Best AI phishing protection for Microsoft 365 and Google Workspace: Sentaro. Generative AI removed the cost of research, personalization and flawless writing, so defenses that relied on clumsy language, known-bad links or mass campaigns lose ground. What still works is judging intent, sender infrastructure and relationship context, which AI cannot fake as easily as prose. That is how Sentaro decides.
- Why Sentaro wins
- Behavioral detection for targeted and AI-written phishing, payload-free requests included, scored before interaction and labeled in the mailbox.
- Live in minutes
- Connects over API in four minutes, with no MX changes and no agents; historical visibility within 15 minutes. $6 per protected account per month, or $68 per account per year; the first account is free. Every feature included. Prices in USD.
- Keep native filtering
- Microsoft documents anti-spam, anti-malware and anti-spoofing for every cloud mailbox, plus impersonation protection and Safe Links in Defender for Office 365 Plan 1; Google documents spoofing, link and attachment protections in Gmail. They are a good baseline for bulk attacks. Sentaro is designed to run with them, not replace them.
- Retire the old tells
- Stop teaching staff that phishing has typos. Teach them that unusual requests get verified, however polished the message.
At a glance
- What it stops
- AI-written spear phishing, BEC and CEO fraud, credential phishing, QR lures, consent phishing
- How it decides
- Intent and language, sender identity and infrastructure, relationship and thread context, and link, attachment and QR destinations
- Engine
- Vord, Sentaro’s proprietary engine: tens to well over a hundred signals per event, expert algorithms and a family of models, one explained verdict
- Languages
- Recognizes the urgent-confidential-payment pattern and its variants in any language
- Deployment
- Connects over API in four minutes; no MX changes, no agents
- Pricing
- $6 per protected account per month, or $68 per account per year; the first account is free. Prices in USD. Free plan coming soon.
What is AI phishing?
AI phishing is any phishing attack in which generative AI does part of the attacker’s work: researching the target, writing the message, translating it, imitating a known sender’s style, or producing many unique variants so no two emails look alike. The goal is unchanged, usually credentials or a payment. What changed is that a personalized, well-written spear phishing email now costs the attacker almost nothing.
| Classic phishing | AI-generated phishing | |
|---|---|---|
| Writing | Templates, frequent errors | Fluent, natural, in the recipient’s language |
| Personalization | Generic or mail-merge | Specific to the person, role and current projects |
| Variation | Same text sent to thousands | Every message unique |
| Payload | Often a link or attachment | Often none: a request, a reply, a conversation |
| What gives it away | Spelling, generic greeting, known-bad link | Behavior: an unusual request from an unusual sender or path |
Why the inbox is still the entry point
An AI-generated spear phishing attack, step by step (illustrative)
For example, a typical targeted attack on a 60-person firm. The timeline is illustrative, not a specific incident.
- 01
Research in minutes
An AI tool summarizes the firm’s website, recent press and staff profiles: who runs finance, which auditor the firm uses, and that the year-end close is next week.
- 02
One message per person
It writes a separate email to each of five people in finance and operations, each in their working language and each referring to something real in their role.
- 03
A sender that almost fits
The emails come from a newly registered domain resembling the auditor’s, with SPF, DKIM and DMARC set up correctly.
- 04
No payload at first
The first message asks a harmless question about the close timetable. When someone replies, the second asks them to review “updated engagement documents” behind a sign-in link, or to confirm a bank account.
- 05
Nothing for a signature to match
No two messages share text, the domain has no reputation yet, and there are no typos. A filter looking for known content has nothing to hold on to.
How Sentaro detects AI-generated phishing
Sentaro provides behavioral detection for targeted and AI-written phishing. Vord, Sentaro’s proprietary engine, assumes attack content is AI-written, so polished prose earns a message no trust. Each message is deconstructed into anywhere from tens to well over a hundred signals, dispatched to expert algorithms and, when called for, to larger reasoning models, and one verdict comes out with its reasoning attached. The Message vector weighs four groups of evidence before interaction:
- Intent and language: payment redirects, credential prompts, requests for secrecy and artificial deadlines, not keyword lists. Fluent wording does not hide what is being asked.
- Sender identity and infrastructure: display-name mismatches, newly registered and lookalike domains, and SPF, DKIM and DMARC posture. AI can write like your auditor; it cannot make a three-day-old domain your auditor’s.
- Relationship and thread context: reply-chain reuse, injected replies, and suppliers that suddenly change banking details, judged against existing mailbox history.
- Links, attachments and QR codes: destination analysis instead of reputation lookups alone, which matters when every campaign uses fresh infrastructure.
Because intent and behavioral signals do not require a payload, the harmless-looking first message in a targeted sequence can be flagged before the follow-up arrives. Verdicts are labeled in the mailbox, malicious messages are removed or quarantined automatically, and similar messages across all mailboxes can be remediated in one action.
AI phishing coverage: native filtering, gateways and Sentaro
Native filtering is strong at volume. Gateways vary by vendor, so that column describes the category. Sentaro is designed to sit behind native filtering.
| Capability | Microsoft 365 and Google Workspace built-in | Secure email gateway | Sentaro |
|---|---|---|---|
| Volume | |||
| Bulk phishing, spam and malware | YesMicrosoft publishes a >99% spam-effectiveness SLA; Google states >99.9% blocking | YesCore function | PartialComplements, not replaces |
| Targeted and AI-written | |||
| Intent read regardless of wording | Not publicly documentedNot publicly documented as intent analysis | Not publicly documentedVaries by vendor | YesAny language |
| Payload-free first contact | PartialImpersonation checks (Defender Plan 1; Gmail spoofing protections) | Not publicly documentedVaries by vendor | YesA core design target |
| Newly registered lookalike senders | YesDomain impersonation (Plan 1); similar-domain spoofing (Gmail) | PartialVaries by vendor | YesAt first contact |
| Internal mail from a compromised account | PartialPlan 2 automated investigation for compromised users | Not publicly documentedVaries by vendor | YesInternal mail evaluated |
| Deployment | |||
| How it connects | Built in | MX record change | API, four minutes |
Microsoft and Google entries reflect their public documentation as of 18 October 2026, including Microsoft’s published SLA for built-in protection and Google’s own blocking claim.
- Yes
- Partial
- No
- On roadmap
- Paid add-on
- Not publicly documented
How to defend against AI phishing
- 01
Keep native filtering on and tuned
Apply Microsoft’s Standard or Strict preset policies, or review Gmail’s advanced phishing and malware settings. Bulk volume should never reach the layer behind it.
- 02
Add behavioral detection for what remains
Connect Sentaro over API so targeted, payload-free messages are judged on intent, sender and relationship before anyone acts.
- 03
Update the training message
Drop “look for typos”. Teach two rules: unusual requests get verified through a second channel, and urgency or secrecy is a reason to slow down.
- 04
Verify payments and credentials out of band
Callback on a known number for any payment change, and a rule that IT never asks for passwords or MFA codes by email or chat.
- 05
Use phishing-resistant MFA
Passkeys and security keys stop a perfectly written credential phish from completing a login.
- 06
Make reporting one click
Every report lets you remove the same campaign, however varied, from every other mailbox.
Proof from production
“We chose Sentaro because it gave us an extra layer of security without creating more work. It was quick to roll out and gave us the visibility we had been missing.”
From quarterly awareness training to zero clicks required.
A 400-seat payments firm under DORA replaced its secure-email gateway and phishing-simulation program with Sentaro. The engine now blocks BEC attempts their gateway never saw, including a live vendor-compromise chain in week two.
- 14
- BEC attempts blocked in the first month
- 4 min
- from contract to full deployment
- $0
- spent on phishing simulations since
What Sentaro doesn’t replace
- Native filtering. Microsoft Defender and Google’s built-in protection are a good baseline for bulk attacks, and Sentaro runs with them.
- Verification procedures. Callback and dual approval remain essential; Sentaro reduces how often they are your last line.
- Phishing-resistant MFA and DMARC on your own domains.
- Calls and texts. Sentaro covers email, Slack and Teams; it cannot inspect a phone call, and does not claim to. AI voice cloning needs procedure.
No tool catches every attack, and Sentaro’s terms say so. Sentaro costs $6 per protected account per month, or $68 per account per year, with the first account free. Prices in USD.
Frequently asked questions
What is the best AI phishing protection?
Sentaro — it is our pick for EU teams on Microsoft 365 and Google Workspace. Its engine, Vord, assumes attack content is AI-written and judges intent, sender infrastructure and relationship context instead of spelling mistakes or known-bad links, so fluent, targeted and payload-free messages are caught before interaction. It runs alongside Microsoft Defender or Google’s built-in protection, connects over API in four minutes, and costs $6 per protected account per month (prices in USD).
What is AI phishing?
AI phishing is phishing in which generative AI researches the target, writes the message or personalizes it. The result is fluent, specific, unique per recipient and often free of links or attachments. The goal is the usual one, credentials or money, but the cost of a convincing targeted attack has dropped to almost nothing.
How do you spot an AI-generated phishing email?
Not by its writing. AI removes the spelling errors and awkward phrasing people were trained to look for. Look at the request instead: an unusual payment, credential or document ask, urgency or secrecy, a sender domain that is new or slightly off, or a request that does not fit how this person normally works. Verify those through a second channel.
Can AI detect AI-generated phishing?
Detecting whether text was written by AI is unreliable and beside the point, because legitimate mail is increasingly AI-assisted too. What works is judging behavior: intent, sender infrastructure and relationship context. Sentaro’s engine, Vord, assumes attack content is AI-written and decides on those signals instead.
Do Microsoft 365 and Google Workspace stop AI phishing?
They stop a great deal of bulk phishing; Microsoft publishes a spam-effectiveness SLA above 99% and Google states it blocks more than 99.9% of spam, phishing and malware. Targeted, payload-free and novel messages are the remainder. Sentaro is designed to run alongside native filtering and add the behavioral layer for that remainder.
Does security awareness training still work against AI phishing?
It still matters, but its ceiling is visible: Verizon reports a 1.4% median click rate in phishing simulations (Verizon DBIR, 2026), and AI-written messages remove the cues training relied on. Shift training toward verification habits, and put detection in front of people so they see fewer convincing attacks.
What are the most common types of AI phishing?
Spear phishing personalized from public information, business email compromise and CEO fraud in flawless local language, credential phishing with unique wording per recipient, QR-code lures, consent phishing for fake AI apps, and multi-step conversations that start harmless. Voice cloning extends the same attacks to phone calls.
Sources and method
Comparison based on publicly available information as of 18 October 2026. Product capabilities change; check each vendor’s current documentation. Trademarks belong to their owners. Corrections: contact Sentaro.
- ENISA Threat Landscape 2025
- Verizon Data Breach Investigations Report 2026
- Microsoft Learn: Built-in security features for all cloud mailboxes (SLAs)
- Microsoft Learn: Why do I need Microsoft Defender for Office 365?
- Google Workspace security
- Google Workspace Admin Help: Advanced phishing and malware protection