Malware is evolving faster than ever, leveraging obfuscation, packing, and sandbox evasion techniques to slip past traditional defenses. In today’s environment, relying on a single method of malware analysis—whether static, dynamic, or AI—is no longer enough. To truly stay ahead, organizations need a comprehensive, layered approach that analyzes every angle of a threat.
That’s exactly what CodeHunter delivers.
Static Analysis: Foundational Insight Without Execution
Static analysis inspects files without running them, examining code structure, metadata, headers, strings, and embedded content. This method is incredibly fast and lightweight, and it’s ideal for identifying known signatures, suspicious functions, or obfuscation techniques.
Static analysis also helps identify sequencing patterns—examining how code is constructed rather than just what behaviors it exhibits. However, it can fall short when dealing with encrypted or polymorphic malware that hides its true intent until runtime.
Dynamic Analysis: Behavior in Action
To catch what static analysis can’t see, dynamic analysis comes into play. By executing suspicious files in a secure, sandboxed environment, dynamic analysis monitors real-time behaviors like registry edits, network communications, and file system changes.
This allows CodeHunter to reveal the actual intent of the file—whether it’s privilege escalation, data exfiltration, or lateral movement. Dynamic analysis is especially powerful for identifying threats that use runtime-only tactics or obfuscated delivery methods. While resource-intensive, it’s crucial for observing evasive malware in action.
AI-Powered Analysis: Smarter, Scalable Threat Identification
CodeHunter enhances both static and dynamic analysis with machine learning. Its AI models identify malicious behavior patterns, even in zero-day or previously unknown files. These models continuously learn from new data, improving accuracy over time and scaling to handle thousands of files quickly.
AI analysis isn’t reliant on known signatures and can identify subtle anomalies across large datasets—but its effectiveness is amplified when it’s fed rich context from both static and dynamic layers.
Why Combine All Three?
Individually, static, dynamic, and AI analysis each provide valuable perspectives. But when combined into a single workflow, they deliver highly accurate verdicts, faster. That’s CodeHunter’s strength.
By correlating static indicators, runtime behaviors, and machine-learned patterns, CodeHunter ensures:
- Broader identification of evasive threats
- Accelerated triage and threat prioritization
Whether you're hunting zero-day malware, investigating post-breach activity, or proactively scanning unknown files in your environment, CodeHunter equips your team with deep visibility and context that no single method alone can provide.
The CodeHunter Solution
Sophisticated threats demand sophisticated defenses. CodeHunter’s multi-layered malware analysis platform brings together the best of static, dynamic, and AI-powered techniques to deliver superior protection. Learn how CodeHunter can keep your SOC team one step ahead of complex and unknown threats here.
