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Omega-Suite — Lyrie.ai's autonomous binary analysis and exploit research engine

Project description

Lyrie OMEGA — Autonomous Security Intelligence Platform

Lyrie.ai | OTT Cybersecurity LLC
Proprietary & Confidential — All Rights Reserved


Overview

Lyrie OMEGA is the autonomous offensive/defensive security research core of the Lyrie.ai platform. It powers the HEX Scanner, Lyrie Intel, and the full exploit feasibility pipeline — delivering world-class binary analysis, forensic investigation, and vulnerability validation capabilities.

This suite is a proprietary Lyrie.ai product. All components are developed and owned by OTT Cybersecurity LLC / Lyrie.ai.


Components

Agent Fleet + Expert Personas

17 agentsagents/

Agent Purpose Lyrie Product
crash-analysis-agent Orchestrates full C/C++ crash triage Lyrie HEX Scanner
crash-analyzer-agent Deep root-cause analysis with rr Lyrie HEX Scanner
crash-analyzer-checker-agent Validates crash analyses rigorously Lyrie HEX Scanner
coverage-analysis-generator-agent gcov coverage data generation Lyrie HEX Scanner
function-trace-generator-agent Function execution tracing Lyrie HEX Scanner
exploitability-validator-agent Multi-stage exploitability pipeline Lyrie Core Engine
offsec-specialist Offensive security operations agent Lyrie OMEGA
oss-evidence-verifier-agent Forensic evidence verification Lyrie Intel
oss-hypothesis-checker-agent Hypothesis validation Lyrie Intel
oss-hypothesis-former-agent Evidence-backed hypothesis formation Lyrie Intel
oss-investigator-gh-archive-agent GH Archive BigQuery forensics Lyrie Intel
oss-investigator-github-agent GitHub API + commit recovery Lyrie Intel
oss-investigator-ioc-extractor-agent IOC extraction from vendor reports Lyrie Intel
oss-investigator-local-git-agent Local git repository forensics Lyrie Intel
oss-investigator-wayback-agent Wayback Machine content recovery Lyrie Intel
oss-report-generator-agent Final forensic report generation Lyrie Intel

10 expert personaspersonas/

Persona Use Case
security_researcher Deep vulnerability validation
exploit_developer Working PoC generation
crash_analyst Binary crash + exploitability analysis
patch_engineer Production-ready secure patches
penetration_tester Web payload generation
fuzzing_strategist AFL++ strategy optimization
binary_exploitation_specialist Binary exploit code generation
codeql_analyst CodeQL dataflow path validation
codeql_finding_analyst CodeQL finding exploitability assessment
offensive_security_researcher Mitigation bypass feasibility

Exploit Feasibility Engine

50+ filespackages/

Component Files Purpose
packages/exploit_feasibility/ 36 Binary mitigation analysis, exploitation path scoring
packages/exploitability_validation/ 12 Multi-stage validation pipeline (Stages 0-E)
packages/cvss/ 4 CVSS scoring utilities
core/smt_solver/ 8 SMT-based constraint solving (z3) for one-gadget feasibility

Key API:

from packages.exploit_feasibility import analyze_binary, format_analysis_summary
result = analyze_binary('/path/to/binary')
print(format_analysis_summary(result, verbose=True))

Lyrie Intel — OSS Forensics

40+ filesskills/lyrie-intel/

Lyrie Intel is Lyrie's autonomous forensic investigation engine.

Component Purpose
skills/lyrie-intel/github-archive/ GH Archive BigQuery skill
skills/lyrie-intel/github-evidence-kit/ Evidence collection, storage, and verification
skills/lyrie-intel/github-commit-recovery/ Recover "deleted" git commits
skills/lyrie-intel/github-wayback-recovery/ Recover content from Wayback Machine
skills/lyrie-intel/orchestration/ Multi-agent orchestration skill
commands/oss-forensics.md Command definition for lyrie-intel command

Invocation: /lyrie-intel <research-question> [--max-followups 3]


Lyrie HEX Scanner Enhancement

60+ filesskills/code-understanding/, packages/static-analysis/, packages/codeql/, engine/

Component Files Purpose
skills/code-understanding/ 5 skills Code comprehension and attack surface mapping
packages/static-analysis/ 3 Semgrep integration
packages/codeql/ 16 CodeQL database management + analysis
engine/semgrep/ 30+ Semgrep rules (crypto, injection, secrets, auth)
engine/codeql/ 1 CodeQL suite definitions

Quick Start

1. Install dependencies

pip3 install -r requirements.txt

2. Set environment variable

export LYRIE_DIR=/path/to/lyrie-omega-suite

3. Run exploit feasibility analysis

import sys, os
sys.path.insert(0, os.environ["LYRIE_DIR"])

from packages.exploit_feasibility import analyze_binary, format_analysis_summary

result = analyze_binary('/path/to/binary')
print(format_analysis_summary(result, verbose=True))

4. Use Lyrie Intel for forensics

/lyrie-intel "Investigate suspicious commits in owner/repo between July 10-15 2025"

5. Run code understanding

/understand /path/to/target --map
/understand /path/to/target --trace main
/understand /path/to/target --hunt "unsanitized user input"

Architecture

lyrie-omega-suite/
├── OMEGA-BRAIN.md          ← System prompt for Lyrie OMEGA autonomous mode
├── README.md               ← This file
├── ARCHITECTURE.md         ← Detailed component architecture
├── requirements.txt        ← Python dependencies
├── agents/                 ← 17 Lyrie OMEGA agents
│   ├── crash-analysis-agent.md
│   ├── exploitability-validator-agent.md
│   ├── offsec-specialist.md
│   └── oss-*/...
├── personas/               ← 10 expert personas
│   ├── security_researcher.md
│   ├── exploit_developer.md
│   └── ...
├── packages/               ← Python analysis packages
│   ├── exploit_feasibility/
│   ├── exploitability_validation/
│   ├── cvss/
│   ├── static-analysis/
│   └── codeql/
├── core/
│   └── smt_solver/         ← SMT constraint solving
├── skills/
│   ├── lyrie-intel/        ← OSS Forensics (Lyrie Intel)
│   └── code-understanding/ ← Code comprehension skills
├── commands/
│   └── oss-forensics.md    ← Lyrie Intel command
└── engine/
    ├── semgrep/            ← Semgrep rules + SARIF tools
    └── codeql/             ← CodeQL suites

License

Copyright 2026 OTT Cybersecurity LLC / Lyrie.ai. All rights reserved.
Proprietary and confidential. Unauthorized use, reproduction, or distribution is strictly prohibited.

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