detects common obfuscation patterns in a function—control-flow flattening, string encryption, anti-debugging, and dead code—and returns flags with details.

Instructions

检测常见混淆模式:控制流平坦化、字符串加密、反调试、死代码,返回各标志与详情。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
instance_idNoOptional database instance id. If omitted, use the current target.
function_addressYes要检测混淆的函数地址

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
detailsNo
dead_codeNo
anti_debugNo
flatteningNo
string_encryptionNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv20261008.0.1

TDQS

B3.4/5.0
Behavior3/5

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

readOnlyHint=true already tells the agent this is a non-mutating analysis. The description adds useful context by naming the pattern categories covered and noting it returns per-flag results and details, but it says nothing about analysis cost, timeouts, or limits on functions that can be scanned.

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

Conciseness5/5

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

A single front-loaded sentence that lists the detection scope and the return shape with zero padding. Nothing could be removed without losing information.

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

Completeness4/5

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 need not be explained, and annotations cover the safety profile; the description covers purpose and detection scope adequately. Minor gap: no note about how this differs from the broader analyze_function report tool.

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

Parameters3/5

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

Schema description coverage is 100% and both parameters are documented there, including the optional instance_id fallback and the function_address meaning. The description adds no parameter-level detail beyond confirming the target is a function, so baseline 3 applies.

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 verb (detect) and resource (obfuscation patterns) and enumerates the concrete pattern classes checked (control-flow flattening, string encryption, anti-debugging, dead code). This distinguishes it from analysis siblings, though it never names an alternative tool directly.

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?

There is no explicit when-to-use / when-not-to-use guidance and no mention of related siblings such as analyze_function or analyze_batch that also operate on a function. The agent must infer the entry condition (having a function address) from the schema alone.

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