AI Defense for SAP Exploits Hiding in Plain Sight

About 900 U.S. SAP Gateways were observed in a configuration where anonymous users could potentially run operating system commands. That number didn’t come from a vendor marketing deck—it came from a security conference analysis referenced in a CISA activity alert about public exploit tooling aimed at unsecured SAP configurations.

Most companies get this wrong: they treat SAP exposure as a “patching problem.” The reality is that a lot of SAP compromise paths start earlier—at misconfiguration, unintended internet exposure, and weak segmentation. And when attackers can probe thousands of SAP endpoints at scale, defenders need something equally scalable.

This post is part of our AI in Cybersecurity series, and SAP is a perfect case study. SAP estates are sprawling, customized, and business-critical. When they’re exposed, attackers don’t need novel zero-days—they need time, scanning, and an overlooked setting. AI-powered threat detection is one of the few practical ways to monitor that kind of environment continuously without burning out your security team.

What CISA’s SAP alert still gets painfully right

CISA’s alert (AA19-122A) focused on exploit tools targeting SAP components with insecure configurations exposed to the internet. Even though the advisory is archived, the lesson is current: enterprise systems that were never meant to be public-facing keep ending up public-facing.

Three SAP surfaces called out in the alert show up repeatedly in real incident response because they sit at the intersection of connectivity and trust:

• SAP Gateway (RFC communication between SAP and non-SAP apps)
• SAP Router (connectivity broker between networks)
• SAP Message Server (broker between application servers)

The core failure mode is consistent: a component is reachable from an untrusted network, and access controls default to permissive (or were left permissive to “get things working”). Attackers then use public tooling to turn that reachability into execution, credential capture, or lateral movement.

Here’s the stance I’ll take: if your SAP security posture relies on “we don’t expose SAP,” you don’t have a posture—you have a hope.

How the “10KBLAZE” style attacks work (and why they scale)

The advisory referenced exploit tooling often described under the “10KBLAZE” label. The important point isn’t the brand name; it’s the pattern: repeatable exploitation against repeatable misconfigurations.

SAP Gateway ACL mistakes: when gw/acl_mode becomes a breach

CISA highlighted SAP Gateway access control lists (ACLs) and noted that insecure settings (for example gw/acl_mode = 0) can enable anonymous users to run OS commands.

Why this is so attractive to attackers:

• It’s easy to scan for SAP Gateway exposure.
• Misconfiguration tends to be stable (it doesn’t “accidentally fix itself”).
• The impact can jump quickly from “SAP component reachable” to OS command execution.

From a defender’s perspective, this is a nightmare class of issue because the exploit is fast, but the root cause is slow: legacy landscapes, fragile integrations, undocumented exceptions, and change control that discourages tightening.

SAP Router secinfo: the proxy you didn’t mean to build

The SAP router often exists to help connect SAP systems with external networks. The advisory warned that default secinfo behavior for SAP Gateway can allow OS commands anonymously from internal hosts—and a misconfigured router can effectively act as that “internal host,” proxying attacker requests.

In practical terms, a router reachable from the internet can become a stepping stone into the SAP interior if you haven’t:

• Locked down router access rules
• Restricted which internal endpoints the router can reach
• Audited secinfo policies to prevent anonymous command execution paths

This is one reason SAP incidents feel like they “came out of nowhere.” The visible exposed service is the router, but the damage lands deeper.

SAP Message Server exposure: credential theft before malware

CISA noted Message Servers often listen on port patterns like 39XX and may lack authentication by default. If exposed, attackers can redirect legitimate traffic or perform man-in-the-middle style moves to gain credentials, then use those credentials to execute operations on application servers.

This is the part many teams underestimate: you can lose SAP without a loud exploit chain. Credential capture and session manipulation can be quieter than dropping malware, especially in environments where SAP logs are fragmented and SOC teams don’t have strong SAP telemetry.

The uncomfortable truth: “Not intended for the internet” doesn’t stop attackers

SAP components “typically are not intended to be exposed to the internet,” as the alert put it. That’s accurate—and also incomplete as a defense strategy.

In late 2025, the ways SAP ends up exposed are depressingly routine:

• Cloud migrations that replicate network rules incorrectly
• Temporary vendor access that becomes permanent
• Overly broad firewall objects (“any to SAP subnet”) justified by integration pressure
• Shadow IT connectors and third-party monitoring agents
• Public IPs attached to legacy hosts during datacenter transitions

Attackers don’t care that SAP wasn’t meant to be public. They care that it answers.

What helps is building a program that assumes exposure attempts are constant and asks a different question:

Can we detect SAP misuse early enough to stop it—even when someone makes a networking mistake?

That’s where AI earns its keep.

Where AI actually helps with SAP threat detection (no hype)

AI in cybersecurity is only useful when it reduces time-to-detection and time-to-response in messy environments. SAP estates are exactly that: messy, business-critical, and full of “special cases.”

Here are AI use cases that map cleanly to the behaviors in the CISA alert.

1) Internet exposure discovery that doesn’t rely on spreadsheets

Answer first: AI can continuously spot SAP services that become externally reachable and escalate risk based on what the service is and how it behaves.

Traditional asset inventory fails because SAP landscapes change faster than documentation. AI-assisted attack surface management can:

• Detect new listening services consistent with SAP Gateway/Router/Message Server fingerprints
• Correlate exposure with recent infrastructure changes (new security group, new NAT rule, new load balancer)
• Prioritize “reachable and sensitive” over “reachable and low impact”

The payoff is speed. You want hours, not quarters.

2) Anomaly detection for SAP protocols and command execution patterns

Answer first: AI models can baseline “normal” RFC and message server behavior and flag deviations that look like exploitation or credential-harvesting.

For example, exploitation attempts often create telltale patterns:

• Unusual function/module calls compared to baseline
• Spikes in connections from unfamiliar sources
• Repeated failed attempts followed by a successful call pattern
• Access at odd hours for that specific system (not generic “odd hours”)

This matters because SAP traffic often looks “weird” to generic network tools. AI systems trained on enterprise telemetry (NetFlow, DNS, EDR, identity, and SAP logs where available) can surface the deviations with fewer false positives than brittle rules.

3) Faster triage: joining SAP events to identity and endpoint data

Answer first: AI reduces investigation time by stitching together evidence across systems your analysts don’t have time to manually correlate.

A common SAP incident question is simple and painful: “Is this an admin doing maintenance, or an attacker?”

AI-assisted SOC workflows can correlate:

• SAP authentication events with SSO/IdP logs
• New SAP service exposure with firewall and cloud config changes
• OS command execution indicators with EDR telemetry on the host
• Lateral movement signals (Kerberos oddities, SMB spikes, new remote services)

When this works, you don’t just detect faster—you decide faster.

4) Automated response that’s safe for ERP uptime

Answer first: AI can recommend and execute low-risk containment actions that protect SAP without crashing the business.

Containment in ERP environments is tricky. “Just isolate the server” can stop payroll, invoicing, shipping, or plant operations.

Good automation focuses on reversible, scoped actions, such as:

• Blocking a suspicious source IP at the edge (temporary)
• Tightening an ACL on a specific SAP component path
• Forcing step-up authentication for privileged SAP roles
• Disabling a single exposed service listener while leaving core processing intact

You still want humans in the loop for high-impact actions, but you don’t want humans doing every low-impact step manually at 3 a.m.

A practical mitigation plan you can execute in weeks

CISA’s mitigations were direct: secure configuration, restrict access, and scan for exposure. That’s still the backbone. The difference in 2025 is execution: teams need a plan that fits modern hybrid estates and security operations realities.

Week 1: Prove what’s exposed (don’t assume)

• Inventory all SAP Gateways, SAP Routers, and Message Servers (prod and non-prod)
• Validate which ones are reachable from the internet and from partner networks
• Confirm whether Message Server ports like 39XX are accessible beyond intended clients

Deliverable: a short list of “internet reachable” SAP components with owners and business impact.

Week 2: Fix the highest-risk configs first

Prioritize misconfigurations that enable anonymous access or command execution paths:

• Tighten SAP Gateway ACL behavior (review gw/acl_mode and associated ACL files)
• Review and harden router rules and secinfo behavior
• Restrict Message Server access and ensure ACL protection is in place

Deliverable: a change set that reduces exposure without waiting for a full SAP upgrade.

Week 3: Add detection that your SOC can actually use

• Build detections for SAP component exposure changes (edge + cloud)
• Baseline normal SAP traffic patterns and alert on deviations
• Integrate SAP events into SOC workflows (identity + endpoint + network)

Deliverable: alerts that are routed to the right team with enough context to act.

Week 4: Add guardrails so it doesn’t regress

• Implement continuous scanning for exposed SAP services
• Add policy checks to infrastructure change pipelines (cloud security posture)
• Define “SAP internet exposure” as a high-severity control failure

Deliverable: prevention and fast detection so the same problem doesn’t return next quarter.

People also ask: “Do we need AI if we already have SIEM rules?”

Answer first: If your SAP environment is stable, fully logged, and tightly segmented, rules might be enough. Most environments aren’t.

Rules are great for known, consistent patterns. SAP estates tend to have:

• Incomplete logging coverage
• Custom code and integrations that change traffic patterns
• Third-party access that blurs “normal”
• High cost of false positives (because every alert involves business owners)

AI doesn’t replace rules; it prioritizes and correlates so rules don’t drown you.

The lead-gen question that matters: can you prove you’d catch this?

CISA’s alert highlighted a simple, repeatable reality: attackers target unsecured SAP configurations because they work. If you run SAP for finance, HR, supply chain, utilities, healthcare, or government operations, the blast radius isn’t theoretical.

If you’re leading security operations, here’s what I’d pressure-test before the year ends:

• Can we detect an SAP component becoming internet reachable within 24 hours?
• Can we tell the difference between a maintenance RFC call and exploit-like behavior?
• Can we contain suspicious SAP access without taking the business down?

If any of those answers are “not really,” AI-powered threat detection and response isn’t a nice-to-have—it’s the only way to scale coverage across a complex SAP landscape.

What would your SOC see first: the exposed port, or the invoice fraud two weeks later?