You can deploy this model and start earning money today!

sreejanjalagam/
gate2-security-reviewer

Name: gate2-security-reviewer
Availability: InStock

Views

No views yet

Semantic Firewall - Gate 2: Logic Intent Scanner

LLM-powered PR security reviewer that catches authentication bypass vulnerabilities that unit tests miss.

Mission

Every PR opened by an AI agent passes through Gate 2. The system analyzes the full git diff for security logic changes.

Core Actions

analyze_diff - Pattern pre-filter + LLM deep analysis
generate_adversarial_tests - Exploit test generation with phantom-validation detection
trigger_war_room - Auto-convene on score >= 7
allow_pr - Merge gate after resolution
shadow_deploy - Isolated validation environment

Demo: Beat 5

PR diff removes requiresAuth() from /admin/users:

diff

-  requiresAuth(),
   async (req, res) => {

Gate 2 scores: 8/10 -> "Authentication bypass: endpoint /admin/users now returns data to unauthenticated callers."

Threshold 7 crossed -> War Room auto-convened with security-lead, identity-team, CTO.

Detection Rate

Metric	Before	After Training
Auth bypass caught	~5%	~70%+
War Room triggered	--	Auto on score >=7
False positive rate	--	~14%

Reward Breakdown

Action	Reward
Auth bypass caught	+70
War Room triggered	+60
Score < threshold (correct clear)	+40
False War Room call	-20

Failure Modes Guarded Against

LLM returns non-JSON -> parse fallback scores 5/10, War Room not triggered
Context window too small -> diff truncation preserves removed lines
Adversarial tests phantom validation -> explicit phantom risk annotation per test

Files

gate2_security_reviewer/analyzer.py - Core diff analysis & LLM pipeline
gate2_security_reviewer/war_room.py - War Room orchestration
gate2_security_reviewer/adversarial.py - Adversarial test generation
gate2_security_reviewer/training.py - Synthetic data & training pipeline
gate2_security_reviewer/evaluator.py - Novel pattern evaluation
app.py - Gradio demo interface
demo_beat5.py - Standalone Beat 5 demo
training_data.jsonl - 1,200 synthetic training examples

Usage

python

from gate2_security_reviewer.analyzer import DiffAnalyzer
from gate2_security_reviewer.war_room import WarRoomOrchestrator

analyzer = DiffAnalyzer()
review = analyzer.analyze_diff(diff_text, pr_id="PR-1042")

war_room = WarRoomOrchestrator(threshold=7)
event = war_room.evaluate(review)

Citation

Based on:

OpenVul (2026): SFT->GRPO pipeline for vulnerability detection
SWE-PRBench (2026): LLM-as-judge for PR diff review
VulInstruct (2025): Specification-guided reasoning

sreejanjalagam/gate2-security-reviewer