With all the advances in email security, it would be easy to assume that phishing emails are a relic of the past. However, they continue to land in inboxes every day. Hidden among legitimate messages are fake invoices, password reset requests, and urgent warnings that somehow slip through. With all the advances in email security, it would be easy to assume that phishing emails are a relic of the past. However, they continue to land in inboxes every day. Hidden among legitimate messages are fake invoices, password reset requests, and urgent warnings that somehow slip through. Phishing has evolved from the old spray-and-pray tactics to more methodical ways to bypass filters. While various methods to keep them at bay exist, cybercriminals are constantly adapting. Many security systems have yet to get ahead and stay that way, so implementing multiple defenses remains critical for all email users. Here’s what hackers are doing to infiltrate inboxes and how users can stop them in their tracks. 1. Utilize Social Engineering One weapon hackers have used for years is psychology. It’s one of the most popular forms of phishing, with research showing that around 90% of these incidents involve some form of social engineering. Rather than using brute-force measures, attackers manipulate human behavior to open the door for them. 90% of these incidents This tactic works so well because it often relies on urgency or fear. A phishing email can look like it's from an IT department and warn the recipient of something like a suspended account. This pushes people to act quickly, causing them to respond without pause. How does it bypass content filters in the first place? The short answer is adaptability. Some hackers will send several emails to establish credibility before delivering the attack. By the time security systems detect a threat, the human element has already been compromised. 2. Mimic Real Emails 2. Mimic Real Emails Phishing attacks are most effective when they don’t look suspicious at all. One sophisticated strategy is mimicking a legitimate email that looks like it’s coming from an organization or colleague. Hackers will even use the right formatting, logos, language, and tone. These emails are almost indistinguishable from the real deal. Cyber experts refer to this tactic as clone phishing. This method involves copying an email and swapping out a link or attachment with a malicious one. Sometimes, cybercriminals carry out this attack via email message replies. Attackers will take a message from a commonly known entity and send it to their target. When it comes from what appears to be a known contact or brand, the chance of it slipping past security filters increases dramatically. What makes this method especially dangerous is how seamlessly it fits into normal communication patterns. Research finds that about 94% of malware comes from emails, largely because phishing messages are often unsuspecting. A regular-looking email will not raise red flags — it only needs to feel familiar enough to lower the recipient’s guard. about 94% of malware 3. Exploit Technical Loopholes 3. Exploit Technical Loopholes Phishing emails do more than trick people — they also lean on tricking systems. While email security filters have grown more sophisticated, attackers know how to exploit the existing technical gaps. These loopholes are often small, such as in how browsers interpret URLs or filters analyze metadata. These instances are enough to get a malicious email through the gate. A common trick is homograph spoofing, which uses Unicode characters to make malicious URLs look innocent. For example, a Cyrillic “a” may replace a Latin “a” in “amazon.com” — visually identical to the human eye but leading to somewhere entirely different. Filters that improperly normalize these characters can miss the deception altogether. Attackers also abuse open redirects, where a link points to a legitimate domain that redirects the user to a harmful one. Filters may scan the initial URL and deem it safe without realizing what comes next. Similarly, embedding payloads within cloud platforms helps phishers bypass domain-based filtering entirely. After all, most security systems lack configurations to block links from trusted cloud services. 4. Avoid Spam Filter Triggers 4. Avoid Spam Filter Triggers Phishing emails have grown far beyond clumsy messages with glaring typos and suspicious “CLICK HERE” links. Today, many slide under the radar with tactics that strip emails of anything that may trigger automatic detection. Attackers achieve this by incorporating specific language to ensure they leave out keywords the system finds spammy. For instance, a hacker will leave out words like “click,” “account,” “urgent,” or “Microsoft” to keep spam scores low. They’ll also deliberately choose language that feels neutral or routine. The email content is also minimal. A message sent with something vague like “Please see the attached file” or “Can we talk?” avoids keyword-based filtering entirely. This method also copies the phrasing of internal memos or meeting requests, making security systems less likely to raise flags. 5. Evade Subject Line and Content Filtering 5. Evade Subject Line and Content Filtering Email filters often depend on pattern recognition to flag suspicious subject lines, phrasing, or formatting that match known phishing templates. However, today’s attackers no longer work manually. They’re leveraging automation to generate and test phishing campaigns at scale, making it harder for filters to keep up. Tools that hackers commonly use include scripts, which can scan thousands of systems in minutes, identifying known vulnerabilities or misconfigured mail servers. Once they find a target, they can generate custom phishing messages that bypass common filters. The setup for these emails includes: can scan thousands of systems Randomized subject lines
Slightly altered phrasing in each version
Adjusted message formatting to avoid repetition Randomized subject lines Slightly altered phrasing in each version Adjusted message formatting to avoid repetition Why Filters Fail Email filters may provide a defense against phishing, but they’re far from foolproof. They utilize rules, heuristics, threat databases, and machine learning to assess risk. While they catch many malicious emails, attackers only need one to get through. When that happens, the consequences stem from a technical flaw and a false sense of security. A recent study found that users who believed their email filters were highly reliable were likelier to lower their guard and fall for phishing attempts. The assumption that anything malicious would be automatically removed led some to overlook warning signs. The more people trust automated protection, the less critically they tend to assess what lands in their inbox. likelier to lower their guard Overreliance is dangerous because filters aren’t perfect. They often miss brand-new phishing domains or links hosted on trusted platforms. To avoid false positives, filters may lean toward caution, delivering questionable content as a result. Even with all the technical defenses in place, these tools are only part of the solution. The rest depends on human behavior. What to Do to Mitigate Phishing Risks While no system is impenetrable, there are several ways to reduce the chances of phishing attacks slipping through: Deploy large language model (LLM) detection tools: One study introduced ChatSpamDetector, which uses LLMs to analyze email content. The system achieved 99.70% accuracy in identifying phishing attempts. Integrating LLMs into security workflows is becoming the top method for spotting deception, especially with how quickly and more advanced these systems are compared to traditional filtering.
Strengthen domain authentication protocols: Ensure the Sender Policy Framework (SPF), Domain-Based Message Authentication, Reporting and Conformance (DMARC), and DomainKeys Identified Mail (DKIM) have the proper configurations. These protocols validate messages from approved servers to prevent spoofing.
Use blockchain for email verification: Blockchain technology can confirm if email service providers are real. It works by connecting verification extensions through decentralized ledgers, allowing providers to authenticate the message and detect anomalies.
Restrict link access and macros: Limit the use of links and macros in emails, especially from unknown sources. Sandboxing suspicious attachments before opening them can further reduce exposure. Deploy large language model (LLM) detection tools: One study introduced ChatSpamDetector, which uses LLMs to analyze email content. The system achieved 99.70% accuracy in identifying phishing attempts. Integrating LLMs into security workflows is becoming the top method for spotting deception, especially with how quickly and more advanced these systems are compared to traditional filtering. Deploy large language model (LLM) detection tools: system achieved 99.70% accuracy Strengthen domain authentication protocols: Ensure the Sender Policy Framework (SPF), Domain-Based Message Authentication, Reporting and Conformance (DMARC), and DomainKeys Identified Mail (DKIM) have the proper configurations. These protocols validate messages from approved servers to prevent spoofing. Strengthen domain authentication protocols: Use blockchain for email verification: Blockchain technology can confirm if email service providers are real. It works by connecting verification extensions through decentralized ledgers, allowing providers to authenticate the message and detect anomalies. Use blockchain for email verification: connecting verification extensions through decentralized ledgers Restrict link access and macros: Limit the use of links and macros in emails, especially from unknown sources. Sandboxing suspicious attachments before opening them can further reduce exposure. Restrict link access and macros: Securing Emails Beyond Filtering Phishing attacks are increasingly common and advanced. While email filters can handle most attempts, they can still slip up. That’s why it’s important to use prevention strategies outside of the software by leveraging next-gen tools and rethinking trust in automation. By incorporating the next level of defense, email users are more likely to spot what filters miss.

The is an opinion piece based on the author’s POV and does not necessarily reflect the views of HackerNoon.

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