ThreatLens is an enterprise-grade Cyber Threat Intelligence (CTI) and automated binary forensics platform. Engineered to bridge static binary analysis with multi-vendor threat telemetry, ThreatLens delivers instant threat consensus and automated incident response SOPs for Tier-1 SOC analysts.
Aggregates multi-vendor intelligence queries and cryptographic hash signatures. Synthesizes detection ratios into a unified, weighted consensus score to eliminate false positives.
Calculates block-level Shannon entropy, maps PE section headers, and executes YARA pattern-matching rules to uncover packed code, anti-debugging routines, and process injection APIs.
Combines live cloud LLM queries with automated local fallback heuristics to generate executive risk briefings, potential impact assessments, and step-by-step SOC remediation SOPs.
ThreatLens relies on static entropy calculation, YARA heuristic evaluation, and multi-vendor consensus queries. While systematically validated across thousands of samples, dynamic binary variations or custom packed artifacts may occasionally yield slight result variations. In cybersecurity engineering, no single tool guarantees 100% absolute accuracy; output telemetry should serve to augment tier-1 SOC analytical verification.
ThreatLens accelerates threat containment by converting technical binary indicators into actionable security policies. From network C2 domain blocklists to endpoint isolation checklists, ThreatLens provides SOC engineering teams with immediate operational clarity.
Explore the automated 4-phase forensic pipeline and essential technical answers regarding binary inspection, entropy metrics, and incident response synthesis.
Submitted binaries are sanitized through an OWASP-Hardened Pipeline. Cryptographic digests (MD5, SHA-1, SHA-256) and exact file metadata are calculated in a single high-speed streaming pass.
Calculates Shannon Information Entropy across byte blocks to detect obfuscated payloads. Scans extracted ASCII/Unicode strings for high-risk execution keywords and API calls.
Queries SHA-256 digests against global threat databases aligned with the MITRE ATT&CK Framework to extract threat family signatures and multi-vendor detection ratios.
Our hybrid AI engine synthesizes technical binary indicators into executive risk briefings and actionable SOC Standard Operating Procedures aligned with NIST Cybersecurity Framework standards.
Essential answers regarding ThreatLens architecture, file boundaries, and forensic methodologies.
ThreatLens supports a wide range of binary formats including Windows Executables (.exe, .dll), Scripts (.py, .js, .bat), Documents (.pdf, .docx), and Archives (.zip, .apk). The maximum upload boundary is 200 MB per file, powered by streaming chunk inspection.
Shannon Entropy measures byte randomness on a scale from 0.0 to 8.0. Standard text or compiled code usually measures between 4.0 and 6.2. An entropy score exceeding 7.2 strongly indicates compressed, encrypted, or packed malware structures trying to evade static inspection.
YARA is an industry-standard rule engine used by malware researchers to classify threat families. ThreatLens scans PE section headers and byte sequences against compiled YARA heuristic rules to detect process injection APIs, anti-debugging routines, and ransomware encryption hooks.
The Threat Consensus Score (0 to 100) is calculated using a weighted multi-factor decision matrix combining multi-vendor antivirus detection ratios, static behavior weights, YARA heuristic severities, and entropy modifiers to minimize false positives.
The AI Security Advisor combines live cloud LLM reasoning with deterministic local fallback heuristics. It analyzes the specific threat verdict and indicator patterns to generate step-by-step SOC remediation SOPs, C2 domain blocklists, and endpoint containment protocols.
Student of Computer Engineering & Cybersecurity Researcher
Connect across official developer networks, engineering repositories, and threat research channels.
Pre-configured cryptographic digests, verification guidelines, and static inspection benchmark resources for evaluating ThreatLens consensus detection accuracy.
The File Analyzer accepts Windows Executables (.exe, .dll), Scripts (.py, .js, .bat), Documents (.pdf, .docx), and Archives (.zip, .apk) up to 200 MB. Below are pre-packaged hosted verification files deployed directly within the application codebase for instant click-to-analyze testing.
Test instant cryptographic hash reconnaissance without uploading physical binaries. Below are pre-configured 64-character SHA-256 signatures for safe utility benchmarks and known threat research samples.
Physical YARA test binaries are strictly isolated and not stored locally on the web server to uphold zero-trust infrastructure security. However, analysts can generate harmless test samples or evaluate rulesets using official security research frameworks below: