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mukul975
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Complete skill folder anatomy across all cybersecurity skills: - scripts/agent.py: 80-150 line Python agents using real libraries (impacket, boto3, azure-mgmt-*, kubernetes, pefile, yara, scapy, shodan, stix2, etc.) - references/api-reference.md: real API documentation with method signatures - LICENSE: MIT license for all skill folders
65 lines
1.5 KiB
Markdown
65 lines
1.5 KiB
Markdown
# API Reference: Detecting DNS Exfiltration
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## Shannon Entropy Calculation
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```python
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import math
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from collections import Counter
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def entropy(text):
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freq = Counter(text)
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length = len(text)
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return -sum((c/length) * math.log2(c/length) for c in freq.values())
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# Normal subdomain: entropy ~2.5-3.0
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# Encoded data: entropy >3.5-4.0
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```
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## Detection Thresholds
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| Metric | Normal | Suspicious |
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|--------|--------|------------|
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| Subdomain entropy | < 3.0 | > 3.5 |
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| Subdomain length | < 20 chars | > 40 chars |
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| TXT record ratio | < 5% | > 30% |
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| Queries to single domain | < 50/hr | > 100/hr |
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## Zeek dns.log Fields
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```
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#fields ts uid id.orig_h id.orig_p id.resp_h id.resp_p proto trans_id
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query qclass qclass_name qtype qtype_name rcode rcode_name
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```
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## DNS Tunneling Tools
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| Tool | Protocol | Indicators |
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|------|----------|------------|
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| iodine | TXT/NULL/CNAME | Encoded subdomains, high volume |
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| dnscat2 | TXT/CNAME | Base32/Base64 subdomains |
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| dns2tcp | TXT | Long TXT responses |
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## Splunk SPL Detection
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```spl
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index=dns
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| eval subdomain=replace(query, "\.[^.]+\.[^.]+$", "")
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| eval entropy=...
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| where len(subdomain) > 40 AND query_count > 100
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| stats count by query, src_ip
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```
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## Suricata DNS Rules
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```
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alert dns any any -> any 53 (msg:"DNS Tunnel - Long Query"; \
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dns.query; content:"."; offset:50; sid:2000001;)
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```
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## CLI Usage
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```bash
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python agent.py --dns-log dns.log --format zeek
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python agent.py --dns-log dns.log --entropy-threshold 3.8 --length-threshold 50
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```
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