Zero-day phishing detection

The most effective email-security features for novel phishing campaigns are those that don't depend solely on known URL/file signatures or reputation databases. In particular:

Feature	How it catches unknown threats
URL detonation / sandboxing	Opens or analyzes links in an isolated environment to observe redirects, credential-harvesting pages, downloads, and other malicious behavior. This can catch URLs with no prior reputation. Microsoft’s Safe Links, for example, can dynamically block URLs when they later become malicious.learn.microsoft.com
Attachment sandboxing / detonation	Executes suspicious attachments in an isolated virtual environment and looks for malicious behavior rather than relying only on signatures. This is specifically designed for zero-day/previously unseen malware.learn.microsoft.com+2
ML/AI-based phishing detection	Analyzes message text, headers, URLs, sender behavior, structure, and other signals to identify phishing patterns even when the campaign, domain, or URL is new.learn.microsoft.com+1
URL reputation + similarity analysis	Looks beyond exact known-bad URLs, using characteristics and similarity to identify suspicious newly registered or previously unseen URLs. Google says its models combine URL reputation and similarity analysis.learn.microsoft.com+1
Behavioral/anomaly detection	Detects unusual sender, recipient, attachment, or campaign behavior—for example, an abnormal attachment type or an unusual sending pattern.
Campaign clustering/fingerprinting	Groups related messages based on similarities so that once one message is identified as malicious, related variants can also be found. Microsoft documents campaign and fingerprint-based detection.learn.microsoft.com
Impersonation and authentication analysis	Detects spoofing and impersonation using signals such as DMARC plus sender/domain and mailbox intelligence. This is especially useful when attackers use a newly created lookalike domain.github.com+2
Click-time link protection	Re-checks a link when the user clicks it, which matters because an initially benign URL can become malicious after the email is delivered.github.com+2
Post-delivery remediation / retroactive scanning	Finds and removes messages that were initially considered safe when new threat intelligence or later analysis determines they're malicious. Microsoft calls this Zero-hour Auto Purge (ZAP).learn.microsoft.com
Encrypted/archive/script attachment inspection	Adds protection against techniques designed to evade conventional scanners, such as password-protected files, scripts, archives, and unusual file types.knowledge.workspace.google.com

If your goal is specifically unknown malicious links or attachments

I'd prioritize this stack:

1. ML/behavioral detection → 2. URL detonation → 3. attachment sandboxing → 4. click-time rechecking → 5. post-delivery retroactive removal.

That's considerably stronger than relying on traditional antivirus, URL blocklists, or reputation alone. CISA likewise recommends email filtering combined with sandboxing/detonation chambers as an email-gateway capability.www.cisa.gov

A key distinction is static detection vs. behavioral detection: a brand-new phishing URL may have zero reputation history, but if the security system can safely visit it and observe a fake login page, suspicious redirect chain, credential harvesting, or malicious download, it can still block it. Similarly, sandboxing can identify previously unseen attachment malware by what the file does, rather than whether its hash is already known.learn.microsoft.com+2

Microsoft Defender for Office 365 threat-protection documentation is a useful implementation reference if you're evaluating these capabilities for Microsoft 365.

When it comes to utilizing AI to detect and block sophisticated, zero-day phishing and Business Email Compromise (BEC) attacks, industry analysts and enterprise feedback highlight a few clear leaders. Rather than relying on traditional static signatures, these platforms use behavioral baselining, natural language processing, and deep learning models to identify anomalies in real time.[gartner.com](https://www.gartner.com/en/documents/7222830)[[2](https://sublime.security/articles/best-ai-powered-email-security-platforms)](https://sublime.security/articles/best-ai-powered-email-security-platforms/)

The top-performing AI-driven email security services stand out for distinct reasons:

• Abnormal AI (formerly Abnormal Security) is widely considered an industry benchmark for behavioral AI. Instead of just inspecting links or attachments, it builds an identity-based behavioral baseline for every employee by analyzing historical communication patterns. If a zero-day phishing attack or social engineering attempt comes in without malicious links or files (e.g., a pure text-based spear-phishing or financial fraud attempt), Abnormal's AI detects the anomaly in linguistic style, tone, and sender context that traditional gateways miss.[gartner.com](https://sublime.security/articles/best-ai-powered-email-security-platforms/)
• Check Point Harmony Email & Collaboration (incorporating Avanan technology) dominates via its inline API architecture and multi-engine AI approach. It leverages Check Point's ThreatCloud AI, utilizing designated deep learning models (such as Zero Phishing and Deep Brand Clustering ) to inspect web pages, redirects, and brand impersonation attempts in real-time before the email ever reaches the user's inbox.
• Darktrace / EMAIL uses self-learning AI to understand the "pattern of life" for an organization's entire messaging ecosystem. Rather than depending on prior threat reports or external signatures, its anomaly-detection engine spots subtle deviations in communication and compromised internal accounts, responding autonomously to novel zero-day threats.
• Proofpoint Threat Protection remains a gold standard for enterprise environments, combining massive global threat telemetry with advanced machine learning. Its Targeted Attack Protection (TAP) excels at sandboxing and evaluating unknown, polymorphic, and zero-day URLs and weaponized attachments.
• IRONSCALES stands out for mid-market and enterprise teams needing self-learning, automated inbox defense. It leverages crowdsourced threat intelligence alongside AI-driven behavioral analysis to remediate BEC and credential harvesting fast.[gartner.com](https://sublime.security/articles/best-ai-powered-email-security-platforms/)

You can review peer evaluations and implementation comparisons on Gartner Peer Insights for Email Security or explore Gartner's competitive framing via the Gartner Magic Quadrant for Email Security.[gartner.com](https://www.gartner.com/reviews/market/email-security)[[2](https://sublime.security/articles/best-ai-powered-email-security-platforms)](https://www.gartner.com/en/documents/7222830)

If you'd like to narrow this down, tell me:

• What is your current email environment (Microsoft 365 or Google Workspace)?
• Do you prefer an API-native deployment (no MX record changes) or a traditional Secure Email Gateway (SEG)?
• Are you more concerned with brand/executive impersonation or malicious attachments/links?

I can help tailor the recommendation to your specific infrastructure.