A multi-layer secrets detection system using regex patterns, fine-tuned BERT, and LLM verification.

• Blog Post: What's Your Secret?: Secret Scanning by DeepPass2
• Model: Deeppass2-xlm-roberta

DeepPass2 combines regex rules, a fine-tuned BERT model, and LLM validation to detect both structured tokens and context-dependent free-form passwords in documents. It improves accuracy and reduces false positives by leveraging contextual understanding and a multi-tiered architecture.

Multi-tier architecture: NoseyParker → BERT → LLM validation

pip install -r requirements.txt

• deeppass2.py - Main application
• utils/BERTprocessor.py - BERT token classification
• utils/nprules.py - Async regex checking
• regexRules.jsonl - Regex patterns from Nosey Parker (one pattern per line)
• Fine-tuned model at path/to/merged-model - Request model access from the Huggingface - Huggingface

Create .env file:

LITELLM_API_KEY=<YOUR LITE LLM API KEY>
LITELLM_BASE_URL=<YOUR CUSTOM LITELLM BASE URL LINK>
AUGMENT_MODEL=<MODEL NAME>
hf_token=<YOUR HF TOKEN>
DEEPPASS2=<HOST LINK>

python deeppass2.py

Server starts on http://localhost:5000

curl -X POST http://localhost:5000/api/deeppass2 \
  -H "Content-Type: text/plain" \
  --data-binary "@document.txt"

BERT-based token classification identifies passwords using contextual understanding

1. Nosey Parker: Regex pattern matching (based on Nosey Parker rules)
2. Document Cleaning: Remove regex matches to reduce false positives
3. Chunking: Split document into BERT-compatible chunks (300-400 tokens)
4. BERT Classification: Identify potential credentials using fine-tuned xlm-RoBERTa-base
5. LLM Verification: Confirm if detected tokens are actual secrets

• Strict Accuracy: 86.67% (BERT) / 85.79% (LLM)
• Overlap Accuracy: 97.72% (BERT) / 95.35% (LLM)

Edit line 35 in deeppass2.py:

model_name = "your-model-path"  # Local path or HuggingFace model ID

Replace lines 60-64 with your LLM client:

# Example: Direct OpenAI
import openai
openai.api_key = "your-key"

# Then modify get_secrets_LLM() function to use openai.ChatCompletion.create()

Edit chunk_document() call parameters:

chunks = chunk_document(doc_np_cleaned, tokenizer, 
                       max_len=512,      # Maximum tokens per chunk
                       min_len=300,      # Minimum tokens per chunk
                       overlap_ratio=0.1) # Overlap between chunks

Keep in mind that the BERT model is trained on these min and max lengths. Changing these could hamper the performance of the tool.

Modify lines 40-48 to force specific device:

device = "cuda"  # Force CUDA
# device = "mps"   # Force Apple Silicon
# device = "cpu"   # Force CPU

Add patterns to regexRules.jsonl:

{"name": "AWS Key", "id": "aws_1", "pattern": "AKIA[0-9A-Z]{16}"}
{"name": "GitHub Token", "id": "gh_1", "pattern": "ghp_[a-zA-Z0-9]{36}"}

Edit get_prompt() function:

def get_prompt(text, passwords):
    prompt = f"""Your custom prompt here
    Credentials: {passwords}
    Context: {text}
    """
    return prompt

Keep in mind that this might affect the performance of the tool.

Last line of deeppass2.py:

app.run(port=8080, debug=False)  # Change port and disable debug

DeepPass2 returns detected passwords with surrounding context for human review

{
  "Success": [
    {"Nosey Parker": [...]},
    {"BERT_secrets": [...]},
    {"LLM_scanning": [...]}
  ]
}

• Nosey Parker: Secret detection regex patterns adapted from Praetorian's Nosey Parker
• DeepPass (2022): Original character-level BiLSTM approach by Will Schroeder - Finding Passwords with Deep Learning

If you use DeepPass2 in your research or work, please cite:

@software{gupta2025deeppass2,
  author = {Gupta, Neeraj},
  title = {DeepPass2: Multi-layer Secrets Detection System},
  year = {2025},
  month = {7},
  organization = {SpecterOps},
  url = {https://github.com/SpecterOps/DeepPass2},
  note = {Blog post: \url{https://specterops.io/blog/2025/07/31/whats-your-secret-secret-scanning-by-deeppass2/}}
}

Gupta, N. (2025). DeepPass2: Multi-layer secrets detection system [Computer software]. SpecterOps. 
https://specterops.io/blog/2025/07/31/whats-your-secret-secret-scanning-by-deeppass2/

Gupta, Neeraj. "DeepPass2: Multi-layer Secrets Detection System." SpecterOps, 31 July 2025, 
specterops.io/blog/2025/07/31/whats-your-secret-secret-scanning-by-deeppass2/.

N. Gupta, "DeepPass2: Multi-layer Secrets Detection System," SpecterOps, Jul. 2025. 
[Online]. Available: https://specterops.io/blog/2025/07/31/whats-your-secret-secret-scanning-by-deeppass2/