Skip to main content
Glama
SlanyCukr

Bug Bounty MCP Server

by SlanyCukr

paramspider_mining

Extract URL parameters from web archives using ParamSpider to identify potential attack surfaces for bug bounty reconnaissance and security testing.

Instructions

Execute ParamSpider for parameter mining from web archives with enhanced logging.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
additional_argsNo
domainYes
excludeNopng,jpg,gif,jpeg,swf,woff,svg,pdf,css,ico
levelNo
outputNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • MCP handler function for the 'paramspider_mining' tool. Proxies parameters to the REST API endpoint '/api/paramspider-mining' for execution.
    @mcp.tool()
    def paramspider_mining(
        domain: str,
        level: int = 2,
        exclude: str = "png,jpg,gif,jpeg,swf,woff,svg,pdf,css,ico",
        output: str = "",
        additional_args: str = "",
    ) -> dict[str, Any]:
        """Run ParamSpider to mine parameters from archives with logging."""
        data = {
            "domain": domain,
            "level": level,
            "exclude": exclude,
            "output": output,
            "additional_args": additional_args,
        }
    
        logger.info(f"πŸ•ΈοΈ Starting ParamSpider parameter mining for {domain}")
        result = api_client.safe_post("api/paramspider-mining", data)
    
        if result.get("success"):
            logger.info(f"βœ… ParamSpider mining completed for {domain}")
        else:
            logger.error("❌ ParamSpider mining failed")
    
        return result
  • Backend handler that executes the actual ParamSpider command, parses output, and structures findings.
    @tool(required_fields=["domain"])
    def execute_paramspider():
        """Execute ParamSpider for parameter mining from web archives."""
        data = request.get_json()
        params = extract_paramspider_params(data)
    
        started_at = datetime.now()
        command = build_paramspider_command(params)
        execution_result = execute_command(
            " ".join(command), timeout=params.get("timeout", 600)
        )
        ended_at = datetime.now()
    
        return parse_paramspider_output(
            execution_result, params, command, started_at, ended_at
        )
  • Helper to extract and normalize parameters for ParamSpider execution.
    def extract_paramspider_params(data: dict) -> dict:
        """Extract and organize paramspider parameters from request data."""
        # Extract domain from URL if provided
        domain = data.get("domain", data.get("url", ""))
        if domain.startswith("http"):
            parsed = urlparse(domain)
            domain = parsed.netloc
    
        return {
            "domain": domain,
            "stream": data.get("stream", True),
            "placeholder": data.get("placeholder", "FUZZ"),
            "proxy": data.get("proxy", ""),
            "exclude": data.get("exclude", []),
            "output": data.get("output", ""),
            "level": data.get("level", 1),
            "subs": data.get("subs", False),
            "silent": data.get("silent", False),
            "clean": data.get("clean", False),
            "aggressive": data.get("aggressive", False),
            "additional_args": data.get("additional_args", ""),
            "timeout": data.get("timeout", 600),
        }
  • Helper to construct the ParamSpider CLI command from processed parameters.
    def build_paramspider_command(params: dict) -> list[str]:
        """Build the paramspider command from parameters."""
        args = ["paramspider", "-d", params["domain"]]
    
        # Add stream mode (-s flag) for real-time output
        if params["stream"]:
            args.append("-s")
    
        # Add placeholder for parameter values
        if params["placeholder"] and params["placeholder"] != "FUZZ":
            args.extend(["-p", params["placeholder"]])
    
        # Add proxy if specified
        if params["proxy"]:
            args.extend(["--proxy", params["proxy"]])
    
        # Add level (recursion depth)
        if params["level"] > 1:
            args.extend(["-l", str(params["level"])])
    
        # Add subdomain inclusion
        if params["subs"]:
            args.append("--subs")
    
        # Add exclude patterns
        exclude = params.get("exclude", [])
        if exclude:
            if isinstance(exclude, list):
                exclude_str = " ".join(exclude)
            else:
                exclude_str = str(exclude).strip()
            if exclude_str:
                args.extend(["--exclude", exclude_str])
    
        # Add output file
        if params["output"]:
            args.extend(["-o", params["output"]])
    
        # Add silent mode
        if params["silent"]:
            args.append("--silent")
    
        # Add any additional arguments
        if params["additional_args"]:
            args.extend(params["additional_args"].split())
    
        return args
  • Helper to parse ParamSpider output into structured findings with timings and stats.
    def parse_paramspider_output(
        execution_result: dict[str, Any],
        params: dict,
        command: list[str],
        started_at: datetime,
        ended_at: datetime,
    ) -> dict[str, Any]:
        """Parse paramspider execution results into structured findings."""
        duration_ms = int((ended_at - started_at).total_seconds() * 1000)
    
        if not execution_result["success"]:
            return {
                "success": False,
                "tool": "paramspider",
                "params": params,
                "command": command,
                "started_at": started_at.isoformat(),
                "ended_at": ended_at.isoformat(),
                "duration_ms": duration_ms,
                "error": execution_result.get("error", "Command execution failed"),
                "findings": [],
                "stats": {"findings": 0, "dupes": 0, "payload_bytes": 0},
            }
    
        # Parse successful output
        stdout = execution_result.get("stdout", "")
        findings = []
    
        # Extract parameters from paramspider output
        for line in stdout.strip().split("\n"):
            line = line.strip()
            if not line:
                continue
    
            # Parse parameter findings
            param_info = _extract_parameter_from_line(line)
            if param_info:
                finding = {
                    "type": "parameter",
                    "target": param_info.get("target", params["domain"]),
                    "evidence": {
                        "raw_output": line,
                        "parameter_name": param_info.get("parameter_name"),
                        "url": param_info.get("url"),
                    },
                    "severity": "info",
                    "confidence": "medium",
                    "tags": ["paramspider", "parameter-discovery"],
                    "raw_ref": line,
                }
                findings.append(finding)
    
        payload_bytes = len(stdout.encode("utf-8"))
    
        return {
            "success": True,
            "tool": "paramspider",
            "params": params,
            "command": command,
            "started_at": started_at.isoformat(),
            "ended_at": ended_at.isoformat(),
            "duration_ms": duration_ms,
            "findings": findings,
            "stats": {
                "findings": len(findings),
                "dupes": 0,
                "payload_bytes": payload_bytes,
            },
        }
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'enhanced logging' which hints at output behavior, but fails to describe critical traits: whether this is a read-only or destructive operation, what permissions or prerequisites are needed, rate limits, or what the output entails (e.g., file generation, console output). For a tool with 5 parameters and no annotations, this is a significant gap in transparency.

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, efficient sentence that is front-loaded with the main action. It avoids unnecessary words, though it could be more structured by separating purpose from features. The brevity is appropriate, but the lack of detail reduces its overall utility.

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?

Given the complexity (5 parameters, 0% schema coverage, no annotations) and the presence of an output schema, the description is incomplete. It doesn't explain parameter meanings, usage context, or behavioral traits, relying solely on the output schema for return values. For a tool with multiple parameters and no annotation support, this leaves too many gaps for the agent to operate effectively.

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%, so the schema provides no parameter descriptions. The tool description does not mention any parameters, leaving all 5 parameters (domain, level, exclude, output, additional_args) undocumented. This forces the agent to guess based on titles alone, which is inadequate for effective tool invocation.

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

Purpose3/5

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

The description states the tool 'Execute[s] ParamSpider for parameter mining from web archives' which provides a clear verb ('Execute') and resource ('ParamSpider'), but it's vague about what 'parameter mining' entails and doesn't distinguish it from sibling tools like 'arjun_parameter_discovery' or 'x8_parameter_discovery' that also handle parameter discovery. The 'enhanced logging' addition is somewhat specific but doesn't clarify the core functionality enough.

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?

No guidance is provided on when to use this tool versus alternatives. The description mentions 'parameter mining from web archives' but doesn't specify scenarios, prerequisites, or exclusions compared to siblings like 'gau_discovery' or 'waybackurls_discovery' that might overlap in web archive usage. This leaves the agent without context for tool selection.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/SlanyCukr/bugbounty-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server