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fuzzmind

fuzzmind-frida-mcp

by fuzzmind

frida_linux_preload_detect

Detects LD_PRELOAD attacks and suspicious library injections on Linux by examining environment variables, system config, and loaded libraries for non-standard paths and memory-backed modules.

Instructions

[Linux] Detect LD_PRELOAD and suspicious library injections.

Checks LD_PRELOAD env var, /etc/ld.so.preload, and enumerates loaded libraries flagging non-standard paths, /tmp, /dev/shm, and memfd-backed modules.

target: process name or pid (string).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetYes
Behavior3/5

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

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It explains the checks performed but does not mention safety, potential side effects, permission requirements, or whether the tool modifies any state. It is not misleading but lacks completeness.

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 concise, with a front-loaded summary and structured details. Each sentence adds value. However, it could be slightly more streamlined without losing clarity.

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

Completeness3/5

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

Given the tool's simplicity (one parameter, no output schema), the description adequately explains what it does. However, it does not describe the return value or output format, which would be helpful for an agent to process results. Overall, it covers the basics but could provide more complete context.

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

Parameters5/5

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

The description adds significant value beyond the schema: it clarifies that the 'target' parameter is a process name or PID, and that it is a string. Schema coverage is 0%, so the description fully compensates by explaining the parameter's meaning and usage.

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

Purpose5/5

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

The description clearly states the tool's purpose: 'Detect LD_PRELOAD and suspicious library injections' on Linux. It lists specific checks (LD_PRELOAD env var, /etc/ld.so.preload, loaded libraries marking non-standard paths). This is distinct from sibling tools like frida_linux_seccomp_detect or frida_linux_dbus_intercept.

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

Usage Guidelines3/5

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

The description implies usage for detecting preload injections but does not explicitly state when to use this tool versus alternatives (e.g., other Linux security tools). No guidance on when not to use it or prerequisites. The usage context is inferred but not explicit.

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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