April 4, 2022

Explore Internet-Facing System Vulnerabilities

Read about 2021's top four incidents and how Darktrace's advanced threat detection technology identified and mitigated vulnerabilities. Learn more.

Written by

Sam Lister

SOC Analyst

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

Sam Lister

SOC Analyst

Apr 2022

By virtue of their exposure, Internet-facing systems (i.e., systems which have ports open/exposed to the wider Internet) are particularly susceptible to compromise. Attackers typically compromise Internet-facing systems by exploiting zero-day vulnerabilities in applications they run. During 2021, critical zero-day vulnerabilities in the following applications were publicly disclosed:

Microsoft Exchange
Confluence
GitLab
Log4j-using applications

Internet-facing systems running these applications were consequently heavily targeted by attackers. In this post, we will provide examples of compromises of these systems observed by Darktrace’s SOC team in 2021. As will become clear, successful exploitation of weaknesses in Internet-facing systems inevitably results in such systems doing things which they do not normally do. Rather than focusing on identifying attempts to exploit these weaknesses, Darktrace focuses on identifying the unusual behaviors which inevitably ensue. The purpose of this post is to highlight the effectiveness of this approach.

Exchange server compromise

In January, researchers from the cyber security company DEVCORE reported a series of critical vulnerabilities in Microsoft Exchange which they dubbed ‘ProxyLogon’.^[1] ProxyLogon consists of a server-side request forgery (SSRF) vulnerability (CVE-2021-26855) and a remote code execution (RCE) vulnerability (CVE-2021-27065). Attackers were observed exploiting these vulnerabilities in the wild from as early as January 6.^[2] In April, DEVCORE researchers reported another series of critical vulnerabilities in Microsoft Exchange which they dubbed ‘ProxyShell’.^[3] ProxyShell consists of a pre-authentication path confusion vulnerability (CVE-2021-34473), a privilege elevation vulnerability (CVE-2021-34523), and a post-authentication RCE vulnerability (CVE-2021-31207). Attackers were first observed exploiting these vulnerabilities in the wild in August.^[4] In many cases, attackers exploited the ProxyShell and ProxyLogon vulnerabilities in order to create web shells on the targeted Exchange servers. The presence of these web shells provided attackers with the means to remotely execute commands on the compromised servers.

In early August 2021, by exploiting the ProxyShell vulnerabilities, an attacker gained the rights to remotely execute PowerShell commands on an Internet-facing Exchange server within the network of a US-based transportation company. The attacker subsequently executed a number of PowerShell commands on the server. One of these commands caused the server to make a 28-minute-long SSL connection to a highly unusual external endpoint. Within a couple of hours, the attacker managed to strengthen their foothold within the network by installing AnyDesk and CobaltStrike on several internal devices. In mid-August, the attacker got the devices on which they had installed Cobalt Strike to conduct network reconnaissance and to transfer terabytes of data to the cloud storage service, MEGA. At the end of August, the attacker got the devices on which they had installed AnyDesk to execute Conti ransomware and to spread executable files and script files to further internal devices.

In this example, the attacker’s exploitation of ProxyShell immediately resulted in the Exchange Server making a long SSL connection to an unusual external endpoint. This connection caused the model Device / Long Agent Connection to New Endpoint to breach. The subsequent reconnaissance, lateral movement, C2, external data transfer, and encryption behavior brought about by the attacker were also picked up by Darktrace’s models.

A non-exhaustive list of the models that breached as a result of the behavior brought about by the attacker:

Device / Long Agent Connection to New Endpoint
Device / ICMP Address Scan
Anomalous Connection / SMB Enumeration
Anomalous Server Activity / Outgoing from Server
Compromise / Beacon to Young Endpoint
Anomalous Server Activity / Rare External from Server
Compromise / Fast Beaconing to DGA
Compromise / SSL or HTTP Beacon
Compromise / Sustained SSL or HTTP Increase
Compromise / Beacon for 4 Days
Anomalous Connection / Multiple HTTP POSTs to Rare Hostname
Unusual Activity / Enhanced Unusual External Data Transfer
Anomalous Connection / Data Sent to Rare Domain
Anomalous Connection / Uncommon 1 GiB Outbound
Compliance / SMB Drive Write
Anomalous File / Internal / Additional Extension Appended to SMB File
Anomalous Connection / Suspicious Read Write Ratio
Anomalous Connection / Suspicious Read Write Ratio and Unusual SMB
Anomalous Connection / Sustained MIME Type Conversion
Unusual Activity / Anomalous SMB Move & Write
Unusual Activity / Unusual Internal Data Volume as Client or Server
Device / Suspicious File Writes to Multiple Hidden SMB Shares
Compromise / Ransomware / Suspicious SMB Activity
Anomalous File / Internal / Unusual SMB Script Write
Anomalous File / Internal / Masqueraded Executable SMB Write
Device / SMB Lateral Movement
Device / Multiple Lateral Movement Model Breaches

Confluence server compromise

Atlassian’s Confluence is an application which provides the means for building collaborative, virtual workspaces. In the era of remote working, the value of such an application is undeniable. The public disclosure of a critical remote code execution (RCE) vulnerability (CVE-2021-26084) in Confluence in August 2021 thus provided a prime opportunity for attackers to cause havoc. The vulnerability, which arises from the use of Object-Graph Navigation Language (OGNL) in Confluence’s tag system, provides attackers with the means to remotely execute code on vulnerable Confluence server by sending a crafted HTTP request containing a malicious parameter.^[5] Attackers were first observed exploiting this vulnerability towards the end of August, and in the majority of cases, attackers exploited the vulnerability in order to install crypto-mining tools onto vulnerable servers.^[6]

At the beginning of September 2021, an attacker was observed exploiting CVE-2021-26084 in order to install the crypto-mining tool, XMRig, as well as a shell script, onto an Internet-facing Confluence server within the network of an EMEA-based television and broadcasting company. Within a couple of hours, the attacker installed files associated with the crypto-mining malware, Kinsing, onto the server. The Kinsing-infected server then immediately began to communicate over HTTP with the attacker’s C2 infrastructure. Around the time of this activity, the server was observed using the MinerGate crypto-mining protocol, indicating that the server had begun to mine cryptocurrency.

In this example, the attacker’s exploitation of CVE-2021-26084 immediately resulted in the Confluence server making an HTTP GET request with an unusual user-agent string (one associated with curl in this case) to a rare external IP. This behavior caused the models Device / New User Agent, Anomalous Connection / New User Agent to IP Without Hostname, and Anomalous File / Script from Rare Location to breach. The subsequent file downloads, C2 traffic and crypto-mining activity also resulted in several models breaching.

A non-exhaustive list of the models which breached as a result of the unusual behavior brought about by the attacker:

Device / New User Agent
Anomalous Connection / New User Agent to IP Without Hostname
Anomalous File / Script from Rare Location
Anomalous File / EXE from Rare External Location
Anomalous File / Internet Facing System File Download
Device / Initial Breach Chain Compromise
Anomalous Connection / Posting HTTP to IP Without Hostname
Compliance / Crypto Currency Mining Activity
Compromise / High Priority Crypto Currency Mining
Device / Internet Facing Device with High Priority Alert

GitLab server compromise

GitLab is an application providing services ranging from project planning to source code management. Back in April 2021, a critical RCE vulnerability (CVE-2021-22205) in GitLab was publicly reported by a cyber security researcher via the bug bounty platform, HackerOne.^[7] The vulnerability, which arises from GitLab’s use of ExifTool for removing metadata from image files, ^[8] enables attackers to remotely execute code on vulnerable GitLab servers by uploading specially crafted image files.^[9] Attackers were first observed exploiting CVE-2021-22205 in the wild in June/July.^[10] A surge in exploitations of the vulnerability was observed at the end of October, with attackers exploiting the flaw in order to assemble botnets.^[11] Darktrace observed a significant number of cases in which attackers exploited the vulnerability in order to install crypto-mining tools onto vulnerable GitLab servers.

On October 29, an attacker successfully exploited CVE-2021-22205 on an Internet-facing GitLab server within the network of a UK-based education provider. The organization was trialing Darktrace when this incident occurred. The attacker installed several executable files and shell scripts onto the server by exploiting the vulnerability. The attacker communicated with the compromised server (using unusual ports) for several days, before making the server transfer large volumes of data externally and download the crypto-mining tool, XMRig, as well as the botnet malware, Mirai. The server was consequently observed making connections to the crypto-mining pool, C3Pool.

In this example, the attacker’s exploitation of the vulnerability in GitLab immediately resulted in the server making an HTTP GET request with an unusual user-agent string (one associated with Wget in this case) to a rare external IP. The models Anomalous Connection / New User Agent to IP Without Hostname and Anomalous File / EXE from Rare External Location breached as a result of this behavior. The attacker’s subsequent activity on the server over the next few days resulted in frequent model breaches.

A non-exhaustive list of the models which breached as a result of the attacker’s activity on the server:

Anomalous Connection / New User Agent to IP Without Hostname
Anomalous File / EXE from Rare External Location
Anomalous File / Multiple EXE from Rare External Locations
Anomalous File / Internet Facing Device with High Priority Alert
Anomalous File / Script from Rare Location
Anomalous Connection / Application Protocol on Uncommon Port
Anomalous Connection / Anomalous SSL without SNI to New External
Device / Initial Breach Chain Compromise
Unusual Activity / Unusual External Data to New IPs
Anomalous Server Activity / Outgoing from Server
Device / Large Number of Model Breaches from Critical Network Device
Anomalous Connection / Data Sent to Rare Domain
Compromise / Suspicious File and C2
Unusual Activity / Enhanced Unusual External Data Transfer
Compliance / Crypto Currency Mining Activity
Compliance / High Priority Crypto Currency Mining
Anomalous File / Zip or Gzip from Rare External Location
Compromise / Monero Mining
Device / Internet Facing Device with High Priority Alert
Anomalous Server Activity / Rare External from Server
Compromise / Slow Beaconing Activity To External Rare
Compromise / Beaconing Activity To External Rare
Compromise / HTTP Beaconing to Rare Destination
Compromise / High Volume of Connections with Beacon Score
Anomalous File / Numeric Exe Download

Log4j server compromise

On December 9 2021, a critical RCE vulnerability (dubbed ‘Log4Shell’) in version 2 of Apache’s Log4j was publicly disclosed by researchers at LunaSec.^[12] As a logging library present in potentially millions of Java applications,^[13] Log4j constitutes an obscured, yet ubiquitous feature of the digital world. The vulnerability (CVE-2021-44228), which arises from Log4j’s Java Naming and Directory Interface (JNDI) Lookup feature, enables an attacker to make a vulnerable server download and execute a malicious Java class file. To exploit the vulnerability, all the attacker must do is submit a specially crafted JNDI lookup request to the server. The fact that Log4j is present in so many applications and that the exploitation of this vulnerability is so simple, Log4Shell has been dubbed the ‘most critical vulnerability of the last decade’.^[14] Attackers have been exploiting Log4Shell in the wild since at least December 1.^[15] Since then, attackers have been observed exploiting the vulnerability to install crypto-mining tools, Cobalt Strike, and RATs onto vulnerable servers.^[16]

On December 10, one day after the public disclosure of Log4Shell, an attacker successfully exploited the vulnerability on a vulnerable Internet-facing server within the network of a US-based architecture company. By exploiting the vulnerability, the attacker managed to get the server to download and execute a Java class file named ‘Exploit69ogQNSQYz.class’. Executing the code in this file caused the server to download a shell script file and a file related to the Kinsing crypto-mining malware. The Kinsing-infected server then went on to communicate over HTTP with a C2 server. Since the customer was using the Proactive Threat Notification (PTN) service, they were immediately alerted to this activity, and the server was subsequently quarantined, preventing crypto-mining activity from taking place.

In this example, the attacker’s exploitation of the zero-day vulnerability immediately resulted in the vulnerable server making an HTTP GET request with an unusual user-agent string (one associated with Java in this case) to a rare external IP. The models Anomalous Connection / Callback on Web Facing Device and Anomalous Connection / New User Agent to IP Without Hostname breached as a result of this behavior. The device’s subsequent file downloads and C2 activity caused several Darktrace models to breach.

A non-exhaustive list of the models which breached as a result of the unusual behavior brought about by the attacker:

Anomalous Connection / Callback on Web Facing Device
Anomalous Connection / New User Agent to IP Without Hostname
Anomalous File / Internet Facing System File Download
Anomalous File / Script from Rare External Location
Device / Initial Breach Chain Compromise
Anomalous Connection / Posting HTTP to IP Without Hostname

Round-up

It is inevitable that attackers will attempt to exploit zero-day vulnerabilities in applications running on Internet-facing devices. Whilst identifying these attempts is useful, the fact that attackers regularly exploit new zero-days makes the task of identifying attempts to exploit them akin to a game of whack-a-mole. Whilst it is uncertain which zero-day vulnerability attackers will exploit next, what is certain is that their exploitation of it will bring about unusual behavior. No matter the vulnerability, whether it be a vulnerability in Microsoft Exchange, Confluence, GitLab, or Log4j, Darktrace will identify the unusual behaviors which inevitably result from its exploitation. By identifying unusual behaviors displayed by Internet-facing devices, Darktrace thus makes it almost impossible for attackers to successfully exploit zero-day vulnerabilities without being detected.

For Darktrace customers who want to find out more about detecting potential compromises of internet-facing devices, refer here for an exclusive supplement to this blog.

Thanks to Andy Lawrence for his contributions.

Footnotes

1. https://devco.re/blog/2021/08/06/a-new-attack-surface-on-MS-exchange-part-1-ProxyLogon/

2. https://www.volexity.com/blog/2021/03/02/active-exploitation-of-microsoft-exchange-zero-day-vulnerabilities/

3. https://www.zerodayinitiative.com/blog/2021/8/17/from-pwn2own-2021-a-new-attack-surface-on-microsoft-exchange-proxyshell

4. https://www.rapid7.com/blog/post/2021/08/12/proxyshell-more-widespread-exploitation-of-microsoft-exchange-servers/

5. https://www.kaspersky.co.uk/blog/confluence-server-cve-2021-26084/23376/

6. https://www.bleepingcomputer.com/news/security/atlassian-confluence-flaw-actively-exploited-to-install-cryptominers/

7. https://hackerone.com/reports/1154542

8. https://security.humanativaspa.it/gitlab-ce-cve-2021-22205-in-the-wild/

9.https://about.gitlab.com/releases/2021/04/14/security-release-gitlab-13-10-3-released/

10. https://www.rapid7.com/blog/post/2021/11/01/gitlab-unauthenticated-remote-code-execution-cve-2021-22205-exploited-in-the-wild/

11. https://www.hackmageddon.com/2021/12/16/1-15-november-2021-cyber-attacks-timeline/

12. https://www.lunasec.io/docs/blog/log4j-zero-day/

13. https://www.csoonline.com/article/3644472/apache-log4j-vulnerability-actively-exploited-impacting-millions-of-java-based-apps.html

14. https://www.theguardian.com/technology/2021/dec/10/software-flaw-most-critical-vulnerability-log-4-shell

15. https://www.rapid7.com/blog/post/2021/12/15/the-everypersons-guide-to-log4shell-cve-2021-44228/

16. https://www.microsoft.com/security/blog/2021/12/11/guidance-for-preventing-detecting-and-hunting-for-cve-2021-44228-log4j-2-exploitation/

Written by

Sam Lister

SOC Analyst

Inside the SOC

Written by

Sam Lister

SOC Analyst

•

September 8, 2025

Emma Foulger

Global Threat Research Operations Lead

Product Marketing Manager, Network Detection & Response

Watch the NIS2 Webinar

Blog

Network

September 9, 2025

The benefits of bringing together network and email security

In many organizations, network and email security operate in isolation. Each solution is tasked with defending its respective environment, even though both are facing the same advanced, multi-domain threats.

This siloed approach overlooks a critical reality: email remains the most common vector for initiating cyber-attacks, while the network is the primary stage on which those attacks progress. Without direct integration between these two domains, organizations risk leaving blind spots that adversaries can exploit.

A modern security strategy needs to unify email and network defenses, not just in name, but in how they share intelligence, conduct investigations, and coordinate response actions. Let’s take a look at how this joined-up approach delivers measurable technical, operational, and commercial benefits.

Technical advantages

Pre-alert intelligence: Gathering data before the threat strikes

Most security tools start working when something goes wrong – an unusual login, a flagged attachment, a confirmed compromise. But by then, attackers may already be a step ahead.

By unifying network and email security under a single AI platform (like the Darktrace Active AI Security Platform), you can analyze patterns across both environments in real time, even when there are no alerts. This ongoing monitoring builds a behavioral understanding of every user, device, and domain in your ecosystem.

That means when an email arrives from a suspicious domain, the system already knows whether that domain has appeared on your network before – and whether its behavior has been unusual. Likewise, when new network activity involves a domain first spotted in an email, it’s instantly placed in the right context.

This intelligence isn’t built on signatures or after-the-fact compromise indicators – it’s built on live behavioral baselines, giving your defenses the ability to flag threats before damage is done.

Alert-related intelligence: Connecting the dots in real time

Once an alert does fire, speed and context matter. The Darktrace Cyber AI Analyst can automatically investigate across both environments, piecing together network and email evidence into a single, cohesive incident.

Instead of leaving analysts to sift through fragmented logs, the AI links events like a phishing email to suspicious lateral movement on the recipient’s device, keeping the full attack chain intact. Investigations that might take hours – or even days – can be completed in minutes, with far fewer false positives to wade through.

This is more than a time-saver. It ensures defenders maintain visibility after the first sign of compromise, following the attacker as they pivot into network infrastructure, cloud services, or other targets. That cross-environment continuity is impossible to achieve with disconnected point solutions or siloed workflows.

Operational advantages

Streamlining SecOps across teams

In many organizations, email security is managed by IT, while network defense belongs to the SOC. The result? Critical information is scattered between tools and teams, creating blind spots just when you need clarity.

When email and network data flow into a single platform, everyone is working from the same source of truth. SOC analysts gain immediate visibility into email threats without opening another console or sending a request to another department. The IT team benefits from the SOC’s deeper investigative context.

The outcome is more than convenience: it’s faster, more informed decision-making across the board.

Reducing time-to-meaning and enabling faster response

A unified platform removes the need to manually correlate alerts between tools, reducing time-to-meaning for every incident. Built-in AI correlation instantly ties together related events, guiding analysts toward coordinated responses with higher confidence.

Instead of relying on manual SIEM rules or pre-built SOAR playbooks, the platform connects the dots in real time, and can even trigger autonomous response actions across both environments simultaneously. This ensures attacks are stopped before they can escalate, regardless of where they begin.

Commercial advantages

While purchasing “best-of-breed" for all your different tools might sound appealing, it often leads to a patchwork of solutions with overlapping costs and gaps in coverage. However good a “best-in-breed" email security solution might be in the email realm, it won't be truly effective without visibility across domains and an AI analyst piecing intelligence together. That’s why we think “best-in-suite" is the only “best-in-breed" approach that works – choosing a high-quality platform ensures that every new capability strengthens the whole system.

On top of that, security budgets are under constant pressure. Managing separate vendors for email and network defense means juggling multiple contracts, negotiating different SLAs, and stitching together different support models.

With a single provider for both, procurement and vendor management become far simpler. You deal with one account team, one support channel, and one unified strategy for both environments. If you choose to layer on managed services, you get consistent expertise across your whole security footprint.

Even more importantly, an integrated AI platform sets the stage for growth. Once email and network are under the same roof, adding coverage for other attack surfaces – like cloud or identity – is straightforward. You’re building on the same architecture, not bolting on new point solutions that create more complexity.

Check out the white paper, The Modern Security Stack: Why Your NDR and Email Security Solutions Need to Work Together, to explore these benefits in more depth, with real-world examples and practical steps for unifying your defenses.

[related-resource]

About the author

Mikey Anderson

Product Marketing Manager, Network Detection & Response

Blog

September 9, 2025

Unpacking the Salesloft Incident: Insights from Darktrace Observations

Introduction

On August 26, 2025, Google Threat intelligence Group released a report detailing a widespread data theft campaign targeting the sales automation platform Salesloft, via compromised OAuth tokens used by the third-party Drift AI chat agent [1][2]. The attack has been attributed to the threat actor UNC6395 by Google Threat Intelligence and Mandiant [1].

The attack is believed to have begun in early August 2025 and continued through until mid-August 2025 [1], with the threat actor exporting significant volumes of data from multiple Salesforce instances [1]. Then sifting through this data for anything that could be used to compromise the victim’s environments such as access keys, tokens or passwords. This had led to Google Threat Intelligence Group assessing that the primary intent of the threat actor is credential harvesting, and later reporting that it was aware of in excess of 700 potentially impacted organizations [3].

Salesloft previously stated that, based on currently available data, customers that do not integrate with Salesforce are unaffected by this campaign [2]. However, on August 28, Google Threat Intelligence Group announced that “Based on new information identified by GTIG, the scope of this compromise is not exclusive to the Salesforce integration with Salesloft Drift and impacts other integrations” [2]. Google Threat Intelligence has since advised that any and all authentication tokens stored in or connected to the Drift platform be treated as potentially compromised [1].

This campaign demonstrates how attackers are increasingly exploiting trusted Software-as-a-Service (SaaS) integrations as a pathway into enterprise environment.

By abusing these integrations, threat actors were able to exfiltrate sensitive business data at scale, bypassing traditional security controls. Rather than relying on malware or obvious intrusion techniques, the adversaries leveraged legitimate credentials and API traffic that resembled legitimate Salesforce activity to achieve their goals. This type of activity is far harder to detect with conventional security tools, since it blends in with the daily noise of business operations.

The incident underscores the escalating significance of autonomous coverage within SaaS and third-party ecosystems. As businesses increasingly depend on interconnected platforms, visibility gaps become evident that cannot be managed by conventional perimeter and endpoint defenses.

By developing a behavioral comprehension of each organization's distinct use of cloud services, anomalies can be detected, such as logins from unexpected locations, unusually high volumes of API requests, or unusual document activity. These indications serve as an early alert system, even when intruders use legitimate tokens or accounts, enabling security teams to step in before extensive data exfiltration takes place

What happened?

The campaign is believed to have started on August 8, 2025, with malicious activity continuing until at least August 18. The threat actor, tracked as UNC6395, gained access via compromised OAuth tokens associated with Salesloft Drift integrations into Salesforce [1]. Once tokens were obtained, the attackers were able to issue large volumes of Salesforce API requests, exfiltrating sensitive customer and business data.

Initial Intrusion

The attackers first established access by abusing OAuth and refresh tokens from the Drift integration. These tokens gave them persistent access into Salesforce environments without requiring further authentication [1]. To expand their foothold, the threat actor also made use of TruffleHog [4], an open-source secrets scanner, to hunt for additional exposed credentials. Logs later revealed anomalous IAM updates, including unusual UpdateAccessKey activity, which suggested attempts to ensure long-term persistence and control within compromised accounts.

Internal Reconnaissance & Data Exfiltration

Once inside, the adversaries began exploring the Salesforce environments. They ran queries designed to pull sensitive data fields, focusing on objects such as Cases, Accounts, Users, and Opportunities [1]. At the same time, the attackers sifted through this information to identify secrets that could enable access to other systems, including AWS keys and Snowflake credentials [4]. This phase demonstrated the opportunistic nature of the campaign, with the actors looking for any data that could be repurposed for further compromise.

Lateral Movement

Salesloft and Mandiant investigations revealed that the threat actor also created at least one new user account in early September. Although follow-up activity linked to this account was limited, the creation itself suggested a persistence mechanism designed to survive remediation efforts. By maintaining a separate identity, the attackers ensured they could regain access even if their stolen OAuth tokens were revoked.

Accomplishing the mission

The data taken from Salesforce environments included valuable business records, which attackers used to harvest credentials and identify high-value targets. According to Mandiant, once the data was exfiltrated, the actors actively sifted through it to locate sensitive information that could be leveraged in future intrusions [1]. In response, Salesforce and Salesloft revoked OAuth tokens associated with Drift integrations on August 20 [1], a containment measure aimed at cutting off the attackers’ primary access channel and preventing further abuse.

How did the attack bypass the rest of the security stack?

The campaign effectively bypassed security measures by using legitimate credentials and OAuth tokens through the Salesloft Drift integration. This rendered traditional security defenses like endpoint protection and firewalls ineffective, as the activity appeared non-malicious [1]. The attackers blended into normal operations by using common user agents and making queries through the Salesforce API, which made their activity resemble legitimate integrations and scripts. This allowed them to operate undetected in the SaaS environment, exploiting the trust in third-party connections and highlighting the limitations of traditional detection controls.

Darktrace Coverage

Anomalous activities have been identified across multiple Darktrace deployments that appear associated with this campaign. This included two cases on customers based within the United States who had a Salesforce integration, where the pattern of activities was notably similar.

On August 17, Darktrace observed an account belonging to one of these customers logging in from the rare endpoint 208.68.36[.]90, while the user was seen active from another location. This IP is a known indicator of compromise (IoC) reported by open-source intelligence (OSINT) for the campaign [2].

Figure 1: Cyber AI Analyst Incident summarizing the suspicious login seen for the account.

The login event was associated with the application Drift, further connecting the events to this campaign.

Figure 2: Advanced Search logs showing the Application used to login.

Following the login, the actor initiated a high volume of Salesforce API requests using methods such as GET, POST, and DELETE. The GET requests targeted endpoints like /services/data/v57.0/query and /services/data/v57.0/sobjects/Case/describe, where the former is used to retrieve records based on a specific criterion, while the latter provides metadata for the Case object, including field names and data types [5,6].

Subsequently, a POST request to /services/data/v57.0/jobs/query was observed, likely to initiate a Bulk API query job for extracting large volumes of data from the Ingest Job endpoint [7,8].

Finally, a DELETE request to remove an ingestion job batch, possibly an attempt to obscure traces of prior data access or manipulation.

A case on another US-based customer took place a day later, on August 18. This again began with an account logging in from the rare IP 208.68.36[.]90 involving the application Drift. This was followed by Salesforce GET requests targeting the same endpoints as seen in the previous case, and then a POST to the Ingest Job endpoint and finally a DELETE request, all occurring within one minute of the initial suspicious login.

The chain of anomalous behaviors, including a suspicious login and delete request, resulted in Darktrace’s Autonomous Response capability suggesting a ‘Disable user’ action. However, the customer’s deployment configuration required manual confirmation for the action to take effect.

Figure 3: An example model alert for the user, triggered due to an anomalous API DELETE request.

Figure 4: Model Alert Event Log showing various model alerts for the account that ultimately led to an Autonomous Response model being triggered.

Conclusion

In conclusion, this incident underscores the escalating risks of SaaS supply chain attacks, where third-party integrations can become avenues for attacks. It demonstrates how adversaries can exploit legitimate OAuth tokens and API traffic to circumvent traditional defenses. This emphasizes the necessity for constant monitoring of SaaS and cloud activity, beyond just endpoints and networks, while also reinforcing the significance of applying least privilege access and routinely reviewing OAuth permissions in cloud environments. Furthermore, it provides a wider perspective into the evolution of the threat landscape, shifting towards credential and token abuse as opposed to malware-driven compromise.

‍

Credit to Emma Foulger (Global Threat Research Operations Lead), Calum Hall (Technical Content Researcher), Signe Zaharka (Principal Cyber Analyst), Min Kim (Senior Cyber Analyst), Nahisha Nobregas (Senior Cyber Analyst), Priya Thapa (Cyber Analyst)

Appendices

Darktrace Model Detections

· SaaS / Access / Unusual External Source for SaaS Credential Use

· SaaS / Compromise / Login From Rare Endpoint While User Is Active

· SaaS / Compliance / Anomalous Salesforce API Event

· SaaS / Unusual Activity / Multiple Unusual SaaS Activities

· Antigena / SaaS / Antigena Unusual Activity Block

· Antigena / SaaS / Antigena Suspicious Source Activity Block

Customers should consider integrating Salesforce with Darktrace where possible. These integrations allow better visibility and correlation to spot unusual behavior and possible threats.