Blog
/
/
May 14, 2019

[Part 1] 10 Cyber Hygiene Issues Leading to a Security Breach

Spotting cyber hygiene issues caused by a lapse of attention requires AI tools that alert critical changes to network activity. Read part one here!
Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
Max Heinemeyer
Global Field CISO
Default blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog image
14
May 2019

For as long as people have sought to protect their assets from intrusion, they have safeguarded those assets behind ever more formidable walls, from castle walls made of stone to firewalls comprised of code. Yet no matter how impenetrable such fortifications appear, motivated attackers will inevitably find a way to bypass them. Build a 50-foot fence, and the enemy will bring a 50-foot ladder. Install state-of-the-art endpoint security on every employee’s computer, and cyber-criminals will infiltrate via the smart refrigerator in the office kitchen.

Needless to say, reinforcing the perimeter is still a good idea. Just as a castle in ruins makes a poor home for a king, so too do weak endpoint defenses put intellectual property and sensitive data at risk. The reality, however, is that digital environments are exponentially more difficult to wall off than physical ones, given the sheer number of applications and users that can compromise an entire network with just a single vulnerability or oversight. Improving a company’s cyber hygiene is therefore a continual responsibility, the nature of which perpetually changes as the business evolves.

Because even flawless cyber hygiene isn’t guaranteed to keep external attackers — let alone malicious insiders — from breaching the perimeter, leading companies and governments have turned to cyber AI technologies. Cyber AI works by learning the particular behaviors of a network and its users, allowing it to pick up on the subtly anomalous activity associated with an already infected device. Such technologies have shined a light on ten of the most commonly exploited cyber hygiene issues, five of which are examined below. And whereas there is no silver bullet when it comes to securing the enterprise online, patching these holes in the perimeter is nevertheless a critical first step.

Issue #1: Using SMBv1 — for anything

Server Message Block (SMB) is a very common application layer protocol that provides shared access to files, printers, and serial ports to devices in a network. The latest version, SMBv3, was developed with security in mind, whereas the original version, SMBv1, is more than three decades old and — in Microsoft’s own words — “was designed for a world that no longer exists[;] a world without malicious actors.” As a result, Microsoft has long implored users to stop using it in the strongest possible terms.

However, many of these users still have not disabled the protocol on operating systems older than Windows 8.1 and Windows Server 2012 R2, which do not allow SMB1 to be removed. The 2017 WannaCry ransomware attack abused the famous exploit EternalBlue in SMBv1 to infect Windows machines and move laterally in Windows environments, precipitating billions of dollars in global losses. Furthermore, SMBv1 allows NTLM logins using the anonymous credential by default, while successful anonymous logins can allow attackers to enumerate the target device for more information.

In light of the serious security risks that SMBv1 introduces, Darktrace flags its usage as threatening with the following models:

  • Anomalous Connection / Unusual SMB Version 1 Connectivity
  • Compliance / SMB Version 1 Usage

Issue #2: SMB services exposed to the internet

As mentioned above, SMB allows devices in a network to communicate with one another for a variety of purposes — functionalities that render it a complex protocol with many known vulnerabilities. Users are consequently highly discouraged from allowing connections from the internet to internal devices via any version of SMB — not just SMBv1.

Darktrace detected this poor hygiene practice in early 2019, when it observed the use of SMB from external IP addresses connecting to an internal device. The device happened to be a Domain Controller (DC), a server which manages network security and is responsible for user authentication. Due to the critical network function performed by this server, it is a high value target for cyber-criminals, meaning that any external connections should be limited to only essential administrative activity. In this incident, the external device was seen accessing the DC via SMBv1 and performing anonymous login. Fortunately, Darktrace AI detected the potential compromise with the model Compliance / External Windows Communications.

Issue #3: RDP services exposed to the internet

Microsoft’s proprietary Remote Desktop Protocol (RDP) provides a remote connection to a network-connected computer, affording users significant control over another device and its resources. Such extensive capabilities represent the holy grail for attackers, whether they seek to gain an initial foothold in the network, access restricted content, or directly drop malware on the controlled computer. Exposing devices with RDP services to the internet therefore creates a significant vulnerability in the network perimeter, as passwords and user credentials are liable to be brute-forced by those with malign intent.

Last month, Darktrace’s cyber AI detected a large number of incoming connections over the RDP protocol to a customer’s internet-facing device — possible indicators of a brute-force attack. While this activity might have been benign under different circumstances, the AI’s understanding of ‘self’ versus ‘not self’ for the particular device in question enabled it to flag the connections as anomalous, since they breached its Compliance / Incoming RDP from Rare Endpoints model.

By investigating further with Darktrace’s device tracking capability, we can see that the computer also breached several other AI models, including Compliance / Crypto Currency Mining Activity, Compliance / Outbound RDP, and Compromise / Beaconing Activity to External Rare. These breaches suggest that the attackers might have sought to use the computer to plant crypto-mining modules on other network-connected devices.

Models that the device breached within three days

Issue #4: Data uploads to unapproved cloud services

No innovation has antiquated the perimeter-only approach to cyber security more than cloud computing, since cloud and hybrid infrastructures have nebulous borders at best. Nevertheless, there are a number of bad cyber hygiene habits that make bypassing perimeter defenses much easier, including employees who upload data to close storage providers that are not on an organization’s approved list. Whether done maliciously or inadvertently, this decision prevents organizations from gaining any visibility over that data being transferred across the globe.

Darktrace cyber AI detects such unauthorized data movements with the following models:

  • Anomalous Connection / Data Sent To New External Device
  • Unusual Activity / Unusual External Data Transfer

Issue #5: Weak password usage and storage

Among the most common and most avoidable cyber-attacks are those that exploit systems with weak passwords, which can be breached by brute-force or dictionary attacks. Yet stronger, more complex passwords introduce a separate problem: because they are harder to be remember, users tend to store these passwords in sometimes unsafe locations. Whereas passwords housed in encrypted mediums such as password managers are relatively secure, many users instead save them in cleartext. Several modern strains of malware possess the ability to comb through the network in search of possible files which contains passwords, rendering this a critical vulnerability.

Darktrace has a set of models to spot such attempts at password guessing:

  • Device / SMB Session Bruteforce
  • Unusual Activity / Large Volume of Kerberos Failures
  • User / Kerberos Password Bruteforce
  • SaaS / Login Bruteforce Attempt

Darktrace also has a set of models that flag anomalous password storage or access:

  • Compliance / Sensitive Terms in Unusual SMB Connection
  • Compliance / Possible Unencrypted Password Storage
  • SaaS / Unusual SaaS Sensitive File Access

Read the second part: Part two — The perils of convenience

Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
Max Heinemeyer
Global Field CISO

More in this series

No items found.

Blog

/

Identity

/

July 3, 2025

Top Eight Threats to SaaS Security and How to Combat Them

Default blog imageDefault blog image

The latest on the identity security landscape

Following the mass adoption of remote and hybrid working patterns, more critical data than ever resides in cloud applications – from Salesforce and Google Workspace, to Box, Dropbox, and Microsoft 365.

On average, a single organization uses 130 different Software-as-a-Service (SaaS) applications, and 45% of organizations reported experiencing a cybersecurity incident through a SaaS application in the last year.

As SaaS applications look set to remain an integral part of the digital estate, organizations are being forced to rethink how they protect their users and data in this area.

What is SaaS security?

SaaS security is the protection of cloud applications. It includes securing the apps themselves as well as the user identities that engage with them.

Below are the top eight threats that target SaaS security and user identities.

1.  Account Takeover (ATO)

Attackers gain unauthorized access to a user’s SaaS or cloud account by stealing credentials through phishing, brute-force attacks, or credential stuffing. Once inside, they can exfiltrate data, send malicious emails, or escalate privileges to maintain persistent access.

2. Privilege escalation

Cybercriminals exploit misconfigurations, weak access controls, or vulnerabilities to increase their access privileges within a SaaS or cloud environment. Gaining admin or superuser rights allows attackers to disable security settings, create new accounts, or move laterally across the organization.

3. Lateral movement

Once inside a network or SaaS platform, attackers move between accounts, applications, and cloud workloads to expand their foot- hold. Compromised OAuth tokens, session hijacking, or exploited API connections can enable adversaries to escalate access and exfiltrate sensitive data.

4. Multi-Factor Authentication (MFA) bypass and session hijacking

Threat actors bypass MFA through SIM swapping, push bombing, or exploiting session cookies. By stealing an active authentication session, they can access SaaS environments without needing the original credentials or MFA approval.

5. OAuth token abuse

Attackers exploit OAuth authentication mechanisms by stealing or abusing tokens that grant persistent access to SaaS applications. This allows them to maintain access even if the original user resets their password, making detection and mitigation difficult.

6. Insider threats

Malicious or negligent insiders misuse their legitimate access to SaaS applications or cloud platforms to leak data, alter configurations, or assist external attackers. Over-provisioned accounts and poor access control policies make it easier for insiders to exploit SaaS environments.

7. Application Programming Interface (API)-based attacks

SaaS applications rely on APIs for integration and automation, but attackers exploit insecure endpoints, excessive permissions, and unmonitored API calls to gain unauthorized access. API abuse can lead to data exfiltration, privilege escalation, and service disruption.

8. Business Email Compromise (BEC) via SaaS

Adversaries compromise SaaS-based email platforms (e.g., Microsoft 365 and Google Workspace) to send phishing emails, conduct invoice fraud, or steal sensitive communications. BEC attacks often involve financial fraud or data theft by impersonating executives or suppliers.

BEC heavily uses social engineering techniques, tailoring messages for a specific audience and context. And with the growing use of generative AI by threat actors, BEC is becoming even harder to detect. By adding ingenuity and machine speed, generative AI tools give threat actors the ability to create more personalized, targeted, and convincing attacks at scale.

Protecting against these SaaS threats

Traditionally, security leaders relied on tools that were focused on the attack, reliant on threat intelligence, and confined to a single area of the digital estate.

However, these tools have limitations, and often prove inadequate for contemporary situations, environments, and threats. For example, they may lack advanced threat detection, have limited visibility and scope, and struggle to integrate with other tools and infrastructure, especially cloud platforms.

AI-powered SaaS security stays ahead of the threat landscape

New, more effective approaches involve AI-powered defense solutions that understand the digital business, reveal subtle deviations that indicate cyber-threats, and action autonomous, targeted responses.

[related-resource]

Continue reading
About the author
Carlos Gray
Senior Product Marketing Manager, Email

Blog

/

Proactive Security

/

July 2, 2025

Pre-CVE Threat Detection: 10 Examples Identifying Malicious Activity Prior to Public Disclosure of a Vulnerability

Default blog imageDefault blog image

Vulnerabilities are weaknesses in a system that can be exploited by malicious actors to gain unauthorized access or to disrupt normal operations. Common Vulnerabilities and Exposures (or CVEs) are a list of publicly disclosed cybersecurity vulnerabilities that can be tracked and mitigated by the security community.

When a vulnerability is discovered, the standard practice is to report it to the vendor or the responsible organization, allowing them to develop and distribute a patch or fix before the details are made public. This is known as responsible disclosure.

With a record-breaking 40,000 CVEs reported for 2024 and a predicted higher number for 2025 by the Forum for Incident Response and Security Teams (FIRST) [1], anomaly-detection is essential for identifying these potential risks. The gap between exploitation of a zero-day and disclosure of the vulnerability can sometimes be considerable, and retroactively attempting to identify successful exploitation on your network can be challenging, particularly if taking a signature-based approach.

Detecting threats without relying on CVE disclosure

Abnormal behaviors in networks or systems, such as unusual login patterns or data transfers, can indicate attempted cyber-attacks, insider threats, or compromised systems. Since Darktrace does not rely on rules or signatures, it can detect malicious activity that is anomalous even without full context of the specific device or asset in question.

For example, during the Fortinet exploitation late last year, the Darktrace Threat Research team were investigating a different Fortinet vulnerability, namely CVE 2024-23113, for exploitation when Mandiant released a security advisory around CVE 2024-47575, which aligned closely with Darktrace’s findings.

Retrospective analysis like this is used by Darktrace’s threat researchers to better understand detections across the threat landscape and to add additional context.

Below are ten examples from the past year where Darktrace detected malicious activity days or even weeks before a vulnerability was publicly disclosed.

ten examples from the past year where Darktrace detected malicious activity days or even weeks before a vulnerability was publicly disclosed.

Trends in pre-cve exploitation

Often, the disclosure of an exploited vulnerability can be off the back of an incident response investigation related to a compromise by an advanced threat actor using a zero-day. Once the vulnerability is registered and publicly disclosed as having been exploited, it can kick off a race between the attacker and defender: attack vs patch.

Nation-state actors, highly skilled with significant resources, are known to use a range of capabilities to achieve their target, including zero-day use. Often, pre-CVE activity is “low and slow”, last for months with high operational security. After CVE disclosure, the barriers to entry lower, allowing less skilled and less resourced attackers, like some ransomware gangs, to exploit the vulnerability and cause harm. This is why two distinct types of activity are often seen: pre and post disclosure of an exploited vulnerability.

Darktrace saw this consistent story line play out during several of the Fortinet and PAN OS threat actor campaigns highlighted above last year, where nation-state actors were seen exploiting vulnerabilities first, followed by ransomware gangs impacting organizations [2].

The same applies with the recent SAP Netweaver exploitations being tied to a China based threat actor earlier this spring with subsequent ransomware incidents being observed [3].

Autonomous Response

Anomaly-based detection offers the benefit of identifying malicious activity even before a CVE is disclosed; however, security teams still need to quickly contain and isolate the activity.

For example, during the Ivanti chaining exploitation in the early part of 2025, a customer had Darktrace’s Autonomous Response capability enabled on their network. As a result, Darktrace was able to contain the compromise and shut down any ongoing suspicious connectivity by blocking internal connections and enforcing a “pattern of life” on the affected device.

This pre-CVE detection and response by Darktrace occurred 11 days before any public disclosure, demonstrating the value of an anomaly-based approach.

In some cases, customers have even reported that Darktrace stopped malicious exploitation of devices several days before a public disclosure of a vulnerability.

For example, During the ConnectWise exploitation, a customer informed the team that Darktrace had detected malicious software being installed via remote access. Upon further investigation, four servers were found to be impacted, while Autonomous Response had blocked outbound connections and enforced patterns of life on impacted devices.

Conclusion

By continuously analyzing behavioral patterns, systems can spot unusual activities and patterns from users, systems, and networks to detect anomalies that could signify a security breach.

Through ongoing monitoring and learning from these behaviors, anomaly-based security systems can detect threats that traditional signature-based solutions might miss, while also providing detailed insights into threat tactics, techniques, and procedures (TTPs). This type of behavioral intelligence supports pre-CVE detection, allows for a more adaptive security posture, and enables systems to evolve with the ever-changing threat landscape.

Credit to Nathaniel Jones (VP, Security & AI Strategy, Field CISO), Emma Fougler (Global Threat Research Operations Lead), Ryan Traill (Analyst Content Lead)

References and further reading:

  1. https://www.first.org/blog/20250607-Vulnerability-Forecast-for-2025
  2. https://cloud.google.com/blog/topics/threat-intelligence/fortimanager-zero-day-exploitation-cve-2024-47575
  3. https://thehackernews.com/2025/05/china-linked-hackers-exploit-sap-and.html

Related Darktrace blogs:

*Self-reported by customer, confirmed afterwards.

**Updated January 2024 blog now reflects current findings

Continue reading
About the author
Nathaniel Jones
VP, Security & AI Strategy, Field CISO
Your data. Our AI.
Elevate your network security with Darktrace AI