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crlfuzz_scan

Scan a URL for CRLF injection vulnerabilities that enable HTTP response splitting, leading to XSS, cache poisoning, or session fixation.

Instructions

Scan a URL for CRLF injection vulnerabilities using CRLFuzz.

CRLF injection (HTTP Response Splitting) allows attackers to inject arbitrary HTTP headers or split HTTP responses, potentially leading to XSS, cache poisoning, or session fixation.

Args: url: Target URL to scan (e.g. "https://example.com/redirect?url=test"). threads: Number of concurrent threads (default 25, max 50). timeout: Override scan timeout in seconds.

Returns: CRLF injection scan results with vulnerable URLs and evidence.

Note: - Target must be in tengu.toml [targets].allowed_hosts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
threadsNo
timeoutNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations provided, the description carries the transparency burden. It explains the nature of the scan, the impact of CRLF injection, and the allowed_hosts constraint. It does not explicitly state whether the scan is read-only or mention rate limits, but the provided context (threads, timeout) and return behavior give reasonable insight into the tool's operations.

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?

The description is well-organized with clear sections (Description, Impact, Args, Returns, Note). Each sentence adds meaningful information, and the length is appropriate for the complexity of the tool with three parameters and a security-relevant context.

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

Completeness5/5

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

The description covers purpose, parameters, return values, and a usage constraint. It is sufficient for an agent to select and invoke the tool appropriately, especially given the presence of an output schema. The note about allowed_hosts is a critical context piece that is not in the schema.

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?

Despite the input schema having no property descriptions, the description compensates fully with an Args section. It explains each parameter's purpose: url with an example, threads with default and max, and timeout as an override. This is exemplary parameter documentation that goes far beyond the schema.

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 function: "Scan a URL for CRLF injection vulnerabilities using CRLFuzz." This specifies the exact vulnerability type, the target resource, and the underlying tool, making it easily distinguishable from sibling scanning tools like xss_scan or nuclei_scan.

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

Usage Guidelines4/5

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

The description clearly implies when to use the tool (to test for CRLF injection) and includes an important prerequisite: "Target must be in tengu.toml [targets].allowed_hosts." However, it does not explicitly contrast with alternative tools or provide when-not-to-use guidance, so it lacks the full differentiation expected for a 5.

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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