Low Risk

attack_timeline_tool

Attack volume over time, bucketed by hour or day. Use for: 'show attack trends this week', 'was there a spike on port 22?', 'how has SSH scanning changed?', 'attack volume from China over 30 days'. bucket: 'hour' or 'day'. Optional filters: filter_protocol ('tls'/'''), filter_country (2-letter co...

Part of the HoneyLabs server.

attack_timeline_tool is read-only, but an agent in a loop can still rack up calls and cost. PolicyLayer caps every call before it runs. Live in minutes.

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AI agents call attack_timeline_tool to retrieve information from HoneyLabs without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.

Even though attack_timeline_tool only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.

Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "attack_timeline_tool": {}
  }
}

See the full HoneyLabs policy for all 8 tools.

Get this rule live on your own HoneyLabs server in minutes. PolicyLayer enforces it on every call, before it runs.

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These attack patterns abuse exactly the kind of access attack_timeline_tool gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so attack_timeline_tool only ever does what you allow.

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Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.

What does the attack_timeline_tool tool do? +

Attack volume over time, bucketed by hour or day. Use for: 'show attack trends this week', 'was there a spike on port 22?', 'how has SSH scanning changed?', 'attack volume from China over 30 days'. bucket: 'hour' or 'day'. Optional filters: filter_protocol ('tls'/'''), filter_country (2-letter code), filter_dest_port. since/until ISO-8601 UTC.. It is categorised as a Read tool in the HoneyLabs MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on attack_timeline_tool? +

Register the HoneyLabs MCP server in PolicyLayer and add a rule for attack_timeline_tool: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches HoneyLabs. Nothing to install.

What risk level is attack_timeline_tool? +

attack_timeline_tool is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit attack_timeline_tool? +

Yes. Add a rate_limit block to the attack_timeline_tool rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block attack_timeline_tool completely? +

Set action: deny in the PolicyLayer policy for attack_timeline_tool. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides attack_timeline_tool? +

attack_timeline_tool is provided by the HoneyLabs MCP server (https://mcp.honeylabs.net/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every HoneyLabs tool call.

Deterministic rules across all 8 HoneyLabs tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

Free to start. No card required.

4,600+ MCP servers and 31,000+ tools scanned and risk-classified.

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