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ReliaQuest is singularly focused on making security possible for organizations of all sizes, in all locations, and in all industry verticals. This means helping to increase their security visibility, reduce complexity, and manage risk.
To help further this mission, ReliaQuest is pleased to announce the global release of Phishing Analyzer as part of its security operations platform, GreyMatter. Phishing Analyzer is designed to continue to free up your security team and reduce the risk of phishing attacks by automating the entire abuse mailbox management process for you. The tool performs automated phishing analysis on suspicious emails reported by users, takes remediation actions, and sends follow-up notifications to reporters—all without your team ever needing to look at the reported email. Phishing Analyzer frees your team to work on the most important priorities.
Despite advances in technology and increased awareness, email phishing attacks continue to be a persistent threat to individuals and organizations alike. Why is this? Simply put—it works.
Most organizations have a Secure Email Gateway (SEG) as a control to combat email-based threats, but the reality is that some malicious emails slip past the gateway and others are specifically designed to get through.
Some nefarious emails don’t have anything for the email gateway to detect. They may not include a malicious attachment or link that would require further detection and analysis before delivery. They simply use social engineering to trick unsuspecting people into giving up something valuable, whether that’s money, information, access, or something else. This tactic is common in business email compromise (BEC) attacks, which have cost organizations more than $43 billion since 2016.
Email attacks that use social engineering can look like legitimate business communication and may not raise red flags for the email recipient. For example:
There are a couple of tactics a bad actor can use to launch these phishing attacks, including domain spoofing, lookalike domain spoofing, and display name spoofing.
Domain spoofing: A tactic used by cybercriminals to hijack a legitimate domain
Ex. “John Smith” <Person@acme.com>
Lookalike domain spoofing: When a malicious email is sent from a domain that looks like the legitimate domain. This can involve switching a “O” for a “0”, a “5” for an “S”, or a “r” and an “n” for an “m”.
Ex. “John Smith” <Person@cornpany.com>
Display name spoofing: Potentially the most common tactic used due to its simplicity. Display name spoofing is where the “Friendly from” name is changed to whoever the bad actor wants to pretend to be to launch the scam.
Ex. “John Smith” <[email protected]>
Regardless of how bad emails end up in the inboxes, organizations are now reliant on their users to be a protective force on the front lines to help stop these attacks.
The rise in phishing awareness programs has enabled employees, contractors, and partners to assist the security team in the fight against email phishing. Today, many users are trained to spot suspicious emails that show up in their mailboxes.
Plus, organizations can test their users’ knowledge by launching simulated phishing attacks to their users to measure the effectiveness of the training and find additional opportunities to help their users become an additional security layer for the organization.
But simply spotting suspicious emails is not enough. Users need a way to notify the security team about suspicious emails they receive to help the security team prevent email-based attacks across the entire organization. Enter the abuse mailbox.
The abuse mailbox offers an invaluable solution to help stop those additional email-based threats that bypass the initial security controls. Now your security team knows what email threats are getting through, how they’re getting through, and who has been impacted.
The challenge is that the abuse mailbox introduces an additional lift for the security team. Some companies have a full-time headcount dedicated solely to managing the abuse mailbox, but managing the abuse mailbox is not a desirable job. It’s manual, time-consuming, tedious work that can lead to employee dissatisfaction and churn. It requires triaging a continuously growing number of reported emails, taking response actions on each, and notifying the reporters about the analysis decision.
Abuse mailboxes frequently include a high number of false positives because users frequently mass-forward benign emails to the security team in an effort to be overly cautious. Marketing ads, subscription updates, and other spam emails clutter the abuse mailbox. According to ReliaQuest Internal Data, approximately 85% of user-reported phishing emails are benign.
Phishing Analyzer’s end-to-end abuse mailbox management means that once a reported email arrives in the abuse mailbox, it performs automated phishing analysis to determine whether it is malicious or benign. If malicious, the reported email is not only removed from that user’s inbox, but matching emails are also removed from inboxes across the organization
The Phishing Analyzer is powered by the ReliaQuest security operations platform, GreyMatter. This means that you can see the full scope of the phishing attack—including whether a user downloaded a file or clicked on a malicious link—without leaving the platform. We use a combination of information to analyze reported emails—this includes looking at the content (header, sender information, email body, etc.) and context of each email.
Plus, our machine-learning capabilities speed up the analysis process and cut through the noise of false positives. We identify phishing campaigns targeting your organization by matching against duplicate and similar emails across the organization.
GreyMatter Phishing Analyzer automatically sends an analysis write-up to the security team and an analysis decision (malicious or benign) to the reporter. Your security team can leverage this information to add security controls for stronger protection, and end users can become better equipped to identify malicious emails that land in their inboxes.