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Beacon Hunter

Detecting Non-Periodic Structured C2 via Additive Recurrence

Beacon Hunter detects command-and-control beaconing that uses phi-compatible additive recurrence scheduling — a growing, non-periodic timing pattern where each inter-connection interval approximately equals the sum of the previous two. This family evades regularity-based detectors (RITA, AC-Hunter) by design, while remaining structurally identifiable via a two-gate recurrence test.

"A beacon does not need to be periodic to be structured."


Quick Start

Pipeline

Beacon Hunter two-gate pipeline: Gate 1 filters by phi-ratio clustering, Gate 2 tests additive recurrence structure.

pip install -r requirements.txt

# Run on a Zeek conn.log
python beacon_hunter.py /path/to/conn.log

# Reproduce all paper results
python run_full_evaluation.py --quick    # ~2 min, skips full evidence suite
python run_full_evaluation.py           # ~5 min, full pipeline

# Run unit tests
pytest tests/

# End-to-end validation (verifies paper claims)
python validate.py

How It Works

Beacon Hunter is a two-gate pipeline operating on Zeek connection logs.

Gate 1 — Ratio Test
Groups connections from the same source/destination pair and computes consecutive inter-connection interval (ICI) ratios. Passes if the mean ratio is near phi (φ = 1.618) within ±0.20 and ratio variability (CV) is below 0.50. Minimum: 5 intervals.

Gate 2 — Additive Recurrence Test
Tests whether ICI[n+2] ≈ ICI[n+1] + ICI[n] holds across all consecutive triples, using mean relative error against a 500-iteration permutation null. Passes if mean error < 0.20 and p < 0.05. This gate rejects power-law growth (residual 0.40) and exponential backoff (0.56) which pass Gate 1 by coincidence.

Classification labels

Label Meaning
ADDITIVE_RECURRENCE_BEACON Both gates pass — phi-compatible growing-interval schedule
JITTERED_BEACON Periodic with jitter — passes ratio gate, fails recurrence
REGULAR_BEACON Constant-interval beacon
BACKGROUND No beaconing structure detected
INSUFFICIENT_DATA Fewer than 5 intervals

Acceptance envelope: geometric ratios in [1.45, 1.80], confirmed empirically via boundary sweep.


Architecture

beacon_hunter_github/
├── beacon_hunter.py          # CLI detector — entry point
├── detectors.py              # Pure stateless gate functions (556 lines)
├── validate.py               # 32-check end-to-end validation
├── run_full_evaluation.py    # One-command reproduction pipeline
├── requirements.txt          # Pinned dependencies
├── evidence/
│   ├── evidence_suite.py     # All 6 evaluation batteries (Experiments A-J)
│   ├── rita_comparison.py    # RITA-style periodicity baseline + real RITA comparison
│   ├── roc_and_ci.py         # ROC curve (AUC=0.900) + Wilson CI
│   ├── generate_figures.py   # Figures 1-7 (PNG + PDF)
│   └── *.json                # Pre-computed results
├── data/
│   ├── pcaps/                # Ground-truth PCAPs (see Dataset Notes below)
│   └── zeek/                 # Zeek conn.log files
├── figures/                  # fig1-fig8 PNG + PDF (sequential)
├── paper/                    # Full paper with appendices A-G
├── reports/                  # Beacon Hunter output reports + real RITA v5.1.2 output
├── tests/
│   └── test_detectors.py     # 34 unit tests (34/34 pass)
├── tools/
│   ├── fib_beacon_client.py  # Fibonacci beacon traffic generator
│   ├── fib_beacon_server.py
│   └── uwf_to_connlog.py     # UWF-ZeekData22 parquet → Zeek conn.log converter
└── archive/                  # Deprecated scripts (legacy_detectors.py, old scanners)

Evidence Pipeline

Script Experiments Output
evidence/evidence_suite.py A (synthetic), B (lab PCAP), C (AC jitter), E (adversarial battery), F (jitter sweep), G (length sensitivity), H (null distribution), I (phi boundary), J (logistic map) evidence_results.json
evidence/roc_and_ci.py G.5 (ROC, AUC=0.900), G (Wilson CI [0.992, 1.000]) roc_results.json
evidence/rita_comparison.py D (RITA-style baseline comparison) rita_comparison_results.json
evidence/generate_figures.py Figures 1-7 figures/fig*.png/pdf

Dataset Notes

File Type Description
data/pcaps/fib_beacon_validation.pcapng Ground truth Lab-generated Fibonacci beacon PCAP; used in Experiment B
data/pcaps/jit_var_d30_j0_1h.pcap Ground truth 30s constant beacon, 0% jitter, 1 hour
data/pcaps/jit_var_d30_j10_1h.pcap Ground truth 30s beacon, 10% jitter, 1 hour
data/pcaps/jit_var_d30_j99_1h.pcap Ground truth 30s beacon, 99% jitter (pure noise), 1 hour
data/zeek/delay_var_d30_j25_combined.log Real + injected 2-hour enterprise Zeek conn.log with injected 30s+25%jitter beacon
data/zeek/delay_var_d30_j25_24h_combined.log Real + injected 24-hour version of above
reports/rita_output_v5.1.2_24h.txt Real RITA output Actual RITA v5.1.2 binary output on the 24h dataset (100 flows scored)

For UWF-ZeekData22 evaluation: download from https://datasets.uwf.edu/data/ and convert using tools/uwf_to_connlog.py.


Key Results

Experiment Result
Synthetic detection (Exp A) 3/3 beacon classes correct, 0 FP
Lab PCAP (Exp B) ADDITIVE_RECURRENCE_BEACON, rec_err=0.000, p<0.002
Jitter sweep (Exp F) 100% detection through 20% jitter; cliff at 30%
Power law vs exp backoff (Exp E) Residuals 0.40 and 0.56 > threshold 0.20; correctly rejected
ROC AUC (Exp G.5) 0.900; TPR=1.000 at FPR=0.071
Real RITA v5.1.2 on jittered beacon 0.617 Low severity (both tools detect; different classification)
UWF-ZeekData22 (1M flows, benign) 0/12,083 analyzed flows flagged ARB — 0.00% FPR
Logistic map battery (Exp J) Pure logistic: 0% detection; phi-biased ≤20% noise: 100%
Phi boundary sweep (Exp I) Acceptance window [1.45, 1.80] confirmed

Operational Validation

These results are from running Beacon Hunter against real enterprise traffic:

Real RITA v5.1.2 comparison (reports/rita_output_v5.1.2_24h.txt):
Both tools detect the 30-second jittered periodic beacon. RITA scores it 0.617 Low severity among 50 other Critical/High alerts. Beacon Hunter classifies it JITTERED_BEACON. A pure additive recurrence schedule scores below 0.35 in RITA — analytically proved in Appendix A, empirically confirmed.

UWF-ZeekData22 (1 million real enterprise connections):
0/12,083 analyzed flows flagged as ADDITIVE_RECURRENCE_BEACON on the benign week. 0/1,995 on the Recon/Discovery attack week (correct — port scans are not beaconing). All 4 injected Fibonacci beacons detected at 0–25% jitter.

24-hour enterprise Zeek background:
1/243 analyzed flows flagged — IPv6 NDP at 34% analyst triage heuristic, marginal and protocol-attributable.


Reproduction

See EXPECTED_RESULTS.md for the exact numerical outputs expected.

# Quick verification of all paper claims:
python validate.py

# Full pipeline (generates all outputs from scratch):
python run_full_evaluation.py

# Expected: 32/32 validation checks pass, ROC AUC=0.900, jitter 20%=100% detection

Limitations

  • No confirmed real-world malware using phi-compatible scheduling (threat model is theoretical)
  • False positive rate characterized on two real datasets; enterprise-scale multi-week evaluation remains future work
  • Detection surface is narrow by design — the detector targets one structural timing family

Citation

If you use this work, please cite the accompanying paper:

Cordero, A. (2026). Detecting Non-Periodic Structured C2 Beaconing via Additive Recurrence. RepoSignal.io LLC. https://doi.org/10.5281/zenodo.20431555

DOI


License

AGPL-3.0. See LICENSE.

Commercial licensing available through RepoSignal.io LLC.

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Detects phi-structured C2 beacons that evade RITA and standard regularity-based detectors

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