mirror of
https://github.com/SHOGGOTH-SECTOR/sica-fondt.git
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24f816b6a3
Place useful parts of the surrounding repos into sica-fondt by layer, per the
body model (Ada = membrane; brain/endocrine/capabilities/knowledge non-Ada):
- brain/ LLM reasoning + providers (dapr, hermes, MoMoA)
- capabilities/ REPRAG sidecars: hermes tools/skills, dapr tools, parallel
dispatch, A51 channels, and the OSINT cluster
- knowledge/ LORAG corpus: 754 cyber-skills, agency personas, secure-coding,
MITRE ATT&CK data
- reference/ defensive threat-reference (C3, shhbruh doc) + AdaYaml parser
License handling: AGPL sources (worldosint, advanced_evolution, mercury,
Reticulum) and GPL DeTTECT are SPEC-only clean-room/port descriptions — no
copyleft code copied. MIT/Apache/data parts copied as working trees.
Safety: shhbruh escape/persistence material and C3 covert-C2 kept as reference
only, not wired into the running organism. See CONSOLIDATION.md.
https://claude.ai/code/session_01UehUqEXXJJCsHoA4voCU5c
50 lines
1.4 KiB
Markdown
50 lines
1.4 KiB
Markdown
# API Reference: Hunting Credential Stuffing Attacks
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## Pandas Authentication Log Analysis
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```python
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import pandas as pd
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df = pd.read_csv("auth_logs.csv", parse_dates=["timestamp"])
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# Columns: timestamp, username, source_ip, status, user_agent
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# Failed logins per IP
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df[df["status"] == "failed"].groupby("source_ip")["username"].nunique()
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# Failed logins per account (distributed attack)
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df[df["status"] == "failed"].groupby("username")["source_ip"].nunique()
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# Login velocity (attempts per minute)
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df.set_index("timestamp").resample("1min").count()
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```
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## Detection Thresholds
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| Indicator | Threshold | Attack Type |
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|-----------|-----------|-------------|
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| Unique accounts per IP | > 20 | Credential stuffing |
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| Unique IPs per account | > 5 | Distributed attack |
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| Attempts/account ratio | ~1 | Password spray |
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| Success after N failures | N > 5 | Account compromise |
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| Single UA > 30% of failures | > 50 events | Automated tool |
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## Splunk SPL Patterns
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```spl
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--- Credential stuffing detection
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index=auth status=failed
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| stats dc(username) as accounts, count by src_ip
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| where accounts > 20
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--- Password spray detection
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index=auth status=failed
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| stats dc(username) as accounts, count by src_ip
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| where accounts > 10 AND count <= accounts * 3
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```
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### References
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- OWASP Credential Stuffing: https://owasp.org/www-community/attacks/Credential_stuffing
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- Splunk auth analysis: https://docs.splunk.com/Documentation/ES
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- pandas: https://pandas.pydata.org/docs/
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