Update CyberForge ML models and deployment artifacts

README.md

@@ -19,10 +19,10 @@ Production-ready machine learning models for cybersecurity threat detection.
 
 | Model | Task | Accuracy | F1 Score | Inference Time |
 |-------|------|----------|----------|----------------|
-| phishing_detection | random_forest | 0.9890 | 0.9890 | 0.01ms |
+| phishing_detection | random_forest | 0.9890 | 0.9890 | 0.02ms |
 | malware_detection | gradient_boosting | 0.9985 | 0.9985 | 0.00ms |
 | anomaly_detection | random_forest | 0.9990 | 0.9990 | 0.01ms |
-| web_attack_detection | random_forest | 1.0000 | 1.0000 | 0.03ms |
+| web_attack_detection | random_forest | 1.0000 | 1.0000 | 0.04ms |
 
 
 ## Usage

anomaly_detection/metadata.json

@@ -3,7 +3,7 @@
   "dataset": "anomaly_detection",
   "accuracy": 0.999,
   "f1_score": 0.9989986620975891,
-  "inference_time_ms": 0.006589841842651367,
+  "inference_time_ms": 0.006771755218505859,
   "feature_names": [
     "timestamp",
     "event_id",

anomaly_detection/package_info.json

@@ -4,7 +4,7 @@
   "version": "1.0.0",
   "accuracy": 0.999,
   "f1_score": 0.9989986620975891,
-  "inference_time_ms": 0.006589841842651367,
+  "inference_time_ms": 0.006771755218505859,
   "files": {
     "model": {
       "path": "anomaly_detection/model.pkl",
@@ -19,5 +19,5 @@
       "path": "anomaly_detection/metadata.json"
     }
   },
-  "packaged_at": "2026-02-15 19:21:08"
+  "packaged_at": "2026-02-23 01:55:27"
 }

malware_detection/metadata.json

@@ -3,7 +3,7 @@
   "dataset": "malware_detection",
   "accuracy": 0.9985,
   "f1_score": 0.9984999996249999,
-  "inference_time_ms": 0.0010334253311157227,
+  "inference_time_ms": 0.001075148582458496,
   "feature_names": [
     "file_size",
     "entropy",

malware_detection/package_info.json

@@ -4,7 +4,7 @@
   "version": "1.0.0",
   "accuracy": 0.9985,
   "f1_score": 0.9984999996249999,
-  "inference_time_ms": 0.0010334253311157227,
+  "inference_time_ms": 0.001075148582458496,
   "files": {
     "model": {
       "path": "malware_detection/model.pkl",
@@ -19,5 +19,5 @@
       "path": "malware_detection/metadata.json"
     }
   },
-  "packaged_at": "2026-02-15 19:21:08"
+  "packaged_at": "2026-02-23 01:55:27"
 }

manifest.json

@@ -6,7 +6,7 @@
       "version": "1.0.0",
       "accuracy": 0.9889857732905002,
       "f1_score": 0.9889844643474395,
-      "inference_time_ms": 0.010500483799549678,
+      "inference_time_ms": 0.015778189243773572,
       "files": {
         "model": {
           "path": "phishing_detection/model.pkl",
@@ -21,7 +21,7 @@
           "path": "phishing_detection/metadata.json"
         }
       },
-      "packaged_at": "2026-02-15 19:21:08"
+      "packaged_at": "2026-02-23 01:55:27"
     },
     "malware_detection": {
       "name": "malware_detection",
@@ -29,7 +29,7 @@
       "version": "1.0.0",
       "accuracy": 0.9985,
       "f1_score": 0.9984999996249999,
-      "inference_time_ms": 0.0010334253311157227,
+      "inference_time_ms": 0.001075148582458496,
       "files": {
         "model": {
           "path": "malware_detection/model.pkl",
@@ -44,7 +44,7 @@
           "path": "malware_detection/metadata.json"
         }
       },
-      "packaged_at": "2026-02-15 19:21:08"
+      "packaged_at": "2026-02-23 01:55:27"
     },
     "anomaly_detection": {
       "name": "anomaly_detection",
@@ -52,7 +52,7 @@
       "version": "1.0.0",
       "accuracy": 0.999,
       "f1_score": 0.9989986620975891,
-      "inference_time_ms": 0.006589841842651367,
+      "inference_time_ms": 0.006771755218505859,
       "files": {
         "model": {
           "path": "anomaly_detection/model.pkl",
@@ -67,7 +67,7 @@
           "path": "anomaly_detection/metadata.json"
         }
       },
-      "packaged_at": "2026-02-15 19:21:08"
+      "packaged_at": "2026-02-23 01:55:27"
     },
     "web_attack_detection": {
       "name": "web_attack_detection",
@@ -75,7 +75,7 @@
       "version": "1.0.0",
       "accuracy": 1.0,
       "f1_score": 1.0,
-      "inference_time_ms": 0.02898440998830613,
+      "inference_time_ms": 0.04354221805645402,
       "files": {
         "model": {
           "path": "web_attack_detection/model.pkl",
@@ -90,9 +90,9 @@
           "path": "web_attack_detection/metadata.json"
         }
       },
-      "packaged_at": "2026-02-15 19:21:08"
+      "packaged_at": "2026-02-23 01:55:27"
     }
   },
   "version": "1.0.0",
-  "created_at": "2026-02-15 19:21:08"
+  "created_at": "2026-02-23 01:55:27"
 }

phishing_detection/metadata.json

@@ -3,7 +3,7 @@
   "dataset": "phishing_detection",
   "accuracy": 0.9889857732905002,
   "f1_score": 0.9889844643474395,
-  "inference_time_ms": 0.010500483799549678,
+  "inference_time_ms": 0.015778189243773572,
   "feature_names": [
     "num_dots",
     "subdomain_level",

phishing_detection/package_info.json

@@ -4,7 +4,7 @@
   "version": "1.0.0",
   "accuracy": 0.9889857732905002,
   "f1_score": 0.9889844643474395,
-  "inference_time_ms": 0.010500483799549678,
+  "inference_time_ms": 0.015778189243773572,
   "files": {
     "model": {
       "path": "phishing_detection/model.pkl",
@@ -19,5 +19,5 @@
       "path": "phishing_detection/metadata.json"
     }
   },
-  "packaged_at": "2026-02-15 19:21:08"
+  "packaged_at": "2026-02-23 01:55:27"
 }

web_attack_detection/metadata.json

@@ -3,7 +3,7 @@
   "dataset": "web_attack_detection",
   "accuracy": 1.0,
   "f1_score": 1.0,
-  "inference_time_ms": 0.02898440998830613,
+  "inference_time_ms": 0.04354221805645402,
   "feature_names": [
     "response_code",
     "is_attack",

web_attack_detection/package_info.json

@@ -4,7 +4,7 @@
   "version": "1.0.0",
   "accuracy": 1.0,
   "f1_score": 1.0,
-  "inference_time_ms": 0.02898440998830613,
+  "inference_time_ms": 0.04354221805645402,
   "files": {
     "model": {
       "path": "web_attack_detection/model.pkl",
@@ -19,5 +19,5 @@
       "path": "web_attack_detection/metadata.json"
     }
   },
-  "packaged_at": "2026-02-15 19:21:08"
+  "packaged_at": "2026-02-23 01:55:27"
 }