Our review
Extracts, deduplicates, validates, and classifies Indicators of Compromise (IOCs) from evidence files, logs, or pasted text, outputting structured reports.
Strengths
- Extracts a wide range of IOC types including IPs, domains, hashes, registry keys, and MITRE/CVE IDs.
- Automatically filters false positives like private IPs and benign domains.
- Supports defanged IOC re-fanging and deduplication.
- Generates a structured Markdown report for easy analysis.
Limitations
- Requires evidence to be in text-based format; does not parse binary files directly.
- Heuristics for false positive filtering may occasionally miss or over-filter.
- Context enrichment is limited to simple occurrence counting and positional hints.
Use when you need to quickly extract all observable IOCs from raw evidence during incident response.
Do not use for automated triage or as a standalone detection system; it's a manual analysis aid.
Security analysis
SafeThe skill uses only safe Bash commands for text processing and file reading/writing. There are no network calls, destructive operations, or execution of arbitrary code. It does not exfiltrate data; all output stays local.
No concerns found
Examples
Extract all Indicators of Compromise from the PCAP file at /home/analyst/evidence/capture.pcapI need to extract IOCs from this log file: /var/log/auth.log. Please parse it and output a structured report.Here is a suspicious email body. Extract all IOCs from it: <paste the text here>name: ioc-extract description: Extract, deduplicate, and classify Indicators of Compromise (IOCs) from any evidence source — files, logs, memory dumps, PCAPs, reports, or pasted text. Outputs structured IOC lists in multiple formats. argument-hint: <path-to-evidence-or-paste-text> allowed-tools: Bash Read Write Grep Glob
IOC Extraction
You are extracting and classifying Indicators of Compromise from evidence. Parse all provided material, extract IOCs, deduplicate, validate, and output in structured formats.
Target
Evidence source: $ARGUMENTS
If no file path is provided, the user may paste raw text containing IOCs directly. In that case, analyze the pasted content.
Extraction Procedure
Step 1: Determine Source Type
file <target> 2>/dev/null || echo "Text input mode — analyzing pasted content"
Step 2: Extract IOCs by Category
IPv4 Addresses
grep -oE "([0-9]{1,3}\.){3}[0-9]{1,3}" <source> | sort -u | while read ip; do
# Filter out RFC1918 private ranges, localhost, broadcast
echo "$ip" | grep -vE "^(10\.|172\.(1[6-9]|2[0-9]|3[01])\.|192\.168\.|127\.|0\.|255\.)" || true
done | sort -u
IPv6 Addresses
grep -oiE "([0-9a-f]{1,4}:){2,7}[0-9a-f]{1,4}" <source> | sort -u
Domains
grep -oiE "[a-z0-9]([a-z0-9-]{0,61}[a-z0-9])?\.[a-z]{2,}" <source> | sort -u | grep -viE "\.(png|jpg|gif|css|js|ico|svg|woff)$"
URLs
grep -oiE "https?://[^ \"'<>]+" <source> | sort -u
Email Addresses
grep -oiE "[a-z0-9._%+-]+@[a-z0-9.-]+\.[a-z]{2,}" <source> | sort -u
File Hashes
# MD5
grep -oiE "\b[a-f0-9]{32}\b" <source> | sort -u
# SHA1
grep -oiE "\b[a-f0-9]{40}\b" <source> | sort -u
# SHA256
grep -oiE "\b[a-f0-9]{64}\b" <source> | sort -u
File Names / Paths
grep -oiE "[a-z0-9_.-]+\.(exe|dll|ps1|bat|cmd|vbs|js|hta|scr|pif|msi|doc[xm]?|xls[xm]?|ppt[xm]?|pdf|jar|py|sh|elf|bin|iso|img|vhd)" <source> | sort -u
Registry Keys (Windows)
grep -oiE "HKEY_[A-Z_]+\\\\[^ \"']+" <source> | sort -u
MITRE ATT&CK Technique IDs
grep -oE "T[0-9]{4}(\.[0-9]{3})?" <source> | sort -u
CVE IDs
grep -oiE "CVE-[0-9]{4}-[0-9]{4,}" <source> | sort -u
User Agents
grep -oiE "Mozilla/[^ ]+ \([^)]+\)[^\"]*" <source> | sort -u | head -20
JA3/JA3S Hashes
# These are MD5-length but in specific context
grep -oiE "ja3[s]?=[a-f0-9]{32}" <source> | sort -u
Step 3: Validation & Deduplication
For each extracted IOC category:
- Deduplicate: Remove exact duplicates
- Defang check: Handle defanged IOCs (e.g.,
hxxp://,[.]com,[:]80)# Re-fang common defanging patterns for analysis sed -e 's/hxxp/http/gi' -e 's/\[.\]/./g' -e 's/\[:\]/:/g' -e 's/ dot /./gi' - False positive filtering:
- Remove private/reserved IPs (10.x, 172.16-31.x, 192.168.x, 127.x)
- Remove common benign domains (microsoft.com, google.com, etc.) — unless contextually relevant
- Remove hash-like strings that are clearly not hashes (e.g., CSS color codes in context)
- Validate format: Ensure IPs have valid octets (0-255), domains have valid TLD, hashes are correct length
Step 4: Enrichment (if possible)
For high-priority IOCs, note context:
- Where in the evidence was this IOC found?
- How many times does it appear?
- Is it associated with a specific process, user, or timeframe?
Output Formats
Format 1: Structured Report (default)
Write to ./reports/ioc-extract-report.md:
# IOC Extraction Report
**Date**: <date>
**Source**: <evidence source>
**Analyst**: Claude Code DFIR
## Summary
- **Total unique IOCs**: <count>
- **Categories**: <list>
## IOCs by Category
### Network Indicators
#### IP Addresses (<count>)
| IP | Occurrences | Context |
|----|-------------|---------|
#### Domains (<count>)
| Domain | Occurrences | Context |
|--------|-------------|---------|
#### URLs (<count>)
| URL | Context |
|-----|---------|
### Host Indicators
#### File Hashes
| Hash Type | Hash | Associated Filename |
|-----------|------|---------------------|
#### File Names
| Filename | Context |
|----------|---------|
#### Registry Keys
| Key | Context |
|-----|---------|
### Email Addresses
| Email | Context |
|-------|---------|
### Threat Intel References
| CVE | MITRE ATT&CK | Context |
|-----|---------------|---------|
Format 2: CSV (for SIEM import)
Also write to ./reports/iocs.csv:
type,value,context,source
Format 3: STIX-compatible JSON (simplified)
Also write to ./reports/iocs.json:
{
"type": "bundle",
"objects": [
{
"type": "indicator",
"pattern": "[ipv4-addr:value = 'x.x.x.x']",
"valid_from": "<date>",
"description": "<context>"
}
]
}
Create the reports/ directory if it does not exist. Generate all three output formats.
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