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Threatlist Analyze Agent

On-Demand IOC Investigation

A production module inside a Security Command Center (SCC) platform that takes a single indicator of compromise (IP, domain, URL, or hash) and runs a full analyst investigation autonomously — fanning out to many intelligence sources in parallel, sending a browser OSINT agent to visit and reason about the target, then synthesizing a verdict with an LLM: malicious, suspicious, benign, or an official asset.

#Threat Intelligence#IOC Enrichment#OSINT Automation#LLM / Agentic AI#Browser Automation#Multi-Source Fusion#Agentic RAG#Security Automation (SOC/SOAR)

// Overview

What it does. When an analyst encounters a suspicious IP, domain, URL, or file hash, the manual investigation is the same every time: check it against threat-intel feeds, look up WHOIS/registrar and hosting, see if it's appeared in past alerts, maybe open it in a sandbox, and finally decide — is this malicious, suspicious, benign, or actually one of our own official assets? This module does that whole investigation on demand and returns a single structured verdict with a risk score, the matched/impersonated brand, the indicators that fired, and a written rationale. Crucially it also distinguishes official vs impersonation, so a legitimate corporate domain isn't flagged as a threat.

// Background

The challenge

Every suspicious IOC triggers the same multi-step ritual.

Checking many feeds, WHOIS, and the live site — manually.

01

Same manual ritual, every time

Each IOC meant hand-checking several feeds, WHOIS,

past alerts, and the live site — minutes per indicator.

Repetitive multi-tab work, impossible at volume

02

Single-source verdicts were brittle

Relying on one reputation feed gave false confidence;

real judgment needs multiple signals fused together.

One feed says clean; another says malicious

03

B2B partners & own assets misflagged

Without company knowledge, B2B partner domains and

own infra looked suspicious — generating false positives.

B2B context missing → partners flagged malicious

04

Recon didn't scale

Actually visiting a site to read its branding and intent

was too slow to do for every indicator.

Human-grade recon was the bottleneck

Net effect

Manual multi-tab investigations, single-source verdicts,

and no brand ground truth made IOC triage slow,

inconsistent, and error-prone.

// Solution

Threatlist agent — parallel enrichment + browser OSINT

Data sources

One IOC (IP/domain/hash)

by analyst or automation

Intelligence sources

TIP · WHOIS · reputation APIs

knowledge base · asset RAG

Pipeline

Enrich

parallel asyncio

TIP·WHOIS·RAG

Enrich

AI Agents

AI browser agent

search · visit

Recon

Evidence

aggregate all

enrich+OSINT

Merge

Synthesis

DSPy signature

verdict+score

Synthesize

Result

stateless JSON

OFFICIAL / MALICIOUS

Result

Parallel asyncio fan-out · bounded semaphores · browser-use agent (read-only) · DSPy verdict synth · stateless JSON

// Impact

IOC triage: multi-tab → one call

Before · by hand

5+ tabs · WHOIS · open site

After · agent call

one call → parallel enrich → verdict

6+

concurrent enrichment sources per IOC

own assets falsely flaggedprevented
Manual multi-tab workeliminated

Operational impact

Whole investigation in one call

minutes → one scored verdict

Fused, robust judgments

concurrent enrichment beats one feed

B2B & official assets protected

B2B partners → OFFICIAL, not malicious

Human-grade recon, automated

agent does 'go look' at machine scale

Composable by design

stateless JSON: portal, chat, pipelines

Every agent run traced

OSINT steps replayable · audit trail

Results

Verdict classes

4

Enrich sources

6+

stateless

0

explainable

100%

B2B partners flaggedprevented
Manual multi-tab triageautomated

Verdict · risk score · matched brand ·

key indicators · summary per IOC.

// Tech Stack

LayerTechnologies
EnrichmentLocal TIP store + historical alerts (PostgreSQL), commercial threat-intel & reputation APIs, WHOIS/RDAP, live browse, asset-search hybrid RAG
OSINT agentbrowser-use autonomous agent, LLM reasoning, structured-findings extraction, Laminar trace capture, semaphore-bounded concurrency
Verdict synthesisDSPy signature, LLM, secret-backed credentials (Infisical)
Concurrencyasyncio parallel fan-out, bounded semaphores, timeouts
Backend APIFastAPI (stateless JSON, no DB writes)

// Architecture & Diagrams

1 / 4System Architecture — Simple (high level)
rendering…

Disclaimer: sample visuals may contain anonymized, simulated, or non-production values for presentation purposes.

// Demo

No demo configured yet.