AI-Powered Malware Analysis: From Hidden Phishing Attacks to Faster SOC Response 

A suspicious PDF opens normally. The link inside leads to a CAPTCHA page. Nothing obviously malicious appears, yet the real attack is still several steps away. 

For SOC analysts, cases like this can turn a routine phishing alert into a lengthy investigation. Following redirects, examining network activity, checking related infrastructure, and preparing evidence for escalation all take time. 

AI-assisted malware analysis is changing this workflow. By combining automated attack execution, interactive investigation, threat intelligence, and AI-generated reporting, security teams can reach malicious activity faster and spend more time examining what matters. 

Inside an AI-Assisted Investigation: Following the Full Attack Chain 

One of the biggest challenges in phishing analysis is getting beyond the initial lure. An attachment may contain no executable malware, while the actual threat remains hidden behind several browser interactions. 

A recent ANY.RUN sandbox investigation provides a practical example. 

The analysis started with a PDF hosted on the legitimate acrobat.adobe.com platform. Inside the document, an embedded link led to additional stages of the attack, including a CAPTCHA challenge. 

With ANY.RUN’s AI-assisted Automated Interactivity enabled, the sandbox continued through the chain automatically: 

1. Opened the PDF hosted on Adobe’s platform. 
2. Followed the URL embedded in the document. 
3. Navigated the subsequent browser interactions, including the CAPTCHA. 
4. Reached the Microsoft OAuth phishing flow and captured the resulting activity. 

The important part is what happens during execution. The sandbox continues recording behavioral and network evidence as the attack progresses, allowing analysts to examine suspicious URLs, connections, and other artifacts rather than relying only on the initial document. 

Automation also doesn’t mean losing control. Analysts can interact with the sandbox at any stage, inspect suspicious behavior, or explore another path without starting a separate investigation. 

This combination is especially useful when a phishing campaign depends on user interaction to reveal its malicious content. 

Uncover hidden attack chains faster with AI-assisted automation that handles complex interactions while keeping your analysts in control. Accelerate Threat Analysis with AI 

Beyond the Initial Alert: Finding Related Threat Infrastructure 

Reaching the phishing page confirms the immediate threat, but it doesn’t tell analysts how many other domains, URLs, or previous investigations may be connected to it. 

That requires threat intelligence correlation. 

ANY.RUN’s new Related Threat Context capability addresses this step by showing related sandbox analyses directly alongside suspicious indicators. Analysts can move from an individual finding to previous investigations without rebuilding the search manually. 

In the OAuth phishing investigation, the capability surfaced more than 70 related analyses. 

One domain, slybee[.]com, provided a useful starting point for deeper research. A pivot into ANY.RUN Threat Intelligence Lookup revealed: 

Investigation finding	Observed data
Related sandbox analyses	40
Associated IP addresses	8
Related URLs	29
Network connections	41
Threat classifications	oauth-ms-phish, skyw4lker

These findings connected the suspicious infrastructure to activity associated with the SkyW4lker phishing campaign. 

For analysts, the value is in what they can do next. The related indicators provide starting points for checking SIEM logs, EDR telemetry, proxy records, and DNS activity for signs that the same infrastructure has appeared elsewhere in the organization. 

A single phishing investigation can therefore support broader threat hunting and detection engineering, rather than ending with an isolated malicious verdict. 

From Raw Evidence to an Actionable Tier 1 Report 

Once malicious activity is confirmed, analysts still have another task: turning the investigation into something the rest of the SOC can use. 

A sandbox session may contain multiple URLs, network connections, behavioral indicators, and threat classifications. Reviewing this information and documenting the findings can take significant time, particularly when several cases are waiting in the queue. 

ANY.RUN’s SOC-ready Tier 1 report helps with this step by combining technical investigation evidence with two AI-generated components: 

• AI Summary: Explains the observed behavior, key findings, and potential threat impact. 
• AI Recommendations: Suggests investigation and response steps based on the evidence, including relevant technical checks and MITRE ATT&CK context where applicable. 

In the OAuth phishing case, analysts can use the generated report to understand the observed authentication-related activity, review supporting indicators, and identify what needs further investigation. 

The report does not replace analyst judgment. Recommendations still need to be checked against the sandbox evidence and the organization’s own security telemetry. 

However, it gives Tier 1 a documented starting point and provides Tier 2 with the information needed to continue an investigation without repeating every initial step. 

From AI-Assisted Investigations to Stronger SOC Detection 

Uncovering a phishing attack is valuable, but the intelligence behind it can help protect against future threats, too.

Malicious URLs, IP addresses, domains, and behavioral indicators collected during sandbox investigations can strengthen detection across an organization’s security infrastructure. 

ANY.RUN connects this intelligence to wider SOC operations through its Threat Intelligence Feeds, which deliver fresh, verified indicators collected from real-world malware and phishing investigations. 

Instead of relying on manual indicator collection, security teams can integrate these feeds into existing SIEM, SOAR, and threat intelligence platforms using STIX/TAXII or API/SDK connections. 

Here’s how this helps SOC teams: 

Capability	SOC benefit
Real-time IOC delivery	Keep detection systems updated with newly identified malicious infrastructure
SIEM and SOAR integration	Automatically enrich alerts with threat intelligence and support response workflows
Context-rich indicators	Connect suspicious activity to known threats and related sandbox evidence
Continuous intelligence updates	Improve detection coverage as new phishing and malware campaigns emerge

For analysts, this means fewer manual lookups and more context when investigating suspicious activity. For SOC leaders, it means getting more value from existing security investments, improving detection coverage, and reducing the risk of threats reaching corporate systems unnoticed.  

See How AI-Powered Malware Analysis Improves SOC Efficiency and Reduces Costs 

For SOC leaders, improving security performance while keeping costs under control is a constant challenge.

AI-powered malware analysis offers a practical way to handle more investigations with existing resources, reduce repetitive work, and respond to threats before they turn into costly incidents. 

According to customer results reported by ANY.RUN, improved investigation workflows have delivered measurable benefits: 

SOC Performance Metric	Reported Improvement
Mean time to respond (MTTR)	21 minutes less per incident
Tier 1 investigation workload	Up to 20% reduction
Tier 1-to-Tier 2 escalations	30% fewer
Threats identified	Up to 58% more

The Adobe phishing investigation shows how these capabilities work together: automated interactions expose hidden threats, connected intelligence reveals related attack activity, and AI-generated reports help analysts reach decisions faster. 

For organizations looking to improve SOC performance without continuously expanding their teams, AI-assisted analysis offers a way to make better use of existing security investments while reducing the risk and financial impact of cyberattacks. 

Reduce SOC costs, cut investigation time, and handle more threats without increasing headcount with AI-powered malware analysis. Boost SOC Efficiency with AI 

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