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Estimative language empowers CTI (Cyber Threat Intelligence) analysts to be more clear, precise, and transparent in their reporting. Here are six steps to start using it today!
1️⃣ Understand the Standard Descriptors
Familiarize yourself with the key probability terms, confidence levels, and qualitative descriptors used to describe how certain you are about an assessment.
2️⃣ Choose the Type of Descriptor
Choose the estimative language you use based on the assessment you are making. If you are assessing the likelihood of an event occurring, use a probability term. If you are evaluating the quality and reliability of the information supporting your assessment, use a level of confidence.
3️⃣ Provide Context and Justification
Explain how you reached a probability or confidence level using a qualitative descriptor. This descriptor can provide context (e.g., based on THIS evidence) or justification (e.g., based on X amount of corroborating evidence). You can use facts, corroborating evidence, or statistical estimates to explain how you came to your conclusions.
4️⃣ Be Clear and Concise
Separate the facts and evidence in your assessments from your judgments and conclusions. You want to avoid ambiguous terms and ensure your report is straightforward and easy to understand.
5️⃣ Tailor the Language to the Audience
Not all intelligence consumers are the same. You must tailor the language you use in your assessment to the audience consuming it. This is fundamental to disseminating threat intelligence and ensuring decision-makers find it valuable.
6️⃣ Review, Revise, and Educate
Estimative language should be fluid and change as new information becomes available. If you can scale your moderate confidence assessment to a high-level one because new evidence comes in, you should (and you should let others know about it).
🔗 Reference: Kraven Security – Estimative Language
You Should Know:
Practical Commands & Tools for CTI Analysts
1. Threat Intelligence Gathering (Linux/CLI Tools)
- WHOIS Lookup:
whois example.com
- DNS Enumeration:
dig example.com ANY nslookup -query=ANY example.com
- IP Reputation Check:
curl -s https://www.abuseipdb.com/check/[IP_ADDRESS]
2. Log Analysis with Linux Commands
- Extract Suspicious IPs from Logs:
grep -E -o "([0-9]{1,3}.){3}[0-9]{1,3}" /var/log/auth.log | sort | uniq -c | sort -nr - Monitor Live Logs:
tail -f /var/log/syslog
3. Automating CTI Reports with Python
- Fetch Threat Feeds:
import requests response = requests.get("https://otx.alienvault.com/api/v1/pulses/subscribed") print(response.json())
4. Windows Threat Hunting (PowerShell)
- Check Suspicious Processes:
Get-Process | Where-Object { $_.CPU -gt 90 } - Analyze Network Connections:
netstat -ano | findstr "ESTABLISHED"
5. Confidence Scoring in CTI (Bash Script)
!/bin/bash confidence_level="High" if [[ $confidence_level == "High" ]]; then echo "This assessment is highly reliable." else echo "Further verification needed." fi
What Undercode Say:
Estimative language is crucial in CTI to ensure clarity and actionable insights. By integrating structured probability terms and confidence levels, analysts enhance decision-making for security teams. Automation through scripting (Bash/Python) and log analysis strengthens intelligence validation. Continuous refinement of assessments ensures accuracy in dynamic threat landscapes.
Expected Output:
A well-structured CTI report with estimative language, supported by automated threat validation scripts and log analysis commands.
🔗 Further Reading: Kraven Security – Estimative Language
References:
Reported By: Adamgoss1 Cti – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
