Malware analysis involves looking at malicious software to understand its functionality, origin, and potential impact. Security teams use different malware analysis techniques to peek under the hood of suspicious files, decide their threat level, and plan an appropriate response.

The analysis process may include code examination, behavior monitoring, and tracing the threat's footprint across affected systems. Some methods give you a quick heads-up, while others read the malware’s diary cover to cover.

Key benefits of malware analysis include determining the full scope of an intrusion, identifying the culprit (or at least their digital fingerprints), assessing the attack's sophistication, and pinpointing the exact vulnerability the malware exploited. 

There are three primary types of malware analysis: static, dynamic, and behavioral. 

Static analysis looks at malicious files without executing them. Analysts inspect the file structure, code, and embedded data to identify potential threats and determine basic functionality. It's fast, processing thousands of suspicious files in minutes.

What static analysis reveals

Security teams typically examine:

• File headers and metadata: When someone created, compiled, or last modified the file, providing timeline context.

• Embedded strings: Hardcoded text, URLs, IP addresses, or file paths that indicate the malware's purpose and command-and-control infrastructure.

• Import tables and functions: Which system capabilities or libraries does the malware attempt to access?

• Code structure: How the malware organizes itself and what libraries or functions it references.

• Hash values: Unique file signatures that analysts compare against threat intelligence databases.

Advantages and limitations

Static analysis is great at quick triage. It identifies known malware signatures and obvious indicators of compromise. But most modern malware comes with encryption, packing, or obfuscation. Essentially, malware says, “Nice try, static analysis, but not today.” Static analysis alone won’t tell you what the malware does at runtime.

Dynamic analysis runs suspicious files in a controlled environment (a sandbox) and observes their behavior. It’s like giving malware a tiny, safe playground to show off and throw tantrums, but not do any damage, while you take notes. Be warned, though: sophisticated malware sometimes knows it's being watched and plays nice just to fool you.

The sandbox environment

Proper sandboxes isolate malware from production systems while providing realistic execution conditions. As the malware executes, analysts monitor:

• Network traffic: Connection attempts, data exfiltration, and command-and-control communications.

• File system changes: Files the malware creates, modifies, or deletes, including dropped payloads.

• Registry modifications: Persistence mechanisms and system configuration changes.

• Process activity: Additional processes the malware spawns or code the malware injects into legitimate processes.

• Memory operations: How the malware manipulates system memory to hide itself or steal sensitive data.

Real-world impact assessment

Behavioral analysis watches what malware does, not what it says it does. It doesn’t care how the malware is built or its code structure. The only thing that matters is what it does. 

Action-based detection

Behavioral analysis identifies suspicious patterns like:

• Encryption of user files: This indicates potential ransomware activity.

• Credential scraping: From memory or password managers.

• Process injection: Into legitimate system processes to hide malicious activity.

• Defense evasion techniques: Disabling security tools or clearing event logs.

• Command-and-control communication patterns: Indicating that the malware receives instructions from threat actors.

• Privilege escalation attempts: Aiming to gain administrator access.

• Data staging operations: Where the malware collects and prepares files for exfiltration.

Detecting evasion tactics

Behavioral analysis shines against polymorphic malware and variants that evade signature-based detection. 

It also correlates system logs and contextual data, so a single suspicious action isn’t judged alone. Security teams can leverage SIEM platforms to aggregate and analyze these behavioral patterns across their entire environment, because it’s the patterns that tell the real story.

While malware analysis is about techniques, the malware itself usually spans a wide range of categories, each with distinct behaviors and infection vectors:

• Viruses: Self-replicating code that attaches to other files.

• Worms: Self-propagating malware that spreads across networks without user interaction.

• Trojans: Malicious programs masquerading as legitimate software.

• Ransomware: Encrypts data and demands payment for decryption.

• Infostealers: Harvest sensitive data like credentials, financial info, and session tokens.

• Keyloggers: Record keystrokes to capture passwords and other input.

• Downloaders: Deliver additional malware payloads after initial infection.

• Rootkits: Conceal malware or attacker activity deep within the OS.

Each type requires tailored analysis depending on behavior and infection vector.

Malware analysis improves security operations in a few ways:

• Developing detection rules: Analysis findings inform new signatures and behavioral detections.

• Improving incident response: Attack pattern understanding helps SOC teams respond faster and more effectively.

• Identifying entry vectors: Tracing how malware entered the environment helps prevent future infections.

• Exposing adversary infrastructure: Command-and-control servers and related indicators enable broader threat hunting.

• Informing cyber threat intelligence: Analysis contributes to the organization's overall understanding of threat actor TTPs (Tactics, Techniques, and Procedures) and campaign patterns.

The average security analyst takes 40 minutes to a few hours to analyze a single malware sample manually, and organizations receive hundreds of alerts daily. The maths simply doesn’t work. Huntress Managed EDR helps organizations act on these findings so your team can spend less time chasing malware and more time wondering how humans keep clicking suspicious links. 

If you want automated malware analysis with SOC oversight, let’s talk. Huntress Managed EDR gives deep visibility into endpoint behaviour, from static property inspection to behavioral correlation, identifying threats traditional tools miss. Huntress Managed SIEM correlates activity across your entire environment, connecting the dots between endpoints, users, and systems. Our SOC analysts verify findings, eliminate false positives, and provide actionable intelligence directly to your team.