GlassEye BBP/VDP v1 (LoRA)
GlassEye ? authorized HackerOne Bug Bounty (BBP) / Vulnerability Disclosure (VDP) assistant.
Training
- Base:
mistralai/Mistral-7B-Instruct-v0.3 - Init: Hancock pentest v4 LoRA (detection-leaning)
- Data:
glasseye_bbp_v1.jsonl(~3740 samples) ? scope, reporting, severity, ethical web methodology - Steps: 300 | train_loss ? 0.24 | QLoRA
- Hardware: glasseye NVIDIA RTX 5070 only (no cloud GPUs)
Intended use
In-scope HackerOne program workflows: policy/scope, report writing, severity rationale, remediation. Not for unauthorized testing or exploit dump recipes.
Load
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
base = "mistralai/Mistral-7B-Instruct-v0.3"
tok = AutoTokenizer.from_pretrained(base)
model = AutoModelForCausalLM.from_pretrained(base, torch_dtype=torch.bfloat16, device_map="auto")
model = PeftModel.from_pretrained(model, "cyberviser/glasseye-bbp-v1")
Owner: Johnny Watters (0ai-Cyberviser) / 0AI / GLASSEYE
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Model tree for cyberviser/glasseye-bbp-v1
Base model
mistralai/Mistral-7B-v0.3 Finetuned
mistralai/Mistral-7B-Instruct-v0.3