SamSam Ransomware: Stop RDP Attacks With AI Defense

Most companies still treat ransomware as an email problem. SamSam is the counterexample that keeps proving them wrong.

SamSam (also tracked as MSIL/Samas) became notorious because it didn’t need a user to click anything. The operators frequently got in through Windows servers—first via vulnerable app servers (like JBoss), and later (more consistently) via Remote Desktop Protocol (RDP). Once inside, they moved fast: escalate privileges, drop payloads, and encrypt what they can reach across the network.

This matters a lot in late 2025. Hybrid work is normal, IT teams are lean, and exposed remote access paths still exist in surprising places—especially in cloud-hosted virtual machines and “temporary” admin setups. Traditional controls (a firewall rule, a SIEM alert, a weekly vulnerability scan) often spot SamSam-style intrusion after the attacker is already operating like a legitimate admin. The better approach is to pair hardening with AI-powered threat detection that can recognize the early behavioral signals of an RDP-based compromise.

Why SamSam worked: it attacked the access path, not the inbox

SamSam succeeded because it targeted the same tools admins rely on. That changes the detection problem.

Many ransomware families start with phishing and malware execution on an endpoint. Security teams have built a lot of muscle around that: email filtering, user training, endpoint protection, attachment sandboxing. SamSam’s operators often skipped the whole “user execution” step by entering through server-side weaknesses and remote access.

Two patterns showed up repeatedly in victim investigations:

Pattern 1: Exploit a known server weakness (early wave)

Early reporting tied some SamSam intrusions to exploiting vulnerable JBoss deployments using exploit kits. That playbook is straightforward: find an exposed service, exploit it, and implant a foothold.

It’s also the kind of thing that gets missed when patching is inconsistent or when owners don’t realize an internet-facing application server is still running an older, vulnerable configuration.

Pattern 2: Get in through RDP (later wave)

As time went on, RDP became a common entry point. RDP intrusions are hard because they can look like “normal work.” There’s no macro, no suspicious executable from a user’s Downloads folder—just a successful login.

SamSam operators commonly used:

• Brute force attempts against RDP
• Stolen credentials (often purchased from criminal marketplaces)

Once they have valid credentials, they can move from “external attacker” to “internal admin session” within hours.

A painful truth: if your detection strategy depends on spotting malware execution, you’re already late for ransomware that arrives via approved remote access.

The RDP problem in 2025: visibility gaps, not just open ports

The obvious fix is “close port 3389.” Do that whenever you can. But the bigger issue is knowing which remote access paths exist and whether they behave like you expect.

In real environments, RDP exposure tends to happen for predictable reasons:

• A cloud VM spun up for a project, given a public IP, and never fully hardened
• A vendor who “just needs RDP for maintenance,” and it becomes permanent
• A legacy server where RDP can’t be removed without disrupting operations
• An emergency troubleshooting change that never got rolled back

Even when RDP isn’t directly exposed to the internet, the risk remains if:

• VPN-connected devices are unmanaged or compromised
• Credentials are reused across systems
• Admin accounts aren’t protected with strong MFA
• Logs exist, but nobody is reviewing them with enough context

This is where AI in cybersecurity earns its keep: not by replacing basic hardening, but by connecting weak signals across identity, endpoint, and network activity fast enough to stop encryption.

How AI-powered threat detection spots SamSam-style intrusions earlier

AI is especially useful against SamSam-like ransomware because the earliest indicators are behavioral and distributed. No single alert tells the story. The story emerges from patterns.

Here’s what AI-driven detection can do well in this scenario.

Behavioral baselining for RDP and admin activity

A practical machine learning approach is to baseline “normal” for:

• Which accounts use RDP
• From which source IP ranges
• At what times
• To which servers
• With what follow-on activity (process launches, remote execution tools, credential dumping signals)

When an attacker logs in with valid credentials, the login itself may not look malicious. But the sequence often does.

Example signals AI models can flag with high confidence:

• First-time RDP login to a critical server by an account that never uses RDP
• “Impossible travel” patterns across sessions (geography or network segments)
• Login followed by rapid privilege escalation attempts
• A burst of remote admin actions across multiple hosts (enumeration, service creation, scheduled tasks)

Detecting ransomware staging before encryption starts

Ransomware operators typically prepare the environment: disable defenses, enumerate shares, locate backups, and distribute payloads.

AI-assisted detections can correlate:

• Suspicious PowerShell or cmd.exe usage after RDP session start
• Abnormal use of remote management tooling (for example, rapid lateral execution patterns)
• New persistence mechanisms appearing shortly after a new remote access session

Stopping SamSam is often about interrupting the staging phase. Once encryption begins across reachable hosts, response becomes a race you often lose.

Automated triage that reduces “alert debt”

A lot of teams have the right logs but not the time. AI can summarize what matters:

• “This account authenticated via RDP to 12 servers in 9 minutes, then created two new scheduled tasks and attempted to stop security services.”

That’s the difference between a 3-minute decision and a 3-hour investigation.

In the “AI in Cybersecurity” series, this is a recurring theme: the win isn’t more data—it’s faster clarity.

Hardening steps that actually reduce SamSam risk (and where teams slip)

SamSam prevention still depends on basics done well. The issue is most orgs do basics inconsistently.

Below is a set of controls that map directly to the intrusion patterns seen in SamSam incidents, with practical guidance for 2025 environments.

1) Audit and minimize RDP exposure

Start by finding every place RDP exists.

• Inventory systems using RDP internally and externally
• Disable RDP where it’s not required
• If RDP is required, restrict it to specific admin jump hosts

Common slip: RDP enabled “temporarily” during migration or vendor onboarding.

2) Don’t allow public RDP to cloud VMs

Public IP + open RDP is still one of the most expensive mistakes in security.

• Block inbound 3389 from the internet
• Put admin access behind a firewall and require VPN (or a secure remote access gateway)
• Apply cloud provider remote access best practices consistently

Common slip: A security group created for one VM gets copied across environments.

3) Strong passwords, lockouts, and MFA for remote access

Brute force becomes irrelevant when MFA is enforced correctly.

• Enforce long, unique passwords (passphrases work well)
• Turn on account lockout policies tuned to your environment
• Require MFA for RDP, VPN, and privileged actions

Common slip: MFA is enabled for VPN but not for direct RDP or privileged escalation.

4) Patch and update like you mean it

Ransomware operators love old, unpatched systems because they tend to be poorly monitored too.

• Patch internet-facing services first
• Maintain a cadence for OS and third-party software updates
• Validate patches with owners of critical systems, but don’t let “we’re busy” become “never”

Common slip: Servers are excluded from standard patch cycles due to fear of downtime.

5) Logging that’s usable during an incident

Logging only helps if it answers questions quickly.

• Capture RDP login events and keep logs for at least 90 days
• Centralize logs and protect them from tampering
• Regularly review for patterns, not just single events

Common slip: Logs roll off after 7–14 days, which is useless when you discover access was sold and reused over time.

6) Backups that survive ransomware

Backups are the difference between “incident” and “extortion.”

• Use offline or immutable backups
• Test restores quarterly (actually restore, don’t just verify a job ran)
• Separate backup admin credentials from domain admin

Common slip: Backups exist, but restore time is untested and exceeds the business’s tolerance.

A practical AI-assisted playbook for suspected RDP compromise

When SamSam-style ransomware hits, the highest-value time window is before encryption spreads. Here’s a playbook I’ve found teams can execute even under pressure.

Step 1: Contain the access path first

• Disable the suspected account(s)
• Block the source IPs (or isolate the VPN session)
• If feasible, isolate the accessed server from the network

Step 2: Ask AI to summarize the “session story”

If you have an AI-enabled SOC platform or analytics layer, use it to answer:

• What systems were accessed via RDP?
• What did the attacker do in the first 10 minutes after login?
• Which processes launched, and what remote actions followed?
• Were there signs of credential dumping or lateral movement?

The output you want is a short narrative and a prioritized list of impacted assets.

Step 3: Hunt for staging actions across hosts

Look for:

• Service stop attempts on security tools
• New scheduled tasks, new services, new admin shares
• Rapid authentication attempts across many hosts

AI can rank hosts by similarity to known “ransomware staging” sequences so your responders start where it’s hottest.

Step 4: Confirm backup integrity and recovery path

Do this during containment, not after.

• Validate backup snapshots aren’t accessible from compromised credentials
• Verify restore points and expected recovery time objectives

What to do next if you’re responsible for ransomware defense

SamSam is an older name, but the method is current: remote access + stolen credentials + fast lateral movement. If you’re still relying on perimeter rules and manual log review, you’re giving ransomware operators the time advantage.

A strong 2025 posture pairs two things:

• Hardening (reduce exposed RDP, enforce MFA, patch aggressively, keep resilient backups)
• AI-powered threat detection (spot abnormal RDP behavior and ransomware staging early enough to stop it)

If you want a quick gut check, ask yourself: would your team notice a valid RDP login from a “real” account… followed by 30 minutes of admin-like actions across servers? And would you notice it fast enough to stop encryption?

That’s the bar ransomware sets now. Are you meeting it—or just hoping you don’t become the next network-wide incident?