In an ideal world, security teams would be able to prevent phishing emails from getting to an employee’s inbox. But in the modern world, that simply isn’t feasible.
Phishing emails themselves don’t cause harm – the damage comes from what happens after it reaches the user. Post-incident investigation is about determining that damage: checking if users clicked or downloaded something malicious, gave up credentials, or if their machine triggered a process as a result.
If analysts stop at reviewing the email and don’t examine the user’s behavior and endpoint activity, they can miss early signs of compromise that quietly escalate into major incidents.
Here’s a step-by-step guide for post-delivery investigation.
Step 1: Reviewing Inbox Clues and Immediate Indicators
Post-incident delivery can get technical. But it shouldn’t start there. First, analysts should simply confirm whether the user interacted with the message at all. This means checking:
- Communication logs in the user’s mailbox for replies to the sender.
- If email triggered any mail-forwarding rules or if the user created any themselves after receiving the message. Malicious rules can indicate account takeover.
From there, analysts should carry out URL inspection. Analysts should ask themselves: Did the email contain rewritten links from a secure email gateway? If so, these rewrites may reveal follow-on redirects or tampering.
Investigators should map the actual destination domains, watching for redirect chains that bounce between innocuous-looking hops before landing on credential harvesters or malware delivery platforms. A simple URL click can generate a surprisingly deep trail.
Step 2: Investigating User Behavior and Endpoint Activity
This stage is where analysts move from inbox analysis to the user’s actual environment.
Browser logs are the first stop. They show whether the user opened the phishing link, how many redirects were involved, and whether any downloads occurred. Modern browsers also track blocked permissions, certificate warnings, and pop-ups that reveal attempted drive-by scripts or authentication prompts.
Endpoint telemetry is non-negotiable here. EDR logs tell the story of what happened at the process level:
- Was a file from the email downloaded?
- Was it opened?
- Did the system spawn unexpected child processes afterward?
- Did any macros run?
- Did the machine block or allow any scripts or executables tied to the phishing content?
Even when users claim they did nothing, the logs rarely lie. Analysts should hunt for any suspicious file execution, especially Office documents spinning up PowerShell, WMI, or regsvr32. These chains are common in phishing-driven initial access.
Network activity is also revealing. If the user’s device reached out to domains that appear in the phishing email, that is a strong indicator of interaction. Connections to other suspicious domains, including newly registered or known malicious sites, may also signal compromise even if they were not mentioned in the email. Unexpected outbound connections, beaconing patterns, or attempts to talk to command-and-control infrastructure are major red flags. If traffic to known malicious or newly registered domains appears shortly after the email’s delivery, that strongly suggests engagement.
Step 3: Correlating Logs, Network Events, and Telemetry
Think of post-incident investigation like a journalist researching a story. One source is good, but multiple sources make their story bulletproof. For analysts, correlating endpoint logs, browser histories, identity events, and network telemetry help understand the full scope of user activity.
If the user clicked a phishing link but nothing executed, the incident is contained. If the user downloaded something and the system trying to run it, containment is no longer assured. If the device then made outbound calls to suspicious infrastructure, the probability of compromise rises again.
Identity plays a vital role in correlation. Even if the phishing campaign didn’t drop malware, it can still steal credentials. Analysts should search for:
- Authentication attempts from new or implausible geographic regions
- Repeated login failures tied to brute-force attempts or replay of stolen passwords
- MFA push fatigue events
- Newly created OAuth grants or consent to suspicious applications
- Unexpected mailbox rule creation affecting the user
If these identity-level anomalies align with the phishing timeline, the investigation shifts from “possible compromise” to “probable breach.”
Step 4: Determining Whether the Breach Stayed Local or Spread
Once an analyst has figured out that a breach has occurred, they need to answer the biggest question of all: did the incident stay on the user’s machine, or did it escalate?
Lateral movement indicators are the dividing line between an isolated infection and a network-wide threat. Analysts should examine:
- SMB or RDP connections initiated by the user’s device
- Privilege escalation attempts shown in EDR logs
- Use of built-in tools like net.exe, whoami, or systeminfo in unusual sequences
- Credential dumping attempts or unauthorized access to other systems
If none of these artifacts appear and outbound activity didn’t persist, chances are you’re in the clear. But if there’s evidence of repeated authentication failures, privilege escalation attempts, or sustained outbound beaconing, you’re in trouble. After that point, you must starter broader incident response efforts.
How AI and Automation Strengthen Post-Delivery Investigations
As you have probably gathered, post-delivery investigations can be a long, laborious process.
Sifting through the enormous quantity of data involved in post-delivery investigation can overwhelm analysts. In fact, research from Prophet Security, a leading AI SOC provider, revealed that it takes an average of 70 minutes to fully investigate an alert.
AI-augmented investigation platforms help by surfacing the most relevant signals – meaning analysts don’t have to wade through thousands of lines of raw telemetry.
Modern systems can automatically follow the chain from email delivery to user clicks to endpoint activity and highlight anomalies that warrant attention. They can map redirect chains, suspicious file executions, flag malicious domains, and summarize identity-level events that match known compromise patterns.
The best solutions offer explainability – showing exactly why a signal matters and how it fits into the broader attack chain – plus auditability so SOC leads can validate findings.
Moreover, AI tools can automate the workflow outline above – immediately responding to potential phishing emails at any time of day or night.
From Reactive to Proactive Phishing Defense
Post-delivery investigation is the only way to confirm whether a phishing attempt fizzled or succeeded. By digging into the user’s environment, correlating telemetry, and tracking network and identity signals, analysts uncover whether the attack ended at delivery or grew into a compromise.
With AI-enhanced workflows doing the heavy lifting, SOC teams can move from reactive cleanup to proactive resilience. That means spotting threats faster, understanding them better, and responding before attackers gain real leverage.
Josh is a Content writer at Bora. He graduated with a degree in Journalism in 2021 and has a background in cybersecurity PR. He's written on a wide range of topics, from AI to Zero Trust, and is particularly interested in the impacts of cybersecurity on the wider economy.
The opinions expressed in this post belong to the individual contributors and do not necessarily reflect the views of Information Security Buzz.