Zero-Day Behavioral Anomaly Detector
Pillar 6: Unsupervised MLDetects novel, unclassified malware variants via Isolation Forest, One-Class SVM & Deep Autoencoder Reconstruction Loss against 150,000+ clean-ware execution baselines.
1. Isolation Forest (Depth: 16)
98.2%outlier probability
Average isolation path length: 0.3 hops (baseline mean: 15.2)
2. One-Class SVM (RBF Kernel)
96.8%margin divergence
Distance from clean hypersphere: +7.94σ
3. Deep Autoencoder Loss
97.9%L2 loss spike
Bottleneck Latent Loss (MSE): 0.289 (Clean mean: 0.003)
Unsupervised Ensemble Model Weight Rebalancing & Feature Sensitivity
Normalizing weights: w₁(35%) + w₂(30%) + w₃(35%) = 100%Isolation Forest Weight35%
One-Class SVM Weight30%
Deep Autoencoder Weight35%
X-AXIS:
Y-AXIS:
← Clean Baseline Cluster (Low Reconstruction Loss)Extreme Behavioral Outliers (Novel EDR Bypass Vectors) →
Active Sample Inspection
Novel-RustLoader-X09.exe
Novel Rust Direct-Syscall LoaderTop Novel Anomaly Vectors:
Direct Kernel Syscalls (SSN Hook Bypass)+840% (6.42σ)
Observed: 47 raw SYSENTER/SYSCALL opcodes bypassing EDR hooks
Complete avoidance of user-mode hooks; classic zero-day loader characteristic.
Unbacked Executable Memory Allocations (RWX)+620% (5.18σ)
Observed: 3 unbacked RWX pages (total 1.2 MB) allocated in heap
Shellcode staging in non-image backed memory space.
Anomalous N-gram API Sequence Entropy+430% (4.89σ)
Observed: 0.89 (Randomized indirect call jumps)
Polymorphic control flow flattening designed to break static graph analyzers.
Thread Stack Spoofing & Synthetic Frames+510% (4.74σ)
Observed: Fake return addresses pointing into kernel32.dll export offsets
Stack-walking EDR bypass.
Autonomous Heuristic Forge
Generate instant zero-day behavioral YARA/Sigma rules targeting these unsupervised feature anomalies.