Revolutionary High-Performance Security Frameworks
The world's most comprehensive security toolkit written in Julia
The Julia Security Suite is a collection of five revolutionary security frameworks that leverage Julia's high-performance computing capabilities for security research, vulnerability discovery, threat intelligence, and adversarial machine learning.
- ⚡ Performance: Near-C speed with Python-like syntax
- 🧮 Scientific Computing: Built-in support for ML, statistics, and numerical analysis
- 📦 Package Ecosystem: Rich libraries for networking, cryptography, and data processing
- 🔧 Metaprogramming: Powerful macros for domain-specific security languages
- 🔄 Interoperability: Easy integration with C, Python, and R libraries
| Tool | Description | Lines | Status |
|---|---|---|---|
| 🌈 Spectra | High-performance security toolkit with 25+ analyzers | 8,000+ | ✅ Stable |
| 🔮 Oracle | AI-powered vulnerability discovery engine | 11,000+ | ✅ Stable |
| 👻 Phantom | Zero-knowledge proof security framework | 6,300+ | ✅ Stable |
| 🌀 Vortex | Real-time threat intelligence fusion | 8,400+ | ✅ Stable |
| 🎭 Mirage | Adversarial ML security toolkit | 7,000+ | ✅ Stable |
High-Performance Security Toolkit
Spectra is the foundation of the Julia Security Suite, providing core analyzers and utilities that other tools build upon.
- 📊 25+ Security Analyzers: Binary, network, crypto, memory, web, and more
- 🔌 NullSec Integration: Seamless integration with NullSec Linux tools
- 🧩 Extensible Architecture: Plugin system for custom analyzers
- 📈 Performance Metrics: Built-in benchmarking and profiling
- 🎨 Beautiful Output: Rich terminal formatting and reports
using Spectra
# Create analyzer suite
suite = AnalyzerSuite()
# Run comprehensive scan
results = analyze(suite, "target_binary")
# Generate report
report = generate_report(results, format=:markdown)Repository: github.com/bad-antics/spectra
AI-Powered Vulnerability Discovery Engine
Oracle uses machine learning models to predict vulnerabilities before they're exploited, analyzing code patterns across multiple languages.
- 🧠 ML Models: RandomForest, GradientBoosted, Neural Network predictors
- 🔍 15+ Analyzers: Buffer overflow, injection, crypto, deserialization, race conditions
- 📚 300+ Patterns: Comprehensive vulnerability pattern database
- 🎯 MITRE Integration: CWE/CAPEC mapping for all findings
- 🌐 Multi-Language: C, C++, Java, Python, JavaScript, PHP, Ruby, Go, Rust
using Oracle
# Initialize prediction engine
engine = create_oracle_engine(model=:neural)
# Scan codebase
vulnerabilities = scan_codebase(engine, "src/")
# Get predictions with confidence scores
for vuln in vulnerabilities
println("$(vuln.type): $(vuln.location) - Confidence: $(vuln.confidence)")
println(" CWE: $(vuln.cwe_id) | Severity: $(vuln.predicted_severity)")
end
# Generate detailed report
report = generate_vulnerability_report(vulnerabilities)Repository: github.com/bad-antics/oracle
Zero-Knowledge Proof Security Framework
Phantom enables proving security claims without revealing sensitive details - perfect for responsible disclosure and bug bounty programs.
- 🔐 ZK-SNARK Implementation: Full circuit compilation and proving
- 📝 Pedersen Commitments: Cryptographic commitments for vulnerability details
- 💍 Ring Signatures: Anonymous proof generation
- 🏆 Bounty System: Privacy-preserving reward claims
- ⛓️ Blockchain Anchoring: Ethereum, Bitcoin, Polygon support
using Phantom
# Create a vulnerability proof
vuln = Vulnerability(
type=:sql_injection,
severity=:critical,
location="auth.php:127"
)
# Generate ZK proof (proves vuln exists without revealing details)
proof = generate_proof(vuln)
# Verifier can confirm without seeing vulnerability details
is_valid = verify_proof(proof) # true
# Anonymous disclosure
disclosure = create_disclosure(
proof,
timeline=DisclosureTimeline(days=90),
anonymous=true
)Repository: github.com/bad-antics/phantom
Real-time Threat Intelligence Fusion Engine
Vortex aggregates and correlates indicators of compromise from 50+ threat feeds, providing actionable intelligence with ML-powered analysis.
- 📡 50+ Threat Feeds: OTX, Abuse.ch, MISP, VirusTotal, Shodan, and more
- 🔗 19 IOC Types: IP, Domain, URL, Hashes, CVE, JA3, Bitcoin, YARA
- 🧮 ML Clustering: Automatic threat grouping and classification
- 🎯 Threat Hunting: Predefined queries for C2, ransomware, APT
- 📤 Export Formats: STIX 2.1, MISP, Snort, Suricata, YARA, Sigma
using Vortex
# Create threat intel engine
engine = create_vortex_engine()
# Add feeds
add_feed!(engine, urlhaus_feed())
add_feed!(engine, alienvault_otx_feed("API_KEY"))
add_feed!(engine, spamhaus_drop_feed())
# Start real-time processing
start!(engine)
# Search for IOC
results = search_ioc(engine, "192.168.1.100")
# Threat hunting
hunt_result = threat_hunt(engine, hunt_c2_infrastructure())
# Export to STIX
stix_bundle = export_stix(collect(values(engine.iocs)))Repository: github.com/bad-antics/vortex
Adversarial Machine Learning Toolkit
Mirage provides tools for testing ML model robustness against adversarial attacks, including evasion, poisoning, and model extraction.
- 🎯 Evasion Attacks: FGSM, PGD, C&W, DeepFool, and more
- ☠️ Poisoning Attacks: Data poisoning, backdoor insertion
- 🔓 Model Extraction: Black-box model stealing
- 🛡️ Defense Evaluation: Robustness testing and certification
- 📊 Comprehensive Metrics: Attack success rate, perturbation analysis
using Mirage
# Load target model
model = load_model("classifier.onnx")
# Create attack suite
attacks = AttackSuite([
FGSM(epsilon=0.1),
PGD(epsilon=0.1, steps=40),
CarliniWagner(confidence=0.9)
])
# Evaluate robustness
results = evaluate_robustness(model, test_data, attacks)
# Generate adversarial examples
adv_examples = generate_adversarial(model, samples, attack=:pgd)
# Test defenses
defense = AdversarialTraining(model, attack_budget=0.1)
robust_model = train_robust(defense, training_data)Repository: github.com/bad-antics/mirage
- Julia 1.10 or later
- Git
using Pkg
# Add the NullSec registry (optional, for easier updates)
Pkg.Registry.add(RegistrySpec(url="https://github.com/bad-antics/JuliaSecurityRegistry"))
# Install individual packages
Pkg.add(url="https://github.com/bad-antics/spectra")
Pkg.add(url="https://github.com/bad-antics/oracle")
Pkg.add(url="https://github.com/bad-antics/phantom")
Pkg.add(url="https://github.com/bad-antics/vortex")
Pkg.add(url="https://github.com/bad-antics/mirage")julia -e '
using Pkg
for repo in ["spectra", "oracle", "phantom", "vortex", "mirage"]
Pkg.add(url="https://github.com/bad-antics/$repo")
end
'- Vulnerability Scanning Pipeline
- Threat Intelligence Workflow
- Anonymous Bug Bounty Submission
- ML Model Security Audit
All tools are pre-installed in NullSec Linux v4.2.0+:
# Launch Julia security REPL
nullsec-julia
# Or use individual tools
nullsec oracle scan ./target
nullsec vortex hunt c2
nullsec phantom prove vuln.jsonfrom julia import Spectra, Oracle, Vortex
# Use Julia tools from Python
results = Oracle.scan_codebase("src/")
intel = Vortex.search_ioc("8.8.8.8")# GitHub Actions
- name: Security Scan
run: |
julia -e '
using Oracle
vulns = scan_codebase("src/")
exit(length(vulns) > 0 ? 1 : 0)
'| Metric | Value |
|---|---|
| Total Lines of Code | 40,000+ |
| Total Files | 90+ |
| Supported Languages | 9 (for Oracle) |
| Threat Feeds | 50+ (for Vortex) |
| IOC Types | 19 (for Vortex) |
| Attack Methods | 15+ (for Mirage) |
| Vulnerability Patterns | 300+ (for Oracle) |
These tools are intended for authorized security testing and educational purposes only.
- Always obtain proper authorization before testing
- Follow responsible disclosure practices
- Respect privacy and data protection laws
- Report vulnerabilities through proper channels
All tools in the Julia Security Suite are released under the MIT License.
- The Julia community for an amazing language
- Security researchers worldwide for inspiration
- Open source threat intelligence providers
- The NullSec community
Julia Security Suite - High-performance security for the modern era
Part of the bad-antics security ecosystem
| Project | Description | Docs |
|---|---|---|
| NullSec Linux | Security-focused Linux distribution with 135+ tools | 📖 Docs |
| Marshall Browser | Privacy-focused browser with Tor integration | 📖 Docs |
| NullKia | Mobile security framework in 12 languages | 📖 Docs |
| BlackFlag ECU | Automotive security and ECU diagnostics | 📖 Docs |
| NullSec Tools | Multi-language penetration testing toolkit | 📖 Docs |
- NullSec Linux Download
- Marshall Browser Download
- NullKia Installation
- BlackFlag ECU Suite
- NullSec Tools Collection
Documentation maintained by bad-antics | All tools for authorized security testing only