Stop Authentication Coercion With AI-Led Detection

Most companies still treat credential theft like a “user problem.” Phishing. Weak passwords. MFA fatigue.

Authentication coercion flips that story. The attacker doesn’t need your user to type anything. They pressure machines—servers, Domain Controllers, RODCs—into authenticating to attacker-controlled infrastructure, then harvest credentials (often NTLM hashes) that can be relayed into something far worse.

And the trend that should worry you most in late 2025? Attackers are moving away from the famous coercion paths defenders already monitor (like printer-related vectors) and toward rare, barely used Windows RPC interfaces and operation numbers (opnums). If your detections are tuned to known tools, you’ll miss the next wave.

This post is part of our AI in Cybersecurity series, and it’s a good example of where AI actually earns its keep: not by “predicting hackers,” but by finding abnormal authentication and RPC behavior at enterprise scale—the stuff humans can’t baseline by hand.

Authentication coercion: credential theft without phishing

Authentication coercion is simple in outcome and sneaky in execution: a target system is forced to initiate authentication to an attacker-controlled host.

In Windows environments, that typically happens when a system tries to access a remote resource (like a share, a printer, or a service endpoint) and automatically negotiates authentication. If the attacker can trigger that outbound authentication and capture the resulting exchange—especially NTLM—they can often:

• Capture and relay the authentication to other services (NTLM relay)
• Escalate privileges by targeting identity infrastructure (like certificate services)
• Move laterally using machine account material (especially dangerous for Tier 0 assets)

Here’s the blunt version:

If a Domain Controller can be coerced into authenticating outward, you’re one misconfiguration away from domain-wide impact.

This is why authentication coercion keeps showing up in real intrusions. It’s reliable, it’s fast, and it uses normal Windows behavior.

Why defenders keep losing to “known exploit” thinking

A lot of security programs do something like this:

1. A coercion method becomes popular (PrintNightmare/PrinterBug, PetitPotam)
2. Vendors ship detections for the specific interface/opnum pattern
3. Blue teams monitor those known indicators
4. Attackers switch to a different RPC interface that triggers the same outbound auth behavior

The result: your tooling may correctly block yesterday’s exploit signature while quietly ignoring a new coercion path that your environment almost never uses.

The real attack surface is RPC—and it’s bigger than your rules

Windows Remote Procedure Call (RPC) is the plumbing behind a huge amount of Windows and Active Directory functionality. It’s designed to let software call functions on remote machines, frequently with low privilege requirements.

The part that matters for coercion is this: many RPC methods accept parameters that can include UNC paths like \\server\\share\\file. If an attacker can supply a UNC path pointing to attacker infrastructure, they can trigger outbound authentication from the victim.

“Rare opnums” are the new bypass strategy

Security teams often watch the interfaces that popular tools hit:

• Print-related RPC protocols
• Encrypting File System RPC paths
• DFS and VSS-related interfaces
• Event log remoting

But public research has already demonstrated that there are dozens of known working methods and hundreds more untested functions that could plausibly be abused the same way.

That’s the critical shift:

Attackers don’t need new malware. They just need a new RPC method your monitoring ignores.

In practice, this means detections must become more behavior-based and less “this GUID + that opnum.”

Case study lesson: MS-EVEN coercion and why it worked

A real-world incident pattern observed in 2025 is worth copying into your threat modeling.

Attackers used the EventLog Remoting RPC interface (MS-EVEN)—specifically a rarely monitored function often associated with opening backup event logs remotely—to coerce servers into authenticating to an external IP.

What made it stand out wasn’t a classic malware signature. It was behavior:

• A workstation initiated RPC calls to multiple critical servers in a tight window
• The protocol/function combo was rare in the environment (almost no historical usage)
• The RPC parameters contained a network location pointing outside the organization
• Shortly after, there were attempts to use NTLM material against high-value systems (including certificate-related infrastructure)

If you’re thinking “we’d see that,” be careful. In many shops:

• RPC telemetry is noisy and under-instrumented
• “Remote event log” traffic isn’t treated like a Tier 0 concern
• Outbound authentication from servers is common enough that individual events look normal

The defenders who catch this consistently do one thing differently: they focus on relationships and baselines (who talks to whom, using what interface, how often), not just static indicators.

Where AI helps: anomaly detection for RPC and authentication behavior

AI-driven cybersecurity is especially useful here because authentication coercion is a pattern problem:

• Lots of legitimate RPC exists
• Coercion often uses legitimate Windows mechanisms
• Attackers win by choosing what your team “never looks at”

Good detection requires combining signals across endpoint, identity, and network data—then scoring what’s odd.

What AI should baseline (and what it should flag)

If you’re building detections or evaluating an AI SOC platform, here are the behaviors that matter.

1) Rare RPC interface + rare opnum usage

• Baseline which RPC interfaces and opnums are normal for each host role
• Flag first-time or near-zero-frequency interface usage, especially against Tier 0 assets

2) Suspicious UNC path parameters

• Flag RPC calls containing UNC paths pointing to:
  • External IPs
  • Newly seen internal hosts
  • Non-corporate naming patterns
• Prioritize when the destination host is a Domain Controller, CA server, RADIUS server, or Citrix infrastructure

3) Burst behavior across many servers

Coercion tooling often sprays:

• One source host
• Many target servers
• Short time window

That “one-to-many” graph pattern is something ML-based detection is good at spotting.

4) Downstream authentication artifacts

Treat these as a connected storyline, not separate alerts:

• Sudden NTLM authentication attempts from unusual hosts
• Atypical machine account authentications
• Failed NTLM attempts followed by successful auth to sensitive services
• Certificate enrollment anomalies (common after coercion + relay)

The win is correlating “odd RPC” with “odd authentication” quickly enough to stop relay and escalation.

A practical AI detection stance (that doesn’t require magic)

I’m skeptical of vague “AI will detect everything” claims. What works is narrower:

• Entity baselining: normal RPC/auth patterns per host role (DC vs app server vs workstation)
• Peer grouping: compare a Citrix server to other Citrix servers, not to everything
• Graph correlation: connect the initiating host, targeted servers, and outbound auth destinations
• Alert quality gates: suppress known-good admin workflows; elevate novel combinations

If you can’t explain why a detection fired in one sentence, it probably won’t hold up during incident response.

Defensive controls that actually reduce coercion risk

AI helps you spot what’s abnormal. You still need controls that make coercion harder to monetize.

Harden the environment so coerced auth can’t be relayed

Enforce SMB signing where possible

• This is one of the most practical ways to make credential relay harder.

Use Extended Protection for Authentication (EPA) on key services

• EPA helps bind authentication to the channel, reducing relay opportunities in certain configurations.

Reduce or eliminate NTLM where you can

• Many enterprises can’t drop NTLM overnight, but you can often:
  • Restrict NTLM on Tier 0 assets
  • Monitor NTLM usage aggressively
  • Enforce modern auth on the systems that matter most

Shrink the RPC attack surface

Disable unused RPC-based services (especially on Domain Controllers)

• If a service isn’t required for that asset’s role, it shouldn’t be reachable.

Use RPC filtering to block known bad patterns

• Windows supports RPC filters. Even when attackers pivot to new opnums, blocking high-risk interfaces on sensitive servers can help.

Segment who can talk RPC to Tier 0 assets

• “Any domain user can reach DC RPC” is a legacy assumption that doesn’t age well.

Monitoring that pays off fast

If you only implement three monitoring upgrades this quarter, I’d pick these:

1. Alert on outbound authentication from servers to new destinations (especially external)
2. Track rare RPC interfaces/opnums per host role and alert on first-time use
3. Correlate coercion signals with certificate services activity (enrollment, template abuse, unusual machine account requests)

These are high-signal because most enterprises have stable server behavior. When it shifts, it’s usually for a reason.

People also ask: quick answers for security teams

Can authentication coercion succeed without local admin?

Yes. Many coercion techniques rely on RPC methods accessible to standard domain contexts. The attacker mainly needs network reachability to the target service.

Why are Domain Controllers and certificate services targeted so often?

Because coerced machine authentication can be relayed into privileged services. If attackers can turn a coerced authentication into a certificate or elevated token, the rest of the domain gets easier.

Is blocking one tool (like PrinterBug) enough?

No. Tool-specific blocking helps, but attackers are increasingly using less monitored protocols and opnums that don’t match popular signatures.

What to do next (and what not to do)

Authentication coercion keeps evolving because it feeds on two defender habits: over-trusting “normal Windows behavior,” and over-investing in detections tied to yesterday’s exploit.

The better approach is to combine hardening (reduce relay value, shrink RPC exposure) with AI-assisted anomaly detection (spot rare RPC + unusual authentication chains early). That pairing is what stops the attack before it becomes a domain story.

If you’re mapping priorities for 2026 planning, put this on the list: Tier 0 assets should have explicit RPC and authentication baselines, and your SOC should be able to answer, quickly, “Is this RPC behavior normal for this server role?”

What would your team see first in your environment—a rare RPC call, an unusual outbound authentication, or the damage that comes after?