MailWasher is the best spam blocker to help you block spam and scams before they get to your inbox

Attachment Filtering
A spam filter feature that scans email attachments for malicious content, such as viruses or ransomware, blocking or quarantining emails with suspicious files.

Authentication Protocols
Standards like SPF, DKIM, and DMARC that verify the legitimacy of an email’s sender. These help spam filters detect forged emails and protect against phishing and spoofing.

Backscatter
Unwanted bounce-back emails generated when a spammer forges a sender’s address, causing delivery failure notifications to be sent to an innocent third party.

Bayesian Filtering
A statistical technique that classifies emails as spam or ham based on the probability of certain words or phrases appearing. It adapts over time using user feedback and training data.

Blacklist
A database of email addresses, domains, or IP addresses known to send spam. Spam filters use blacklists to block or flag messages from untrusted sources.

Business Email Compromise (BEC)
A type of email scam where attackers impersonate executives or trusted contacts to trick employees into transferring money or sharing sensitive data.

Clickjacking
A malicious technique where users are tricked into clicking on hidden or disguised links in an email, often leading to phishing sites or malware downloads. Spam filters may flag emails with suspicious link structures.

DKIM (DomainKeys Identified Mail)
An email authentication method that uses cryptographic signatures to verify that an email was sent from an authorized domain and hasn’t been altered in transit.

DMARC (Domain-based Message Authentication, Reporting, and Conformance)
A policy that builds on SPF and DKIM to specify how unauthenticated emails should be handled (e.g., rejected or quarantined). It helps protect against email spoofing.

Email Bombing
A form of email attack where a large volume of emails is sent to overwhelm a recipient’s inbox, often as a denial-of-service tactic. Spam filters may detect and throttle such floods.

Email Spoofing
The act of forging an email’s sender address to appear as if it comes from a trusted source. Spoofed emails are often used in phishing or spam campaigns.

False Negative
When a spam or malicious email is incorrectly classified as legitimate and delivered to the inbox, indicating a spam filter’s failure to detect it.

False Positive
When a legitimate email (ham) is mistakenly flagged as spam and moved to the spam folder or blocked, often due to overly aggressive filtering rules.

Grey Mail
Emails that are neither clearly spam nor ham, such as newsletters or promotional emails that users may have subscribed to but no longer want. Grey mail often clogs inboxes and challenges spam filters.

Greylisting
A filtering technique that temporarily rejects emails from unknown senders, requiring the sender’s server to retry delivery. Legitimate servers typically retry, while spam servers often do not.

Ham
Legitimate, non-spam emails that users want to receive. Spam filters aim to correctly identify ham to avoid false positives.

Header Analysis
The process of examining an email’s metadata (e.g., sender, recipient, routing information) to detect signs of spam, spoofing, or malicious intent.

Heuristic Filtering
A method that uses predefined rules or patterns (e.g., suspicious keywords, formatting, or links) to identify spam. It’s fast but less adaptive than machine learning or Bayesian methods.

Image-based Spam
Spam emails that embed text in images to evade text-based spam filters. Advanced filters use optical character recognition (OCR) to detect such content.

Machine Learning
A technique in modern spam filters where algorithms analyze large datasets of emails to identify patterns of spam, phishing, or ham, improving accuracy over time.

Malware
Malicious software (e.g., viruses, ransomware) delivered via email attachments or links. Spam filters scan for known malware signatures or suspicious behavior.

Phishing
A type of email scam designed to trick users into revealing sensitive information (e.g., passwords, credit card details) by posing as a trustworthy entity, such as a bank or company.

Quarantine
A secure area where suspicious emails are held for review before being delivered, deleted, or flagged. Quarantine helps prevent false positives while protecting users.

Ransomware
A type of malware delivered via email that encrypts a user’s files and demands payment for decryption. Spam filters prioritize detecting ransomware payloads.

Reputation Filtering
A method that evaluates the trustworthiness of an email sender based on their IP address, domain, or past behavior. Low-reputation senders are more likely to be flagged as spam.

Sender Policy Framework (SPF)
An email authentication protocol that checks if an email was sent from an authorized server for the domain, helping to detect forged sender addresses.

Smishing
A phishing variant where attackers use SMS or email-to-text messages to trick users into clicking malicious links or sharing personal information.

Snowshoe Spam
A spamming technique where attackers spread their emails across many IP addresses or domains to avoid detection and blacklisting. Filters counter this by analyzing patterns across multiple sources.

Social Engineering
Manipulative tactics used in email scams to exploit human psychology, such as creating urgency or impersonating authority figures to elicit actions like clicking links or sharing data.

Spam
Unwanted or unsolicited emails, often sent in bulk, promoting products, scams, or malicious content. Spam filters aim to block or divert these to the spam folder.

Spam Score
A numerical value assigned to an email based on its likelihood of being spam, calculated using factors like content, sender reputation, and metadata. Filters act based on predefined thresholds.

Spam Trap
An email address created to lure spammers, not used for legitimate communication. Emails sent to spam traps are automatically flagged, helping to identify and blacklist spammers.

Spear Phishing
A targeted phishing attack aimed at specific individuals or organizations, often using personalized information to increase credibility and success rates.

Trigger Words
Words or phrases (e.g., “free,” “win,” “urgent”) commonly associated with spam. Filters flag emails with excessive trigger words, though this can lead to false positives if not balanced.

Two-Factor Authentication (2FA)
A security measure requiring two forms of verification (e.g., password and a code sent to a phone) to access an email account, reducing the risk of unauthorized access from phishing attacks.

URL Obfuscation
A technique used in spam or phishing emails to disguise malicious links by encoding, shortening, or embedding them in misleading text. Filters analyze URLs to detect obfuscation.

Vulnerabilities
Weaknesses in email systems (e.g., outdated software, weak passwords) that spammers or hackers exploit to send spam, phishing emails, or malware.

Whitelist
A list of trusted email addresses, domains, or IP addresses whose emails are always allowed through the spam filter, preventing false positives for known senders.

Zero-Day Exploit
A cyberattack that targets a previously unknown vulnerability in an email client or server, often bypassing spam filters until the vulnerability is patched.

The advantage of being able to check your AOL email or any other email on the server before they get to your PC is you can view all aspects of an email such as who it's really from, hidden links, attachments and many other things about the email.

This helps you to make an informed choice about an email so you don't accidentally click on it, or allow it on to your PC.

MailWasher is quick to setup and you can see all your emails in one place, whether is Gmail, Outlook.com, Yahoo, AOL or any other email account. You can check unlimited emails accounts with MailWasher Pro.

While MailWasher Spam Tools help you identify spam and good emails quickly, you can also quickly train MailWasher to help it identify good and spam emails and then it will do all the work for you.