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Introduction:
The proliferation of Child Sexual Abuse Material (CSAM) on the dark web presents a persistent and technically challenging problem for cybersecurity professionals and law enforcement. CIRCL’s new public onion lookup service provides a critical tool for automating the detection and filtering of these malicious Tor hidden services, shifting the paradigm from reactive analysis to proactive defense. This technical deep dive explores how to integrate this API into security operations, from threat intelligence platforms to custom Python scripts, enabling analysts to build scalable detection pipelines.
Learning Objectives:
- Integrate CIRCL’s CSAM Onion Lookup API into automated threat intelligence workflows.
- Implement bulk hash and URL checking scripts for proactive monitoring and defensive filtering.
- Configure the AIL Project to automatically reject crawling requests linked to known CSAM content.
You Should Know:
1. Direct API Lookup with cURL
`curl -s “https://hashlookup.circl.lu/onion-lookup/example.onion”`
This command performs a direct lookup against CIRCL’s service for a single onion address. The `-s` flag silences the progress meter for clean script integration. A successful query returns a JSON object; a `200` status indicates the address is clean, while a `404` suggests it is not found in the database. For addresses tagged as CSAM, the response will include the `dark-web:topic=”child-sexual-exploitation”` taxonomy tag, which can be parsed by security automation tools.
2. Bulk Onion Address Checking with Python
import requests
onion_list = ['example1.onion', 'example2.onion', 'example3.onion']
api_endpoint = "https://hashlookup.circl.lu/onion-lookup/"
for onion in onion_list:
response = requests.get(api_endpoint + onion)
if response.status_code == 404:
print(f"[!] CSAM MATCH: {onion}")
else:
print(f"[+] Clean: {onion}")
This Python script automates the process of checking a list of onion addresses. It iterates through each address in the onion_list, constructs the API call, and interprets the HTTP status code. A `404` response is the key indicator of a positive match for CSAM content, triggering an alert. This script can be integrated into a SIEM or orchestration platform for continuous monitoring.
3. Integrating Lookups into MISP for Threat Intelligence
Within a MISP (Malware Information Sharing Platform) event, analysts can use the `onion` object type to attribute indicators. The CIRCL API can be configured as an enrichment module. When a new onion address is ingested or created, MISP can automatically perform a lookup and tag the event with `dark-web:topic=”child-sexual-exploitation”` if a match is found. This enriches the intelligence value of the event and allows for automatic sharing with trusted communities under predefined distribution policies.
4. Filtering Crawls in the AIL Project (v6.1+)
AIL (Analysis Information Leak) is designed to crawl the clearnet and dark web for leaked information. To prevent the system from accidentally crawling CSAM content, administrators can enable the onion lookup filter.
Navigate to the AIL configuration file (configs/core.cfg) and ensure the following is set:
`
`</h2>
<h2 style="color: yellow;">`enable_lookup = True`</h2>
`url = https://hashlookup.circl.lu/onion-lookup/`
This configuration instructs AIL's crawler to query the CIRCL service before processing an onion URL. If the address is flagged, the crawl request is dropped, mitigating legal and ethical risks for the organization and its analysts.
<h2 style="color: yellow;">5. Building a Proactive HTTP Proxy Filter</h2>
For organizations monitoring network egress points, a transparent proxy can be configured to block requests to known malicious onion addresses. Using a lightweight Python script with the `http.server` and `socketserver` modules, you can create a filtering proxy that checks outgoing `.onion` requests against the API.
The core logic involves intercepting the HTTP `CONNECT` method, parsing the requested hostname, and performing a real-time lookup to the CIRCL API. If the lookup returns a <code>404</code>, the proxy immediately terminates the connection and logs the attempted access for further investigation, effectively blocking the request at the network boundary.
<h2 style="color: yellow;">6. Leveraging the API for YARA Rule Generation</h2>
The intelligence from the API can fuel deeper forensic hunting. Analysts can create YARA rules to scan for harvested onion addresses linked to CSAM within disk images or memory dumps.
[bash]
rule CSAM_Onion_Addresses {
meta:
description = "Hunt for known CSAM-related onion addresses"
author = "Your DFIR Team"
reference = "CIRCL Hashlookup API"
strings:
$onion1 = "csam123abc456def.onion" wide ascii
$onion2 = "exploit78ghi90jkl.onion" wide ascii
condition:
any of them
}
While the API provides dynamic intelligence, generating static YARA rules based on confirmed positive matches allows for offline, large-scale scanning operations during digital forensics and incident response (DFIR) investigations.
7. Automated Reporting with Bash and jq
For daily threat briefings, a Bash script can automate the collection and formatting of results.
!/bin/bash
Check a list of onions and output a formatted report
echo "CSAM Onion Check Report - $(date)" > report.txt
echo "=================================" >> report.txt
while read -r onion; do
status=$(curl -s -o /dev/null -w "%{http_code}" "https://hashlookup.circl.lu/onion-lookup/$onion")
if [ "$status" -eq 404 ]; then
echo "BLOCKED: $onion" >> report.txt
fi
done < "onions_to_check.txt"
This script reads a list of onions from a file (onions_to_check.txt), checks each one, and appends any positive matches to a timestamped report file. The `-o /dev/null` discards the response body, and `-w “%{http_code}”` extracts only the HTTP status code for efficient parsing, making it ideal for cron jobs and scheduled tasks.
What Undercode Say:
- The release of this API represents a significant pivot towards open, collaborative defense against the most abhorrent content online, filling a critical gap left by non-profit organizations that fail to share data.
- The technical implementation, offering both a simple RESTful API and direct integration into the AIL framework, lowers the barrier to entry for organizations to implement ethical and effective filtering, moving beyond mere blacklists to actionable intelligence.
This development is less about a single tool and more about the democratization of a critical defensive capability. By providing a free, public API, CIRCL is enabling a global network of defenders, from small NGOs to large enterprises, to participate in a collective shield. The technical design choices—using standard HTTP codes and open taxonomies—ensure maximum compatibility and ease of integration, which is often the biggest hurdle in operationalizing threat intelligence. The commitment to adopting Interpol’s Luxembourg Guidelines for terminology also sets a new standard for ethical and accurate classification in threat data sharing.
Prediction:
The technical approach pioneered by CIRCL will catalyze a new wave of automated, API-driven defenses against dark web threats. We predict this will lead to the development of standardized, interoperable APIs for sharing other types of malicious indicators (e.g., financier, malware-hosted) onion addresses, creating a more resilient and collaborative ecosystem. This model will likely be adopted and expanded by other organizations, leading to a decentralized but interconnected network of trust-based threat intelligence services that significantly increase the cost and difficulty for threat actors to operate on the dark web.
🎯Let’s Practice For Free:
IT/Security Reporter URL:
Reported By: Adulau Csam – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
