Valh4x

Hunting Lazarus Part IV: Real Blood on the Wire It has been only days since we published Part III—where we asked whether we were hunting Lazarus or walking into a honeypot. We did not expect to be back this soon. But what we found makes everything ...

oh, we didn't expect that...

redasgard.com/blog/hunting...

what are your thoughts?

#lazarus #dprk #threatintelligence #malwareanalysis #ottercookie

#ContagiousInterview #Lazarus #DPRK #CTI

Hunting Lazarus Part III: The Infrastructure That Was Too Perfect We discovered a second malware family, mapped approximately 20 ghost servers with consistent configurations, attempted to exploit the C2 infrastructure—and ended up questioning whether we were hunting...

oh, that's weird. here's the link: redasgard.com/blog/hunting...

Hunting Lazarus Part III: The Infrastructure That Was Too Perfect We discovered a second malware family, mapped approximately 20 ghost servers with consistent configurations, attempted to exploit the C2 infrastructure—and ended up questioning whether we were hunting...

oh, that's weird. here's the link: redasgard.com/blog/hunting...

for those who waited long...

redasgard.com/blog/hunting-l…

We discovered a second malware family, mapped approximately 20 ghost servers with consistent configurations, attempted to exploit the C2 infrastructure – and ended up questioning whether we were hunting them, or they were hunting us...

The AI Red Team Maturity Model: A Capability-Based Framework for LLM Security Testing Most organizations testing their AI systems are doing it wrong. This five-level maturity framework provides structure for understanding where you are, what capabilities you need next, and how much it ...

Interesting take on modern security challenges: "The AI Red Team Maturity Model: A Capability-Based Framework for LLM Security Testing"

Originally published on Red Asgard: redasgard.com/blog/ai-red-...

#llm #ai #redteam #aisecurity #framework
#securitytesting

The End of Syntax Privilege: Why LLMs Are Just the Latest Compiler For most of software engineering history, the hardest skill was translating intent into correct syntax. Syntax mastery became a proxy for competence itself. Large language models quietly break that as...

Great read on cybersecurity insights: "The End of Syntax Privilege: Why LLMs Are Just the Latest Compiler"

Originally published on Red Asgard: redasgard.com/blog/end-of-...

#ai #llm #softwaredevelopment #softwareengineering #programming

Balancer exploited today — over $117M drained.
Root cause: vault-level auth flaw (WITHDRAW_INTERNAL) allowing unauthorized withdrawals.
Composability amplifies failure.
“Audited” ≠ “secure.”
#DeFi #Balancer #Web3Security

4️⃣ Why It Matters
AI security ≠ traditional cybersecurity.
The attack surface is language itself — intent, context, and semantics.
llm-security helps developers bridge that gap before LLMs reach production scale.

Defense starts with awareness.
#AISecurity #LLM #PromptSecurity #Rust

— Valh4x

3️⃣ Usage Example

let security = LLMSecurityLayer::new(LLMSecurityConfig::default());

// Sanitize before sending to LLM
let safe_code = security.sanitize_code_for_llm(user_code)?;

// Validate LLM response
security.validate_llm_output(llm_response)?;

Protect your AI from manipulation. 🔐
#RustCode

2️⃣ The Solution
llm-security protects both input and output channels.

✅ 90+ detection patterns
✅ Jailbreak prevention
✅ Unicode sanitization
✅ Output validation
✅ Semantic cloaking detection
✅ Secure prompt generation

Integrate directly with your Rust AI pipelines
#LLMSecurity #Protection #Rust #AI

1️⃣ The Problem
LLMs can be tricked, manipulated, or socially engineered.
Common exploits include:
• “Ignore previous instructions” injections
• Jailbreak prompts (DAN, STAN, etc.)
• Persuasive social engineering
• Output poisoning or malicious instructions

#PromptInjection #Jailbreaking #AISecurity

crates.io: Rust Package Registry

🚀 Released llm-security v0.1.0 🦀🤖
The first Rust library for LLM security — protects against 90+ prompt injections, jailbreaks, and semantic cloaking.

✅ Output validation · Unicode defense · Secure prompt gen

📦 crates.io/crates/llm-s...

#Rust #AI #LLMSecurity #AISecurity #OpenSource

3️⃣ Usage Example

let mut engine = ThreatIntelEngine::new(ThreatIntelConfig::default());
engine.initialize().await?;

let vulns = engine.query_vulnerabilities("apache", "2.4").await?;
let assessment = engine.assess_risk(&vulns);

Unify your threat intelligence
#Security #ThreatIntelligence

— Valh4x

2️⃣ The Solution
Unified access to threat data —
✅ Multi-source aggregation
✅ 4 authentication modes
✅ Retry with exponential backoff
✅ Risk assessment & failure isolation
✅ Capability-based queries

Reliable intel from one interface.
#ThreatIntel #Rust #Automation

1️⃣ The Problem
Threat intel aggregation is messy — multiple sources, formats, and auth schemes.
JSON, XML, STIX, TAXII… every feed looks different, updates at different times, and breaks your parser.

threat-intel unifies this chaos.
#ThreatIntel #RustLang #CyberSecurity

crates.io: Rust Package Registry

🚀 Released threat-intel v0.1.0 🦀🎯
Rust framework for multi-source threat intel — unified access to MITRE ATT&CK, CVE, Abuse.ch.

✅ 4 auth modes · risk assessment · retry + failure isolation · capability-based queries

📦 crates.io/crates/threa...

#Rust #Security #ThreatIntelligence #OpenSource

3️⃣ Usage Example

use path_security::validate_path;
let safe = validate_path(user_input, base_dir)?;

Blocks encoding, Unicode, and NTFS tricks before they bite. 🔐

— Valh4x

2️⃣ The Solution
path-security neutralizes all known traversal techniques.
Zero dependencies (only anyhow), production-tested, cross-platform.

Perfect for web uploads, archives, and git operations.
#RustLang #CrossPlatform #ProductionReady

1️⃣ The Problem
Most validators just block ../, missing dozens of bypasses:
• %2e%2e%2f, %252e%252e%252f
• UTF-8 overlong bytes
• Unicode homoglyphs (․․/)
• NTFS alternate data streams

#AttackVectors #Unicode #Windows #SecurityResearch

crates.io: Rust Package Registry

🚀 Released path-security v0.2.0 🦀🛡️
Rust library for a path validation - protects against 62+ traversal techniques used in real-world exploits.

✅ URL & UTF-8 overlong encoding
✅ Unicode homoglyphs / zero-width tricks
✅ NTFS streams, UNC paths
✅ 95.81% test coverage

📦 crates.io/crates/path-security

3️⃣ Quick start

let shield = QuantumShield::new();
let (pub, priv) = shield.generate_keypair().await?;
let encrypted = shield.encrypt_hybrid(&data, &pub).await?;

Stay ahead of the curve. ⚡

— Valh4x

2️⃣ Built for the real world
6+ months in production.
Zero unnecessary deps.
Memory-safe, auto-zeroized, cross-platform.
Works on blockchain, IoT, and air-gapped systems.

1️⃣ Why it matters
RSA and ECDSA won’t survive quantum decryption.
quantum-shield uses Kyber (KEM) + Dilithium (signatures) with hybrid encryption — classical + quantum strength.

crates.io: Rust Package Registry

🚀 Dropped quantum-shield v0.1.0 — a Rust 🦀 library bringing post-quantum cryptography (Kyber, Dilithium) to production.

✅ Hybrid RSA + PQ
✅ Zeroized memory
✅ no_std compatible
✅ Optional async

Future-proof crypto before quantum breaks RSA.
🔗 crates.io/crates/quantum-shield